Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Deep Learning (3)
- Machine Learning (2)
- Alleles (1)
- Arrhythmia (1)
- Artificial Immune System (1)
-
- Auto-regressive process (1)
- Autonomous Aerial Vehicle (1)
- Autonomous vehicles (1)
- Autonomy (1)
- Biosensors (1)
- Burg estimation method (1)
- CACC (1)
- Convolutional Neural Network (1)
- DNA (1)
- DNA Analysis (1)
- Degraded DNA (1)
- Electrocardiogram (ECG) (1)
- Electropherogram (1)
- Face Recognition (1)
- GPS-denied Environment (1)
- Gender Classification (1)
- Generalized likelihood ratio test (1)
- Generative Adversarial Network (1)
- Identification (1)
- Image Quality Assessment Orthogonal Regularization (1)
- Image-to-image Translation (1)
- Imitation Learning (1)
- Integrated Biosensors (1)
- Internal (1)
- Kalman filter (1)
Articles 1 - 12 of 12
Full-Text Articles in Computer Engineering
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 …
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 …
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 …
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 …
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 …
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. …
Mitigating Insider Threats In A Cooperative Adaptive Cruise Control System Using Local Intra-Vehicle Data, Alexander Francis Colon
Mitigating Insider Threats In A Cooperative Adaptive Cruise Control System Using Local Intra-Vehicle Data, Alexander Francis Colon
Graduate Theses, Dissertations, and Problem Reports
With the rise of Connected-and-Automated-Vehicle (CAV) technologies on roadways, transportation networks have become increasingly connected through Vehicle-to-Everything (V2X) systems. With access to the additional data from V2X, modern cruise control systems like Adaptive Cruise Control (ACC) are further improved upon to develop systems like Cooperative ACC (CACC) which reduces traffic congestion and increases driver safety and energy efficiency. With that increased connectivity, previously closed vehicle systems are now vulnerable to new security threats which pose new technical challenges. Significant research has been done to strengthen the network against external threats such as denial-of-service attacks (DoS) or passive eavesdropping attacks using …
Palmprint Gender Classification Using Deep Learning Methods, Minou Khayami
Palmprint Gender Classification Using Deep Learning Methods, Minou Khayami
Graduate Theses, Dissertations, and Problem Reports
Gender identification is an important technique that can improve the performance of authentication systems by reducing searching space and speeding up the matching process. Several biometric traits have been used to ascertain human gender. Among them, the human palmprint possesses several discriminating features such as principal-lines, wrinkles, ridges, and minutiae features and that offer cues for gender identification. The goal of this work is to develop novel deep-learning techniques to determine gender from palmprint images. PolyU and CASIA palmprint databases with 90,000 and 5502 images respectively were used for training and testing purposes in this research. After ROI extraction and …
Route Planning For Long-Term Robotics Missions, Christopher Alexander Arend Tatsch
Route Planning For Long-Term Robotics Missions, Christopher Alexander Arend Tatsch
Graduate Theses, Dissertations, and Problem Reports
Many future robotic applications such as the operation in large uncertain environment depend on a more autonomous robot. The robotics long term autonomy presents challenges on how to plan and schedule goal locations across multiple days of mission duration. This is an NP-hard problem that is infeasible to solve for an optimal solution due to the large number of vertices to visit. In some cases the robot hardware constraints also adds the requirement to return to a charging station multiple times in a long term mission. The uncertainties in the robot model and environment require the robot planner to account …
Immunity-Based Framework For Autonomous Flight In Gps-Challenged Environment, Mohanad Al Nuaimi
Immunity-Based Framework For Autonomous Flight In Gps-Challenged Environment, Mohanad Al Nuaimi
Graduate Theses, Dissertations, and Problem Reports
In this research, the artificial immune system (AIS) paradigm is used for the development of a conceptual framework for autonomous flight when vehicle position and velocity are not available from direct sources such as the global navigation satellite systems or external landmarks and systems. The AIS is expected to provide corrections of velocity and position estimations that are only based on the outputs of onboard inertial measurement units (IMU). The AIS comprises sets of artificial memory cells that simulate the function of memory T- and B-cells in the biological immune system of vertebrates. The innate immune system uses information about …
On Designing An Ecg-Based Intelligent System: Utilizing The Heart’S Electrical Activity To Recognize Humans And Detect Arrhythmia, Sara Saeed Abdeldayem
On Designing An Ecg-Based Intelligent System: Utilizing The Heart’S Electrical Activity To Recognize Humans And Detect Arrhythmia, Sara Saeed Abdeldayem
Graduate Theses, Dissertations, and Problem Reports
The electrocardiogram (ECG) signal is the bioelectrical signal that reflects the heart's activity. It has been extensively used as a diagnostic tool since it holds information about the cardiac health condition. However, recent researches have shown that it exhibits an inter-subject variability property. Therefore, it can be used as a biometric-based modality for either identification or verification purposes. Nevertheless, some of the challenges are faced while employing such a signal. For instance, ECG signal is prone to noise, accordingly, noise filters should be designed to remove the noise while keeping the signal properties. Moreover, factors such as medications, health condition, …