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Articles 1 - 30 of 61
Full-Text Articles in Engineering
Machine Learning For Environmental Sustainability, Syeda Nyma Ferdous
Machine Learning For Environmental Sustainability, Syeda Nyma Ferdous
Graduate Theses, Dissertations, and Problem Reports
This research proposes a comprehensive approach to address pressing challenges in environmental sustainability, agricultural residue management, using machine learning based approaches. Machine learning (ML) techniques have emerged as powerful tools for addressing environmental sustainability challenges by facilitating the analysis and prediction of ecological phenomena, and optimization of resource management strategies. The study explores the synergies between environmental sustainability and machine learning to develop a framework that leverages artificial intelligence techniques covering a wide range of tasks including crop residue management, soil CO2 flux prediction, and forest carbon system prediction for sustainable development. The study analyze various ML models, such as, …
An Approach For Robotic Pollination That Utilizes Imitation Learning, Ronald Michael Butts Ii
An Approach For Robotic Pollination That Utilizes Imitation Learning, Ronald Michael Butts Ii
Graduate Theses, Dissertations, and Problem Reports
The global decline in pollinator populations poses a significant threat to agriculture, motivating the development of robotic pollination systems. Previous works demonstrated successful robotic pollination of bramble flowers using visual servoing; however, pollination was limited to specific flower orientations. As such, the objective of this work is to develop a robotic pollination system that is capable of pollinating a wider range of orientations.
This research introduces an imitation learning-based framework for robotic pollination that positions the manipulator to view chosen flowers in specific orientations. The developed model leverages object detection (YOLOv8) to identify individual flowers and a convolutional neural network …
Autonomous Object Search Planning In Large-Scale Environments, Matthew A. Collins
Autonomous Object Search Planning In Large-Scale Environments, Matthew A. Collins
Graduate Theses, Dissertations, and Problem Reports
The advancement of autonomous search holds significant promise for applications ranging from emergency response to planetary exploration. This thesis investigates strategies to enhance autonomous search performance in large-scale environments. The main contribution of this work is its practical application in real-world scenarios, where efficient search methods are essential for managing vast amounts of data, particularly in large environments. Effective search planning requires navigating complexities such as limited prior information and managing large state spaces, necessitating advanced strategies to plan with this limited information. Additionally, balancing exploration and exploitation is crucial for optimizing the search process, as it ensures thorough coverage …
On Uncertainty For Ill-Posed Robot Decision Problems, Jared Joseph Beard
On Uncertainty For Ill-Posed Robot Decision Problems, Jared Joseph Beard
Graduate Theses, Dissertations, and Problem Reports
As robots adopt more real world responsibilities, they will be expected to solve more complicated problems. In some cases limited prior knowledge will result in unmodelled environmental conditions; in others, multiple users may have competing perspectives on how to frame a decision problem. Many existing frameworks, namely Markov decision processes (MDP) presuppose users have identified a specific problem with models sufficient to solve or learn a problem. If we wish to extend MDPs to novel problems or those heavily dependent on user feedback, autonomous decision makers must be able to identify limitations in how a given problem is framed and …
Joint Learning Of Unknown Safety Constraints And Control Policies In Reinforcement Learning, Lunet Abiye Yifru
Joint Learning Of Unknown Safety Constraints And Control Policies In Reinforcement Learning, Lunet Abiye Yifru
Graduate Theses, Dissertations, and Problem Reports
Reinforcement learning (RL) has revolutionized decision-making across a wide range of domains over the past few decades. Yet, deploying RL policies in real-world scenarios presents the crucial challenge of ensuring safety. Traditional safe RL approaches have predominantly focused on incorporating predefined safety constraints into the policy learning process. However, this reliance on predefined safety constraints poses limitations in dynamic and unpredictable real-world settings where such constraints may not be available or sufficiently adaptable. Bridging this gap, we propose a novel approach that concurrently learns a safe RL control policy and identifies the unknown safety constraint parameters of a given environment. …
Implementing Test Automation With Selenium Webdriver, Ramana Inturi
Implementing Test Automation With Selenium Webdriver, Ramana Inturi
Graduate Theses, Dissertations, and Problem Reports
Many software programs, such as applications for designing, modeling, simulating, and analyzing systems, are now commonly available as web-based applications. The testing of such sophisticated web applications is highly challenging and can be extremely tedious and error-prone if done manually. Recently automation tools have become increasingly used for testing web-based applications, as they minimize human involvement and repetitive work.
For this problem report project, we have built and implemented an automation testing framework for web applications. The project specifically uses a tool called Selenium WebDriver, which has been used to develop the testing framework. By using this framework, testers may …
Exploiting The Advantages And Overcoming The Challenges Of The Cable In A Tethered Drone System, Rogerio Rodrigues Lima
Exploiting The Advantages And Overcoming The Challenges Of The Cable In A Tethered Drone System, Rogerio Rodrigues Lima
Graduate Theses, Dissertations, and Problem Reports
This dissertation proposes solutions for motion planning, localization, and landing of tethered drones using only tether variables. A tether-based multi-model localization framework for tethered drones is proposed. This framework comprises three independent localization strategies based on a different model. The first strategy uses simple trigonometric relations assuming that the tether is taut; the second method relies on a set of catenary equations for the slack tether case; the third estimator is a neural network-based predictor that can cover different tether shapes. Multi-layer perceptron networks previously trained with a dataset comprised of the tether variables (i.e., length, tether angles on the …
Motion Planning In Artificial And Natural Vector Fields, Bernardo Martinez Rocamora Junior
Motion Planning In Artificial And Natural Vector Fields, Bernardo Martinez Rocamora Junior
Graduate Theses, Dissertations, and Problem Reports
This dissertation advances the field of autonomous vehicle motion planning in various challenging environments, ranging from flows and planetary atmospheres to cluttered real-world scenarios. By addressing the challenge of navigating environmental flows, this work introduces the Flow-Aware Fast Marching Tree algorithm (FlowFMT*). This algorithm optimizes motion planning for unmanned vehicles, such as UAVs and AUVs, navigating in tridimensional static flows. By considering reachability constraints caused by vehicle and flow dynamics, flow-aware neighborhood sets are found and used to reduce the number of calls to the cost function. The method computes feasible and optimal trajectories from start to goal in challenging …
Face Image And Video Analysis In Biometrics And Health Applications, Na Zhang
Face Image And Video Analysis In Biometrics And Health Applications, Na Zhang
Graduate Theses, Dissertations, and Problem Reports
Computer Vision (CV) enables computers and systems to derive meaningful information from acquired visual inputs, such as images and videos, and make decisions based on the extracted information. Its goal is to acquire, process, analyze, and understand the information by developing a theoretical and algorithmic model. Biometrics are distinctive and measurable human characteristics used to label or describe individuals by combining computer vision with knowledge of human physiology (e.g., face, iris, fingerprint) and behavior (e.g., gait, gaze, voice). Face is one of the most informative biometric traits. Many studies have investigated the human face from the perspectives of various different …
Imitation Learning For Swarm Control Using Variational Inference, Hafeez Olafisayo Jimoh
Imitation Learning For Swarm Control Using Variational Inference, Hafeez Olafisayo Jimoh
Graduate Theses, Dissertations, and Problem Reports
Swarms are groups of robots that can coordinate, cooperate, and communicate to achieve tasks that may be impossible for a single robot. These systems exhibit complex dynamical behavior, similar to those observed in physics, neuroscience, finance, biology, social and communication networks, etc. For instance, in Biology, schools of fish, swarm of bacteria, colony of termites exhibit flocking behavior to achieve simple and complex tasks. Modeling the dynamics of flocking in animals is challenging as we usually do not have full knowledge of the dynamics of the system and how individual agent interact. The environment of swarms is also very noisy …
Machine Learning For Biosensors, Gayathri Anapanani
Machine Learning For Biosensors, Gayathri Anapanani
Graduate Theses, Dissertations, and Problem Reports
Biosensors have become increasingly popular as diagnostic tools due to their ability to detect and quantify biological analytes in a wide range of applications. With the growing demand for faster and more reliable biosensing devices, machine learning has become a valuable tool in enhancing biosensor performance. In this report, we review recent progress in the application of machine learning to biosensors. We discuss the potential benefits of using machine learning in biosensors, including improved sensitivity, selectivity, and accuracy. We also discuss the various machine learning techniques that have been applied to biosensors, including data preprocessing, feature extraction, and classification and …
Spatio-Temporal Deep Learning Approaches For Addressing Track Association Problem Using Automatic Identification System (Ais) Data, Md Asif Bin Syed
Spatio-Temporal Deep Learning Approaches For Addressing Track Association Problem Using Automatic Identification System (Ais) Data, Md Asif Bin Syed
Graduate Theses, Dissertations, and Problem Reports
In the realm of marine surveillance, track association constitutes a pivotal yet challenging task, involving the identification and tracking of unlabelled vessel trajectories. The need for accurate data association algorithms stems from the urge to spot unusual vessel movements or threat detection. These algorithms link sequential observations containing location and motion information to specific moving objects, helping to build their real-time trajectories. These threat detection algorithms will be useful when a vessel attempts to conceal its identity. The algorithm can then identify and track the specific vessel from its incoming signal. The data for this study is sourced from the …
Efficacy Of Reported Issue Times As A Means For Effort Estimation, Paul Phillip Maclean
Efficacy Of Reported Issue Times As A Means For Effort Estimation, Paul Phillip Maclean
Graduate Theses, Dissertations, and Problem Reports
Software effort is a measure of manpower dedicated to developing and maintaining and software. Effort estimation can help project managers monitor their software, teams, and timelines. Conversely, improper effort estimation can result in budget overruns, delays, lost contracts, and accumulated Technical Debt (TD). Issue Tracking Systems (ITS) have become mainstream project management tools, with over 65,000 companies using Jira alone. ITS are an untapped resource for issue resolution effort research. Related work investigates issue effort for specific issue types, usually Bugs or similar. They model their developer-documented issue resolution times using features from the issues themselves. This thesis explores a …
A Tool For Biometric Interpretation Of Forensic Str Dna Profiles, Ahmad Jamal Baroudi
A Tool For Biometric Interpretation Of Forensic Str Dna Profiles, Ahmad Jamal Baroudi
Graduate Theses, Dissertations, and Problem Reports
Rapid DNA biometric identification applications are becoming more essential and widely used in human identity validation processes. Despite their powerful identification capabilities, processing a sample to generate a forensic DNA profile still takes longer compared with other rapid biometric technologies. Methods used to speed up the analysis could lead to signal artifacts similar to those arising from low copy or degraded DNA samples, making the electropherogram unsuitable for forensic interpretation and analysis. The goal of this research effort is to apply biometrics and mathematical approaches to forensic STR (Short Tandem Repeat) profiles. To accomplish this goal, a multi-function software tool …
Generation Of High Performing Morph Datasets, Kelsey Lynn O'Haire
Generation Of High Performing Morph Datasets, Kelsey Lynn O'Haire
Graduate Theses, Dissertations, and Problem Reports
Facial recognition systems play a vital role in our everyday lives. We rely on this technology from menial tasks to issues as vital as national security. While strides have been made over the past ten years to improve facial recognition systems, morphed face images are a viable threat to the reliability of these systems. Morphed images are generated by combining the face images of two subjects. The resulting morphed face shares the likeness of the contributing subjects, confusing both humans and face verification algorithms. This vulnerability has grave consequences for facial recognition systems used on international borders or for law …
A Novel Computational Network Methodology For Discovery Of Biomarkers And Therapeutic Targets, Qing Ye
A Novel Computational Network Methodology For Discovery Of Biomarkers And Therapeutic Targets, Qing Ye
Graduate Theses, Dissertations, and Problem Reports
Lung cancer has the second highest cancer incidence rate and the top cancer-related mortality worldwide. An estimate from the American Cancer Society shows that, in 2022, there will be about 236,740 lung cancer cases (117,910 men and 118,830 women) in the US. To date, there are no prognostic/predictive biomarkers to select chemotherapy, immunotherapy, and radiotherapy in individual non-small cell lung cancer (NSCLC) patients. There is an unmet clinical need to identify patients with early-stage NSCLC who are likely to develop recurrence and to predict their therapeutic responses. This dissertation developed a novel computational methodology for modeling molecular gene association networks …
Synthesizing Realistic Substitute Data For A Law Enforcement Database Using A Python Library, Anthony Carrola
Synthesizing Realistic Substitute Data For A Law Enforcement Database Using A Python Library, Anthony Carrola
Graduate Theses, Dissertations, and Problem Reports
In many databases, there is private or sensitive data that should not be accessible to any but a few individuals, such as HIPAA (Health Insurance Portability and Accountability Act) protected or LE (law enforcement) data. However, there is often a need to work with the data or change it for proper and thorough testing, especially for the developers . In some cases, the developers may be authorized to access and view the data, but it is rarely allowable for that data to be changed. Further, it is unlikely, especially on a large project, that all of the developers will have …
System Development Of An Unmanned Ground Vehicle And Implementation Of An Autonomous Navigation Module In A Mine Environment, Jonas Amoama Bredu Jnr
System Development Of An Unmanned Ground Vehicle And Implementation Of An Autonomous Navigation Module In A Mine Environment, Jonas Amoama Bredu Jnr
Graduate Theses, Dissertations, and Problem Reports
There are numerous benefits to the insights gained from the exploration and exploitation of underground mines. There are also great risks and challenges involved, such as accidents that have claimed many lives. To avoid these accidents, inspections of the large mines were carried out by the miners, which is not always economically feasible and puts the safety of the inspectors at risk. Despite the progress in the development of robotic systems, autonomous navigation, localization and mapping algorithms, these environments remain particularly demanding for these systems. The successful implementation of the autonomous unmanned system will allow mine workers to autonomously determine …
Improving Robotic Decision-Making In Unmodeled Situations, Nicholas Scott Ohi
Improving Robotic Decision-Making In Unmodeled Situations, Nicholas Scott Ohi
Graduate Theses, Dissertations, and Problem Reports
Existing methods of autonomous robotic decision-making are often fragile when faced with inaccurate or incompletely modeled distributions of uncertainty, also known as ambiguity. While decision-making under ambiguity is a field of study that has been gaining interest, many existing methods tend to be computationally challenging, require many assumptions about the nature of the problem, and often require much prior knowledge. Therefore, they do not scale well to complex real-world problems where fulfilling all of these requirements is often impractical if not impossible. The research described in this dissertation investigates novel approaches to robotic decision-making strategies which are resilient to …
Multimodal Adversarial Learning, Uche Osahor
Multimodal Adversarial Learning, Uche Osahor
Graduate Theses, Dissertations, and Problem Reports
Deep Convolutional Neural Networks (DCNN) have proven to be an exceptional tool for object recognition, generative modelling, and multi-modal learning in various computer vision applications. However, recent findings have shown that such state-of-the-art models can be easily deceived by inserting slight imperceptible perturbations to key pixels in the input. A good target detection systems can accurately identify targets by localizing their coordinates on the input image of interest. This is ideally achieved by labeling each pixel in an image as a background or a potential target pixel. However, prior research still confirms that such state of the art targets models …
Face Representation Learning And Its Applications: From Image Editing To 3d Avatar Animation, Xudong Liu
Face Representation Learning And Its Applications: From Image Editing To 3d Avatar Animation, Xudong Liu
Graduate Theses, Dissertations, and Problem Reports
Face representation learning is one of the most popular research topics in the computer vision community, as it is the foundation of face recognition and face image generation. Numerous representation learning frameworks have been integrated into applications in daily life, such as face recognition, image editing, and face tracking. Researchers have developed advanced algorithms for face recognition with successful commercial productions, for example, FaceID on the smartphone. The performance record on face recognition is constantly updated and becoming saturated with the help of large-scale datasets and advanced computational resources. Thanks to the robust representation in face recognition, in this dissertation, …
Face Recognition With Attention Mechanisms, Qiangchang Wang
Face Recognition With Attention Mechanisms, Qiangchang Wang
Graduate Theses, Dissertations, and Problem Reports
Face recognition has been widely used in people’s daily lives due to its contactless process and high accuracy. Existing works can be divided into two categories: global and local approaches. The mainstream global approaches usually extract features on whole faces. However, global faces tend to suffer from dramatic appearance changes under the scenarios of large pose variations, heavy occlusions, and so on. On the other hand, since some local patches may remain similar, they can play an important role in such scenarios. Existing local approaches mainly rely on cropping local patches around facial landmarks and then extracting corresponding local representations. …
Incentive Analysis Of Blockchain Technology, Rahul Reddy Annareddy
Incentive Analysis Of Blockchain Technology, Rahul Reddy Annareddy
Graduate Theses, Dissertations, and Problem Reports
Blockchain technology was invented in the Bitcoin whitepaper released in 2008. Since then, several decentralized cryptocurrencies and applications have become mainstream. There has been an immense amount of engineering effort put into developing blockchain networks. Relatively few projects backed by blockchain technology have succeeded and maintained a large community of developers, users, and customers, while many popular projects with billions of dollars in funding and market capitalizations have turned out to be complete scams.
This thesis discusses the technological innovations introduced in the Bitcoin whitepaper and the following work of the last fifteen years that has enabled blockchain technology. A …
An Efficient Ar Model-Based Method For The Detection Of Forced Oscillations In Power Networks: Implementation And Analysis, Maria Waleska Suarez
An Efficient Ar Model-Based Method For The Detection Of Forced Oscillations In Power Networks: Implementation And Analysis, Maria Waleska Suarez
Graduate Theses, Dissertations, and Problem Reports
An active research topic is the detection of various oscillations that may lead to instability and potential disruption in the operation of a power network. Forced Oscillations (FOs) play a unique role in power system stability among various oscillations. They are perturbances that change the system’s state and are caused for many reasons, including but not limited to persistent load changes and oscillatory load or generation, fault, triplane, and other mechanical anomalies. These factors can hugely affect the power grid by either increasing or decreasing the amplitude, causing corrupt modes leading to blackouts, affecting the equipment involved, delivering poor power …
Learning Representations For Human Identification, Sinan Sabri
Learning Representations For Human Identification, Sinan Sabri
Graduate Theses, Dissertations, and Problem Reports
Long-duration visual tracking of people requires the ability to link track snippets (a.k.a. tracklets) based on the identity of people. In lack of the availability of motion priors or hard biometrics (e.g., face, fingerprint, or iris), the common practice is to leverage soft biometrics for matching tracklets corresponding to the same person in different sightings. A common choice is to use the whole-body visual appearance of the person, as determined by the clothing, which is assumed to not change during tracking. The problem is challenging because distinct images of the same person may look very different, since no restrictions are …
Performance Of Sensor Fusion For Vehicular Applications, Nikola Janevski
Performance Of Sensor Fusion For Vehicular Applications, Nikola Janevski
Graduate Theses, Dissertations, and Problem Reports
Sensor fusion is a key system in Advanced Driver Assistance Systems, ADAS. The perfor-
mance of the sensor fusion depends on many factors such as the sensors used, the kinematic
model used in the Extended Kalman Filter, EKF, the motion of the vehicles, the type of
road, the density of vehicles, and the gating methods. The interactions between parameters
and the extent to which individual parameters contribute to the overall accuracy of a sensor
fusion system can be difficult to assess.
In this study, a full-factorial experimental evaluation of a sensor fusion system based
on a real vehicle was performed. …
Evaluating Social Media As A Medium Of Private Communication Through Steganographic Images, Kendall Weldon Coles
Evaluating Social Media As A Medium Of Private Communication Through Steganographic Images, Kendall Weldon Coles
Graduate Theses, Dissertations, and Problem Reports
Social media is a vastly used communication tool with billions of users worldwide. These social networks provide users the ability to share their ideas and thoughts through the messages, videos, and images that they post. The images that are shared can possibly be embedded with private messages through the use of a steganographic tool. The messages are embedded in a fashion that doesn’t change the visual appearance of an image. This allows for these types of images to hide in plain sight, which creates the possibility of someone communicating privately in a public social media setting. This project proved how …
Touching Light: A Framework For The Facilitation Of Music-Making In Mixed Reality, Ian Thomas Riley
Touching Light: A Framework For The Facilitation Of Music-Making In Mixed Reality, Ian Thomas Riley
Graduate Theses, Dissertations, and Problem Reports
Drawing upon the historical development of analog and digital technologies alongside the proliferation of computer-assisted performance practices, this research seeks to develop a framework for integrating Mixed Reality applications to live musical performance, specifically through the creation of a Microsoft HoloLens 2 Mixed Reality application in order to facilitate a live performance of an original musical composition for percussion and real-time Mixed Reality environment. Mixed Reality enables a performer to interact with virtual (holograms, VSTs, etc.) and physical (vibraphone, tuned drums, microphones, etc.) objects simultaneously. Tandem to the development of the conceptual framework was the composition of an original score …
Planetary Rover Inertial Navigation Applications: Pseudo Measurements And Wheel Terrain Interactions, Cagri Kilic
Planetary Rover Inertial Navigation Applications: Pseudo Measurements And Wheel Terrain Interactions, Cagri Kilic
Graduate Theses, Dissertations, and Problem Reports
Accurate localization is a critical component of any robotic system. During planetary missions, these systems are often limited by energy sources and slow spacecraft computers. Using proprioceptive localization (e.g., using an inertial measurement unit and wheel encoders) without external aiding is insufficient for accurate localization. This is mainly due to the integrated and unbounded errors of the inertial navigation solutions and the drifted position information from wheel encoders caused by wheel slippage. For this reason, planetary rovers often utilize exteroceptive (e.g., vision-based) sensors. On the one hand, localization with proprioceptive sensors is straightforward, computationally efficient, and continuous. On the other …
Using Distributed Ledger Technologies In Vanets To Achieve Trusted Intelligent Transportation Systems, Fares Nabil Elamine
Using Distributed Ledger Technologies In Vanets To Achieve Trusted Intelligent Transportation Systems, Fares Nabil Elamine
Graduate Theses, Dissertations, and Problem Reports
With the recent advancements in the networking realm of computers as well as achieving real-time communication between devices over the Internet, IoT (Internet of Things) devices have been on the rise; collecting, sharing, and exchanging data with other connected devices or databases online, enabling all sorts of communications and operations without the need for human intervention, oversight, or control. This has caused more computer-based systems to get integrated into the physical world, inching us closer towards developing smart cities.
The automotive industry, alongside other software developers and technology companies have been at the forefront of this advancement towards achieving smart …