Digital Commons Network^™

Philopatry, Mate Fidelity, And Nest-Site Fidelity For South Polar Skuas Stercorarius Maccormicki At The Vestfold Hills, East Antarctica, John Van Den Hoff, Kris Carlyon, Louise Emmerson, Clive R. Mcmahon, Gary D. Miller

Marine Ornithology

Antarctica experiences continual spatial and temporal expansions in human activities, but information to understand how resident species may be impacted is usually inadequate. We analysed resights of South Polar Skuas Stercorarius maccormicki that were individually marked with leg rings during 1999–2004 to compare breeding behaviours such as philopatry, adult mate fidelity, and site fidelity in the Vestfold Hills population, East Antarctica, with other regions. Despite their impressive dispersal capabilities, philopatry for birds resighted in the study area was within 4 km of the natal nest, and adult nest-fidelity was within 1 km of a previous nest site. Such faithfulness to …

A Common Tern Sterna Hirundo Capturing An Airborne Flying Squid: A Novel Foraging Technique?, Angelico Jose C. Tiongson

Marine Ornithology

Seabirds forage in the air-water interface and have adapted various feeding techniques to exploit resources at or beneath the surface. Here I present photographic evidence of a novel feeding technique by an Eastern Common Tern Sterna hirundo longipennis: the capture of an airborne flying squid. Terns are generally plunge-divers for fish or shrimp, but they are also known to feed extensively on insects and occasionally by kleptoparasitism. Aerial pursuit/capture may be more common among seabirds in areas where flying prey are abundant. This new observation highlights the opportunistic nature and flexibility of seabirds in obtaining prey, as well as the …

Hatching Success Of Common Murres Uria Aalge Is Linked To The Number Of Neighbours And Resource Availability, Amy L. Irvine, Julia E. Gulka, Gail K. Davoren

Marine Ornithology

When breeding within densely populated colonies, seabirds benefit from increased offspring protection from predators, but intraspecific competition for resources may outweigh these benefits. We tested whether the number of breeding-site neighbours and days of predator presence influenced the breeding performance of Common Murres Uria aalge at two different-sized colonies off the northeastern Newfoundland coast: Cabot Island (10000 breeding pairs; < 10 km offshore) and Funk Island (500000 breeding pairs; ~60 km offshore). Gulls, the main predators of murre eggs/chicks, inhabit both islands in similar numbers. During July–August 2018, camera traps placed at topographically similar plots on each colony recorded breeding performance metrics (i.e., hatching, fledging, reproductive success), number of breeding-site neighbours, and daily presence of gulls. Hatching success was lower at Funk Island (64.7%) than Cabot Island (96.2%), but nearly all hatched chicks fledged at both colonies. Lower hatching success at Funk Island was due to higher egg abandonment and predation. It was also associated with fewer breeding-site neighbours, including non-brooding mates and non-breeders, along with higher gull presence (96.6% of all gull sightings at both colonies). Fewer neighbours at Funk Island may have resulted from mates and non-breeding murres spending more time at sea due to longer distances to predictable foraging sites and higher conspecific densities relative to Cabot Island. In turn, with fewer breeding-site neighbours at Funk Island, parents appeared less able to defend against or deter gull predation. Although Funk Island has special conservation status, protection of Cabot Island may also be important for the long-term conservation of murres in Newfoundland.

Distribution Patterns And Population Size Of The Ashy Storm Petrel Oceanodroma Homochroa, R. Glenn Ford, Scott Terrill, Janet Casey, Debi Shearwater, Stephanie R. Schneider, Lisa T. Balance, Linda Terrill, Margot Tollefson, David G. Ainley

Marine Ornithology

The Ashy Storm Petrel (ASSP) Oceanodroma homochroa population has been surveyed intensively, both at sea within the California Current and on the adjacent breeding grounds. Nevertheless, colony-based estimates of breeding populations have significantly underestimated the species’ abundance, especially in the northern portion of its range compared to the southern portion. The species has been described as abundant in central-northern waters, whereas it is considered rare or uncommon in the southern portion. We analyzed aerial and ship tracks from 1980 to 2017 (~497000 km covering 91267 km2 ), to estimate total ASSP population size and at-sea distribution. Modeling the results of …

Motionfusion: A Robust Ensemble Learning Framework For Accurate Sensor-Based Human Activity Recognition, Hussein K. Almulla, Hussam J. Mohammed, Alaa S. Al-Waisy, Shumoos Al-Fahdawi, Ahmed Adnan Had, Bourair Al-Attar

Iraqi Journal for Computer Science and Mathematics

Human activity Recognition (HAR) has emerged as an important research area due to its potential applications in health, sport, and recreation. The widespread availability of smartphone sensors has facilitated data collection for HAR systems. Although machine learning and deep learning models have proven to be effective in detecting human activity from sensor data, their performance may be limited, this study proposes MotionFusion which is an ensemble learning model to increase HAR accuracy utilizing accelerometer and gyroscope data from a smartphone. By combining Histogram-Based Gradient Boosting, Random Forest, and Extra Trees models with a Support Vector Machine classifier and using feature …

Ocean Heat Wave Induces Breeding Failure At The Southern Breeding Limit Of The Northern Gannet Morus Bassanus, William A. Montevecchi, Paul M. Regular, Jean-François Rail, Kyran Power, Chris Mooney, Kyle J.N. D’Entremont, Stefan Garthe, Leanne Guzzwell, Sabina I. Wilhelm

Marine Ornithology

We document unprecedented abandonments and breeding failures by Northern Gannets in eastern Canada at Cape St. Mary’s, Bonaventure Island, and the Magdalen Islands. These events were associated with a marine heat wave during chick rearing in the late summer of 2012. The rapid onset of abandonment at Cape St. Mary’s also coincided with intense lightning and thunder during an overnight storm. Parental desertions at all colonies were transient, resolving over a period of weeks, and appeared to be food-related, resulting in the poorest breeding success on record for each of these colonies. The Northern Gannet’s primary prey during the breeding …

Non-Breeding Movements And Foraging Ecology Of The Black Guillemot Cepphus Grylle In Atlantic Canada, Julia E. Baak, Marty L. Leonard, Carina Gjerdrum, Mark D. Dodds, Robert A. Ronconi

Marine Ornithology

Understanding the movements of seabirds, which are important ecological indicators, can provide new insights into physical and biological aspects of the marine environment. This information can also be used in planning marine conservation and oil spill response strategies. Though Black Guillemots Cepphus grylle are widely distributed in the coastal waters of eastern and arctic Canada, little is known about their movements during the non-breeding season. We used a combination of global location sensors and stable-isotope analyses on Black Guillemots breeding on Country Island, Nova Scotia, Canada and on Kent Island, New Brunswick, Canada to examine their non-breeding movements and trophic …

Reviews: Journal Of A Voyage: Federico Craveri And The Gulf Of California In 1856 (Craveri, F.; T. Bowen [Ed.], B. D'Arpa And B. Cavatorta [Translators]); How To Be An Antiracist (Kendi, I.X.); The Skin We're In: A Year Of Black Resistance And Power (Cole, D.); Hawai'i'S White Tern: Manu-O-Ku, An Urban Seabird (Scott, S.), Daniel W. Anderson, Rachel T. Buxton, David Ainley, Louise Blight, Jenna Cragg, Benjamin Saenz, Lindsay Young

Marine Ornithology

No abstract provided.

Nightly Colony Attendance Patterns Of Provisioning Cassin's Auklet Ptychoramphus Aleuticus Are Consistent And Synchronous, Laura Mcfarlane Tranquilla, John L. Ryder, Louise K. Blight, Patrick D. O’Hara, Douglas F. Bertram

Marine Ornithology

We conducted a multi-year (1999–2001) radio telemetry study to determine patterns of colony attendance among breeding Cassin’s Auklets Ptychoramphus aleuticus during the chick-rearing period on Triangle Island in British Columbia, Canada. A total of 1 625 detections were obtained for 80 individual birds (24–28 birds per year), each detected 20.3 times on average. We found that colony attendance (arrival times, departure times, in-burrow shift duration) and foraging trip duration (i.e., time away from the colony) were remarkably synchronous among individuals and years. On average, birds arrived in a pulse after darkness, with 67% of returns between 23h15 and 00h15 and …

Responses Of Sympatric Shearwaters To Supplemental Food Under Varying Natural Prey Availability On The Wintering Grounds Of Coastal Newfoundland, Canada, Paloma C. Carvalho, Laurie D. Maynard, Gail K. Davoren

Marine Ornithology

Species tend to concentrate in areas with high prey availability, which could lead to competitive interactions within a feeding assemblage as resources become depleted. In coastal Newfoundland, Canada, capelin Mallotus villosus is the focal forage fish species that many top predators feed on during the summer; however, inshore availability varies throughout the boreal summer when abundant aggregations migrate inshore to spawn. We investigated the interactions and responses of Great Shearwaters Ardenna gravis and Sooty Shearwaters A. grisea during their non-breeding season to supplemental food supply under changing natural prey availability (higher and lower capelin availability) by conducting an at-sea experiment …

Retracted: A Quantum Convolutional Neural Network Approach For Early And Accurate Diagnosis Of Parkinson's Disease, Aiesha Mahmoud Ibrahim, Mazin Abed Mohammed, Omar Al-Boridi

Iraqi Journal for Computer Science and Mathematics

Parkinson's disease (PD) is a progressive neurological disorder that primarily affects individuals over the age of 55. It is characterized by a range of motor and non-motor symptoms that can significantly impact various aspects of daily life. Despite notable advancements in medical science, there is currently no permanent cure or definitive treatment for PD. This therapeutic gap underscores the critical importance of early diagnosis, which remains a major focus of ongoing research. Due to the disease's gradual progression, PD symptoms may take years to fully develop, making early detection essential for improving patient outcomes and quality of life. Moreover, the …

Retracted: Solving Time-Fractional Nonlinear Variable-Order Delay Pdes Using Feedforward Neural Networks, Hala S. Alruhaili, Adel S. Hussain, Abdullah M. S. Ajlouni, Funda Türk, Emad A. Az-Zo’Bi, Mohammad A. Tashtoush

Iraqi Journal for Computer Science and Mathematics

This study presents an innovative application of Feedforward Neural Networks ‘FNNs’ to solve Variable-Order Fractional Partial Differential Equations ‘VO-FPDEs’ with time delays. Utilizing the Caputo definition, the variable-order fractional derivatives are approximated in terms of integer-order derivatives. The problem is reformulated as a system of partial differential equations with delay terms, which is then addressed using ‘FNNs’ to achieve explicit approximate solutions. Comprehensive error and convergence analyses validate the method’s precision and reliability. The effectiveness of the proposed approach is highlighted through numerical examples, with graphical and tabular representations showcasing minimal absolute errors and robust convergence. These results demonstrate the …

The Future Of Intelligent Industrial Systems: Plc, Node-Red, And Iot/Iiot, Firas Ahmed Hussein, Mohammad Tariq Yaseen, Mohammed Obaid Mustafa

AUIQ Technical Engineering Science

Integrating Programmable Logic Controllers (PLCs) with Node-RED and IoT/IIoT has emerged as a transformative technique for developing intelligent industrial systems as industrial automation improves. This narrative review brings together more than 70 research sources on industrial PLC, Node-RED, IoT, and IIoT applications. Case studies, experimental implementations, and industry reports are used to discover trends, challenges, and opportunities. The review focuses on three main topics: PLCs in modern industrial systems and their evolution and integration with IoT/IIoT; Node-RED as a middleware for industrial automation and its ability to connect PLCs to cloud and edge computing; and IIoT and smart manufacturing and …

Multi-Agent Architecture With Central Intelligent Agent, Shashwat Anand, Rohan Chaudhury

Defensive Publications Series

This disclosure describes a multi-agent architecture featuring a centralized intelligent agent (orchestrator agent) for complex enterprise environments, e.g., partner interfaces for a cloud computing solutions provider. While agent-driven interfaces are feasible, there are challenges in agent discovery and coordination, leading to fragmented solutions and slower pace of development. By providing a central agent that coordinates with various domain-specific functional agents, the techniques of this disclosure provide a cohesive mechanism for managing and orchestrating agents. The agent is built to service various user personas and uses this context to provide high-fidelity assistance. Agents are built with awareness of access control lists …

Location-Specific Artificial Intelligence Models, Ajay Prasad

Defensive Publications Series

Virtual assistants powered by large language models (LLMs) are capable of interacting with users via chat, voice, or other interfaces and can answer arbitrary queries from the user. However, LLMs may not have access to updated location-specific information. This disclosure describes techniques for integrating location-specific AI models into virtual assistants. This allows virtual assistants to provide hyperlocal information and personalized responses by switching between general-purpose and specialized models with user permission. Location-specific models are trained with data relevant to particular places or businesses. The described techniques enhance user experience by providing accurate and up to date location-specific information appropriate to …

Scope 4 Impact And Reporting Methodology, Marisol Palmero, Snezana Mitrovic, Suresh Krishnan

Defensive Publications Series

The concept of Scope 4 emissions, though not officially recognized in the Greenhouse Gas Protocol, presents a strategic opportunity to enhance sustainable operations. By focusing on "avoided emissions", based on good or best practices, organizations can influence and reduce Scope 2, and even Scope 3 emissions across their value chain. Techniques are proposed herein that seek to reduce energy consumption from networking devices. The proposed techniques could be extended to other practices within organizations. By reducing energy consumption, there is a direct link to improve energy efficiency, optimize resource usage, and ultimately contribute to an organization's overall sustainability goals. The …

Detecting Android Malware Based On Static Analysis Using Classification And Modified Clustering Techniques, Abdullah Allawi Al-Sraratee, Ahmed Habeeb Al-Azawei

Journal of Intelligent Informatics, Networking, and Cybersecurity

Because Android malware harms internet security, prior research proposes several different approaches to detect it accurately. However, such proposed models depend on numerous number of features to attain high accuracy. This could lead to high computation cost and potential overfitting. Furthermore, manual data labeling is labor-intensive, requiring significant human effort and skills. This research aims to: 1) extend previous literature on Android malware detection, 2) improve the accuracy of Android malware detection based on a low number of features, and 3) modify a clustering technique to group data into two different clusters to address the issue of unlabeled data. To …

Communication Assistance Using A Large Language Model, Justin Y. Li

Electrical and Computer Engineering Senior Theses

The number of people diagnosed with Autism Spectrum Disorder is growing annually at a rapid pace. Autistic people are known to have multiple problems with communication, requiring assistance and coaching which is already limited in availability due to the amount of training required. At the same time, there has been a recent exponential rise in usage of LLMs like ChatGPT which is widely available. This project aims to prototype a solution using ChatGPT to provide communication assistance to those diagnosed with autism. The project would record voice input through a microphone and transcribe it into text. The text would be …

Electrochemically-Assisted Low Power Density Laser Writing On Stainless Steel Via Enrichment Of Chromium Oxides, Zechariah Pfaffenberger, Lianlian Liu, Tae Kyong John Kim, Vignesh Venkataramani, Lydia Kisley

Faculty Scholarship

Laser color marking produces nearly permanent, environmentally friendly, vibrant colors on surfaces. However, previous work has used high-power-density pulsed lasers to induce the physicochemical reactions for marking. Here, laser color marking on stainless steel 304 (SS304) is performed with a less expensive continuous wave (CW) laser and a power density five orders of magnitude below that previously reported by combining an electrochemical cell with a fluorescence microscope. Using a combination of optical microscopy, x-ray photoelectron spectroscopy, and bulk electrochemistry, it is demonstrated that the laser-induced luminescence and colors are due to enrichment (32 ± 9% increase) of Cr2O3 in the …

Guinea: A Mining Boom In Defiance Of Standards, Foromo Frédéric Loua

Maryland Journal of International Law

No abstract provided.

From Class To Competition, Mechanical Engineering Students Take On Autonomous Robotics, University Of Dayton

Blog: The Dayton Engineer

In the School of Engineering's Autonomous Systems course, engineering students challenged their technical skills through designing fully autonomous robots.

Developing A Stochastic Rupture Model Catalog For Earthquakes With Magnitudes Of Seven Or Greater Along The Alaskan Subduction Zone, Alexandru Mihai Lapadat

Geosciences

Alaska represents one of the most seismically active regions in the Ring of Fire and world impacted by large-magnitude (Mw > 6.5) earthquake events, posing significant risks to local communities and infrastructure, but also distant populations due to the associated tsunami hazard. However, limited seismo-geodetic datasets hinder the understanding of the slip kinematics of megathrust earthquakes in the Alaskan subduction zone, complicating the estimation of future earthquake probabilities, surface displacements, and the design of a GNSS-aided Earthquake Early Warning (EEW) system. This research contributes an extensive synthetic rupture model catalog for the Alaskan subduction zone, generated using the stochastic methodology of …

Recent Advances In Modelling Of Frost Formation For Mechanical Systems, Yong Tao

Mechanical Engineering Faculty Publications

The physics underlying frost and ice formation has been extensively studied over the past few decades, with significant contributions to our understanding of this phenomenon. These insights have primarily been applied to engineering systems with refrigerated surfaces, such as refrigerators, freezers and heat pumps of various sizes. Despite considerable progress, the dynamic and complex mechanisms governing frost and ice formation remain an active area of research, as competing factors continue to challenge predictive accuracy. The increasing interest from stakeholders in reducing energy consumption and carbon footprints in mechanical systems further underscores the importance of advancing modelling and simulation capabilities in …

Super-Resolution Stimulated X-Ray Raman Spectroscopy, Kai Li, Christian Ott, Marcus Agåker, Phay J. Ho, Gilles Doumy, Alexander Magunia, Marc Rebholz, Marc Simon, Tommaso Mazza, Alberto De Fanis, Thomas M. Baumann, Jacobo Montano, Nils Rennhack, Sergey Usenko, Yevheniy Ovcharenko, Kalyani Chordiya, Lan Cheng, Jan Erik Rubensson, Michael Meyer, Thomas Pfeifer, Mette B. Gaarde, Linda Young

Faculty Publications

Propagation of intense X-ray pulses through dense media has led to the observation of phenomena such as atomic X-ray lasing^1,2, self-induced transparency³ and stimulated X-ray Raman scattering (SXRS)⁴. SXRS has been long predicted as a means to launch and probe valence-electron wavepackets and as a building block for nonlinear X-ray spectroscopies^5,6. However, experimental observations of SXRS to date^4,7,8 have not provided spectroscopic information, and theoretical modelling has largely implemented hard-to-realize phase-coherent attosecond pulses. Here we demonstrate SXRS with spectroscopic precision, that is, detection of valence-excited states in neon with a near Fourier-limited …

Solar Absorption Cooling Systems – A Case Study In Egypt, Hesham Safwat, Iman El-Mahallawi

Mechanical Engineering

Climate change with Egypt’s increasingly hot weather and plans towards energy transition, addressing an approach for clean HVAC (Heating, Ventilation, and Air Condition) solutions is becoming requisite. This paper examines the potential of utilizing solar absorption cooling systems in institutional buildings by presenting a case study of a proposed solar absorption cooling system for a library building with an area of 4402 m2, located at the British University in Egypt. The proposed solution is to replace 30% of the existing conventional air conditioning units with a hot-water driven single-effect absorption chiller powered by solar thermal vacuum tube solar collectors, coupled …

A Predictive Framework For Early Detection And Personalised Monitoring Of Parkinson’S Disease Using Artificial Intelligence And Large Language Models, Priyadharshini S

Theses and Dissertations

Parkinson’s Disease (PD) is a multifaceted and progressive neurodegenerative disorder that presents a spectrum of motor and non-motor symptoms. Early and accurate diagnosis is essential for effective disease management and improved patient outcomes, yet remains clinically challenging due to symptom overlap and diagnostic limitations. This thesis proposes a comprehensive and interpretable artificial intelligence (AI)-driven diagnostic framework that aims to transform the early detection, personalised monitoring, and treatment recommendation process for PD. The proposed solution integrates deep learning, radiomics, evolutionary optimisation, and large language models (LLMs), ensuring a highly accurate and clinically adaptable system.

The research begins by analysing T2-weighted 3D …

Real-Time Fraud Detection Using Big Data, Abdulla Matar Alketbi

Theses

In today’s digital world, fraud detection has become an important part of financial security. This study explores and compares the performance of different machine learning models in identifying fraudulent transactions using the IEEE-CIS Fraud Detection dataset. Techniques such as Random Forest, Gradient Boosting, Deep Neural Networks, and Logistic Regression were evaluated. The dataset was pre-processed using SMOTE to balance the classes and improve model sensitivity to fraud cases. Each performance of the model was assessed using accuracy, precision, recall, and F1-score. The Random Forest model achieved the highest overall performance with an F1-score of 99.23

Limitations Of Using Large Language Models For Automated Essay Scoring, Thomas A. Fink

Theses

Background: Automated essay scoring (AES) is a challenging deep learning problem. The two most widely used methods for predicting essay quality scores, supervised learning-based and LLM-based, have their own limitations. Although supervised learning-based methods are more accurate, they only predict a score and do not offer descriptive feedback to students. On the other hand, LLM-based methods can offer rubric-guided feedback but are known to be less accurate.

Methods: This work focuses on improving the accuracy of state-of-the-art LLM-based AES methods. We began by thoroughly investigating why these methods were performing poorly for certain datasets and certain examples. This led us …

Numerical Simulation Of Frost Formation And Heat Transfer On Fin-And-Tube Heat Exchangers In Turbulent Cross-Flow, Mahsan Farzaneh, ‪Nadim Zgheib, S. Balachandar, S. A. Sherif

Mechanical Engineering Faculty Publications

Frost formation in fin-and-tube heat exchangers in turbulent cross-flow presents significant challenges in industrial refrigeration applications, affecting heat transfer efficiency and operational reliability. The purpose of this work is to investigate frost deposition and growth on a staggered bank of a fin-and-tube freezer coil under turbulent forced convection conditions. The focus here is on investigating conditions that closely replicate real-world scenarios in large walk-in industrial freezers. Using a direct numerical simulation approach, we examine the flow dynamics and thermal behaviour in the presence of frost, considering turbulent regimes characterized by a Reynolds number in the range 1050≤𝑅⁢𝑒𝐷,avg≤4800, with the characteristic …

Predicting Sleep And Sleep Stage In Children Using Actigraphy And Heartrate Via A Long Short-Term Memory Deep Learning Algorithm: A Performance Evaluation, Robert Weaver Med, Phd, James White, Olivia Finnegan, Hongpeng Yang, Zifei Zhong, Keagan Kiely, Catherine Jones, Yan Tong, Srihari Nelakuditi, Rahul Ghosal, David E. Brown, Russell R. Pate Ph.D., Gregory J. Welk, Massimiliano De Zambotti, Yuan Wang, Sarah Burkart, Elizabeth L. Adams Phd, Bridget Armstrong, Michael Beets Med, Mph, Phd

Faculty Publications

Children's ambulatory sleep is commonly measured via actigraphy. However, traditional actigraphy measured sleep (e.g., Sadeh algorithm) struggles to predict wake (i.e., specificity, values typically < 70) and cannot predict sleep stages. Long short-term memory (LSTM) is a machine learning algorithm that may address these deficiencies. This study evaluated the agreement of LSTM sleep estimates from actigraphy and heartrate (HR) data with polysomnography (PSG). Children (N = 238, 5–12 years,52.8% male, 50% Black 31.9% White) participated in an overnight laboratory polysomnography. Participants were referred be-cause of suspected sleep disruptions. Children wore an ActiGraph GT9X accelerometer and two of three consumer wearables(i.e., Apple Watch Series 7, Fitbit Sense, Garmin Vivoactive 4) on their non-dominant wrist during the polysomnogram. LSTM estimated sleep versus wake and sleep stage (wake, not-REM, REM) using raw actigraphy and HR data for each 30-s epoch. Logistic regression and random forest were also estimated as a benchmark for performance with which to compare the LSTM results. A 10-fold cross-validation technique was employed, and confusion matrices were constructed. Sensitivity and specificity were calculated to assess the agreement between research-grade and consumer wearables with the criterion polysomnography. For sleep versus wake classification, LSTM outperformed logistic regression and random forest with accuracy ranging from 94.1to 95.1, sensitivity ranging from 94.9 to 95.9 across different devices, and specificity ranging from 84.5 to 89.6. The addition of HR improved the prediction of sleep stages but not binary sleep versus wake. LSTM is promising for predicting sleep and sleep staging from actigraphy data, and HR may improve sleep stage prediction.