Extracting Edges In Space And Time During Visual Fixations, Lynn Schmittwilken, Marianne Maertens

MODVIS Workshop

No abstract provided.

Eddy Current Defect Response Analysis Using Sum Of Gaussian Methods, James William Earnest

Theses and Dissertations

This dissertation is a study of methods to automatedly detect and produce approximations of eddy current differential coil defect signatures in terms of a summed collection of Gaussian functions (SoG). Datasets consisting of varying material, defect size, inspection frequency, and coil diameter were investigated. Dimensionally reduced representations of the defect responses were obtained utilizing common existing reduction methods and novel enhancements to them utilizing SoG Representations. Efficacy of the SoG enhanced representations were studied utilizing common Machine Learning (ML) interpretable classifier designs with the SoG representations indicating significant improvement of common analysis metrics.

Approximate And Sample Entropy Of Center Of Pressure In Unperturbed Tandem Standing: Contribution Of Embedding Dimension And Tolerance, Jayla Mashae Wesley

Masters Theses

Approximate entropy (ApEn) and sample entropy (SampEn) are statistical methods designed to quantify the regularity or predictability of a time series. Although ApEn has been a prominent choice for use, it is currently unclear as to which method and parameter selection combination is optimal for its application in biomechanics. The goal of this thesis was to examine the difference between ApEn and SampEn related to center of pressure (COP) data during standing balance tasks, while also refining tolerance r, to determine entropy optimization. Six participants completed five 30-second, feet together and tandem standing, trials under eyes-open and eyes-closed conditions. Ground …

Power Amplifier Based On Composite Injection-Voltaic Transistors, Nodira Batirdjanovna Alimova

Chemical Technology, Control and Management

The problem of high-current radio engineering devices is related to the fact that the use of high-power transistors and other semiconductor devices is limited by such a phenomenon as a secondary breakdown, in which there is a sharp decrease in the voltage on the device with simultaneous internal current lacing, and the device fails. To solve the problem of secondary breakdown, schemes have been proposed that operate stably at reverse voltage values 4-5 times higher than usual and at power dissipation 2-3 times higher than the maximum allowable power for an individual device. The problem is proposed to be solved …

Portable Diffuse Reflectance Spectroscopy For Non-Invasive And Quantitative Assessment Of The Parathyroid Glands Viability During Surgery, Mark Romine, Linh Luong, Alex Moazzen, Katie Cho, Paul Lee

Symposium of Student Scholars

Portable Diffuse Reflectance Spectroscopy for Non-invasive and Quantitative Assessment of the Parathyroid Glands Viability During Surgery

Mark Romine, Linh Luong, Alex Moazzen, Katie Cho and Paul Lee

The parathyroid glands (PTGs) are responsible for the regulation of calcium levels in the blood by secreting a parathyroid hormone. This parathyroid hormone then regulates the body’s absorption, storage, and secretion of calcium, which can directly affect the way muscles and nerves operate. PTGs are often at risk of damage, or accidental removal during thyroid surgeries, because it is challenging to identify PTGs and to determine their viability. Current methods of visual inspections …

Investigating The Use Of Recurrent Neural Networks In Modeling Guitar Distortion Effects, Caleb Koch, Scott Hawley, Andrew Fyfe

Belmont University Research Symposium (BURS)

Guitar players have been modifying their guitar tone with audio effects ever since the mid-20th century. Traditionally, these effects have been achieved by passing a guitar signal through a series of electronic circuits which modify the signal to produce the desired audio effect. With advances in computer technology, audio “plugins” have been created to produce audio effects digitally through programming algorithms. More recently, machine learning researchers have been exploring the use of neural networks to replicate and produce audio effects initially created by analog and digital effects units. Recurrent Neural Networks have proven to be exceptional at modeling audio effects …

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

Research Of Three-Phases Current’S Transducers Of Filter-Compensation Devices For Control Reactive Power’S Consumption Of Asynchronous Motor, Ilkhomjon Khakimovich Siddikov, Dilyorbek Karimjonov Doniyorbek O'G'Li -, Abdumutal Abdikarimovich Abdigapirov

Chemical Technology, Control and Management

In the article given materials of developing of three-phase electromagnetic current transducers of reactive power, using with asynchronous motor, methods connecting of two sensing element, series, parallel and differential and loops suitable for each phase, dynamic characteristics of output signals of three-phase electromagnetic current transducers asynchronous motor.

On the basis of modern calculation and design complexes are of great importance in the research variable sizes of three-phase current electromagnetic transducers of filter-compensation devices of reactive power of asynchronous motors. Presented mathematical model of research of electrical, electromagnetic and magnetic elements of electromagnetic current transducers in the …

On Refinements To Qmfd Based Chirp Parameter Estimation, Balu Santhanam, Thalanayar Santhanam

Electrical & Computer Engineering Technical Reports

Commuting matrix methods furnish a full basis of orthog- onal eigenvectors for the discrete Fourier transform or its centered version needed for computing the discrete fractional Fourier transform and multicomponent chirp signal analysis. However, these approaches suffer from ill-conditioning issues at higher matrix sizes, and require a computationally expensive eigenvalue decomposition.

In this paper, ill-conditioning issues associated with the QMFD approach developed previously by the authors are addressed via diagonal modification. Further symmetries of the eigenvectors are used to reduce the size of the underlying eigenvalue problem. These modifications are then incorporated into the real-arithmetic implementation of the QMFD approach …

An Epileptic Seizure Detection Method From Eeg Signals Based On A Classifier-Driven Feature Reduction Technique, Raymond N. Kamel

Theses and Dissertations

Epileptic seizure detection can improve the quality of life of epileptic patients, allow for more accurate medication, and minimize the risk of sudden unexpected death in epilepsy (SUDEP). This thesis work aims to develop a robust and stable algorithm for epileptic seizure detection through the classification of EEG signals. To achieve this aim, a methodology is proposed to develop a classifier that can differentiate between the healthy (normal), interictal, and ictal states of EEG signals, while maximizing the classification accuracy and minimizing the computational redundancy. The main pillar upon which this methodology is designed is using a problem-specific classifier-driven feature …

Editorial, Sameeh Ullah Dr.

International Journal of Smart Sensor and Adhoc Network

This special issue seeks papers that provide a convergent research perspective on business futures, i.e., research that draws on many disciplinary views and strives to establish fresh integrative frameworks and vocabularies. Addressing the difficulty of work culture and intelligent machines in a broad sense necessitates grappling with complicated issues such as motivation, cognition, machine learning, human learning, and system design, among others.

Accelerating A Software Defined Satnav Receiver Using Multiple Parallel Processing Schemes, Logan Reich, Sanjeev Gunawardena, Michael Braasch

Faculty Publications

Excerpt: Satnav SDRs present many benefits in terms of flexibility and configurability. However, due to the high bandwidth signals involved in satnav SDR processing, the software must be highly optimized for the host platform in order to achieve acceptable runtimes. Modules such as sample decoding, carrier replica generation, carrier wipeoff, and correlation are computationally intensive components that benefit from accelerations.

Live-Sky Gnss Signal Processing Using A Dual-Polarized Antenna Array For Multipath Mitigation, Eric Hahn, Sanjeev Gunawardena, Chris Bartone

Faculty Publications

Excerpt: Multipath results from reflections of Global navigation satellite signals (GNSS) signals arriving at a receiver that are delayed with respect to the desired line-of-sight (LOS) signals. The delayed signals distort the received LOS signals, thereby causing pseudorange and carrier phase measurement errors. Traditional multipath mitigation techniques include antenna gain pattern shaping (primarily to reduce ground multipath) and correlator gating techniques (such as narrow correlator and double-delta correlator [1]).

Simulations Of Implementation Of Advanced Communication Technologies, Ivy Yousuf Moutushi

Graduate Theses, Dissertations, and Problem Reports

Wireless communication systems have seen significant advancements with the introduction of 3G, 4G, and 5G mobile standards. Since the simulation of entire systems is complex and may not allow evaluation of the impact of individual techniques, this thesis presents techniques and results for simulating the performance of advanced signaling techniques used in 3G, 4G, and 5G systems, including Code division multiple access (CDMA), Multiple Input Multiple Output (MIMO) systems, and Low-Density Parity Check (LDPC) codes. One implementation issue that is explored is the use of quantized Analog to Digital Converter (ADC) outputs and their impact on system performance.

Code division …

Computational Mechanisms Of Face Perception, Jinge Wang

Graduate Theses, Dissertations, and Problem Reports

The intertwined history of artificial intelligence and neuroscience has significantly impacted their development, with AI arising from and evolving alongside neuroscience. The remarkable performance of deep learning has inspired neuroscientists to investigate and utilize artificial neural networks as computational models to address biological issues. Studying the brain and its operational mechanisms can greatly enhance our understanding of neural networks, which has crucial implications for developing efficient AI algorithms. Many of the advanced perceptual and cognitive skills of biological systems are now possible to achieve through artificial intelligence systems, which is transforming our knowledge of brain function. Thus, the need for …

Eeg-Based Spanish Language Proficiency Classification: An Eeg Power Spectrum And Cross-Spectrum Analysis, Blaise Xavier O'Mara, Skyler Baumer

Honors Theses and Capstones

Second language proficiency may be predicted with electrophysiological techniques. In a machine learning application, this electrophysiological data may be used for language instructors and language students to assess their language learning. This study identifies how electroencephalogram (EEG) power spectrum and cross spectrum data of the brain cortex relates to Spanish second language (L2) proficiency of 20 Spanish language students of varying proficiency levels at the University of New Hampshire. The two metrics for assessing cortical power and processing were event-related desynchronization (ERD)—a measure of relative change in power—of the alpha (8-12 Hz) brain frequency band, and alpha and beta (13-30Hz) …

Enhancing Traffic Safety In Unpredicted Environments With Integration Of Adas Features With Sensor Fusion In Intelligent Electric Vehicle Platform With Implementation Of Environmental Mapping Technology, David S. Obando Ortegon

Electronic Theses and Dissertations

A major objective on society is to reduce the number of accidents and fatalities on the road for drivers, and pedestrians. Therefore, the automotive engineering field is working on this problem through the development and integration of safety technologies such as advanced driving assistance systems. For this reason, this work was intended to develop and evaluate the performance of different ADAS features and IV technologies under unexpected scenarios. This by the development of safety algorithms applied to the intelligent electric vehicle designed and built in this work, through the use of ADAS sensors based on sensor fusion. Evaluation of AEB, …

Botsitter, Maria Hatzis, Gregory Blondheim Jr., Marian Bonto, Brett Jacobsen

Williams Honors College, Honors Research Projects

As society progresses into an era where both parents work, whether it is online or in person, children in the home may be put in dangerous situations if they are not given the attention they need. The BotSitter is an automated system that follows the child around and makes an audio alarm to alert both the child and the nearby guardian. Using RSSI trilateration, predetermined danger areas, and embedded controls, the BotSitter will be able to follow the child. The device can manage to keep track of the child for the guardian while being almost completely automated outside of setup.

Predicting Jamming Systems Frequency Hopping Sequences Using Artificial Neural Networks, Charles Strickland

Electronic Theses and Dissertations

This work proposes a neural network architecture that was designed to predict and reverse engineer frequency hopping jamming systems. The neural network was initially optimized for use with a 12th order linear shift feedback register maximum length sequence utilizing a minimal polynomial as the characteristic polynomial. This neural network was then scaled to accommodate 7 different sequences, of orders 6 through 12. The neural network was trained for these sequences using training data that is 10 times the length of the sequence. This information is then used to generate a hopping sequence that reduces the jamming interference to 0 with …

Wifi Sensing At The Edge Towards Scalable On-Device Wireless Sensing Systems, Steven M. Hernandez

Theses and Dissertations

WiFi sensing offers a powerful method for tracking physical activities using the radio-frequency signals already found throughout our homes and offices. This novel sensing modality offers continuous and non-intrusive activity tracking since sensing can be performed (i) without requiring wearable sensors, (ii) outside the line-of-sight, and even (iii) through the wall. Furthermore, WiFi has become a ubiquitous technology in our computers, our smartphones, and even in low-cost Internet of Things devices. In this work, we consider how the ubiquity of these low-cost WiFi devices offer an unparalleled opportunity for improving the scalability of wireless sensing systems. Thus far, WiFi sensing …