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Articles 1 - 30 of 37
Full-Text Articles in Signal Processing
Multi-Modal Depth Estimation Using Camera And Mmwave Sensors, Alston D. Devero-Belfon
Multi-Modal Depth Estimation Using Camera And Mmwave Sensors, Alston D. Devero-Belfon
Student Theses
For accurately estimating the depth of environments with varying lighting conditions, reliable methods are limited. By utilizing wireless sensor technology in conjunction with cameras, a wide range of environments can be visualized, and objects within these environments can be tracked and monitored. Such methods offer cost-effective alternatives and provide a more secure, data-at-rest option for individuals with low vision, while also enhancing machine perception. In this work, we develop such a prototype that utilizes wireless sensors and cameras, which act in sync, enabling us to estimate the depth of objects within varying lighting environments to a level that is recognizable …
On The Provenance Of Software Systems: Automating Software Traceability With Knowledge Graph And Large Language Model Synergy, Tyler Procko
On The Provenance Of Software Systems: Automating Software Traceability With Knowledge Graph And Large Language Model Synergy, Tyler Procko
Doctoral Dissertations and Master's Theses
The present dissertation delineates a system that enables those engaged in software development to automatically generate and maintain project life cycle provenance. All projects are implemented and made manifest with the development of artifacts, e.g., papers, code files, etc. Tools exist to accelerate artifact creation, but little focus is paid to the processes that produce them. In terms of Ontology, or, from Ancient Greek, the study of being, the two most basic entities in reality are Continuant and Occurrent, or, roughly, “Artifact” and “Process”. This dissertation posits that for any created artifact, its process of creation, i.e., its life …
Island Nation Duress: Simulating Passive Peer-To-Peer Bluetooth Communication During Disaster Relief, Jason K. Medeiros
Island Nation Duress: Simulating Passive Peer-To-Peer Bluetooth Communication During Disaster Relief, Jason K. Medeiros
Theses and Dissertations
Pacific Islands under U.S. jurisdiction are highly vulnerable to natural disasters, yet many lack the infrastructure to effectively respond and recover. Clear communication during and after such events is critical for evacuation, hazard awareness, and first responders’ coordination. This research explores a simulation-based approach using Bluetooth communication to relay messages across Guam, assessing its efficiency through statistical analysis. By examining regional differences and geographic impacts on Bluetooth messaging, the study aims to identify key factors that enhance peer-to-peer communication for timely and effective disaster response.
Aerospace Vehicle Comprising Module For Method Of Terrain, Terrain Activity And Material Classification, Matthew E. Nussbaum, Marissa S. Herron
Aerospace Vehicle Comprising Module For Method Of Terrain, Terrain Activity And Material Classification, Matthew E. Nussbaum, Marissa S. Herron
AFIT Patents
A method of classifying terrain, terrain activity and materials through panchromatic imagery a module programmed to provide such classification and aerospace vehicles comprising such module is provided. Panchromatic images of known materials terrains and terrain activities are taken and processed to form a multiband texture cube, that due it amount of data, is stored as a computer data base. New panchromatic images of unclassified materials, terrains and/or terrain activities are processed and compared via computer with such database that allows for inexpensive, quick and efficient classification of such new images.
Dung Dkar Cloak: Exploring Soft Interfaces For Sonic Interactions, Judit Eszter Kárpáti, Esteban De La Torre
Dung Dkar Cloak: Exploring Soft Interfaces For Sonic Interactions, Judit Eszter Kárpáti, Esteban De La Torre
Textile Society of America: Symposium Proceedings
The importance of crossmodal interaction within the contemporary cultural, technological and scientific panorama has evidently gained significant attention due to its remarkable advantages in creating a meaningful, interwoven, and integrated experience. The use and recontextualization of textiles in such exploratory quest into the human senses has proven to be critical. Computational science, algorithmic logic and digital devices have always been rooted and closely interwoven with textile crafts and practices. Recent technological advancements have further combined technology and textile, generating interactive textile surfaces, constructing endless possibilities for multisensorial experiences. In this presentation we will examine how we can weave a sensitive …
Extracting Edges In Space And Time During Visual Fixations, Lynn Schmittwilken, Marianne Maertens
Extracting Edges In Space And Time During Visual Fixations, Lynn Schmittwilken, Marianne Maertens
MODVIS Workshop
No abstract provided.
Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)
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 …
Emotion Detection Using An Ensemble Model Trained With Physiological Signals And Inferred Arousal-Valence States, Matthew Nathanael Gray
Emotion Detection Using An Ensemble Model Trained With Physiological Signals And Inferred Arousal-Valence States, Matthew Nathanael Gray
Electrical & Computer Engineering Theses & Dissertations
Affective computing is an exciting and transformative field that is gaining in popularity among psychologists, statisticians, and computer scientists. The ability of a machine to infer human emotion and mood, i.e. affective states, has the potential to greatly improve human-machine interaction in our increasingly digital world. In this work, an ensemble model methodology for detecting human emotions across multiple subjects is outlined. The Continuously Annotated Signals of Emotion (CASE) dataset, which is a dataset of physiological signals labeled with discrete emotions from video stimuli as well as subject-reported continuous emotions, arousal and valence, from the circumplex model, is used for …
Composite Style Pixel And Point Convolution-Based Deep Fusion Neural Network Architecture For The Semantic Segmentation Of Hyperspectral And Lidar Data, Kevin T. Decker, Brett J. Borghetti
Composite Style Pixel And Point Convolution-Based Deep Fusion Neural Network Architecture For The Semantic Segmentation Of Hyperspectral And Lidar Data, Kevin T. Decker, Brett J. Borghetti
Faculty Publications
Multimodal hyperspectral and lidar data sets provide complementary spectral and structural data. Joint processing and exploitation to produce semantically labeled pixel maps through semantic segmentation has proven useful for a variety of decision tasks. In this work, we identify two areas of improvement over previous approaches and present a proof of concept network implementing these improvements. First, rather than using a late fusion style architecture as in prior work, our approach implements a composite style fusion architecture to allow for the simultaneous generation of multimodal features and the learning of fused features during encoding. Second, our approach processes the higher …
Machine Learning Land Cover And Land Use Classification Of 4-Band Satellite Imagery, Lorelei Turner, Torrey J. Wagner, Paul Auclair, Brent T. Langhals
Machine Learning Land Cover And Land Use Classification Of 4-Band Satellite Imagery, Lorelei Turner, Torrey J. Wagner, Paul Auclair, Brent T. Langhals
Faculty Publications
Land-cover and land-use classification generates categories of terrestrial features, such as water or trees, which can be used to track how land is used. This work applies classical, ensemble and neural network machine learning algorithms to a multispectral remote sensing dataset containing 405,000 28x28 pixel image patches in 4 electromagnetic frequency bands. For each algorithm, model metrics and prediction execution time were evaluated, resulting in two families of models; fast and precise. The prediction time for an 81,000-patch group of predictions wasmodels, and >5s for the precise models, and there was not a significant change in prediction time when a …
Detecting User Emotions From Audio Conversations With The Smart Assistants, Sunanda Guha
Detecting User Emotions From Audio Conversations With The Smart Assistants, Sunanda Guha
Graduate Theses/Dissertations
With the proliferation of smart home devices like Google Home or Amazon Alexa, significant research endeavors are being carried out to improve the user experience while interacting with these smart assistants. One such dimension in this endeavor is ongoing research on successful emotion detection from short voice commands used in smart home environment. Besides facial expression and body language, etc., speech plays a pivotal role in the classification of emotions when it comes to smart home application. Upon successful implementation of accurate emotion recognition, the smart devices will be able to intelligently and empathetically suggest appropriate actions based on the …
Deepfakes, Shallowfakes, And The Need For A Private Right Of Action, Eric Kocsis
Deepfakes, Shallowfakes, And The Need For A Private Right Of Action, Eric Kocsis
Dickinson Law Review (2017-Present)
For nearly as long as there have been photographs and videos, people have been editing and manipulating them to make them appear to be something they are not. Usually edited or manipulated photographs are relatively easy to detect, but those days are numbered. Technology has no morality; as it advances, so do the ways it can be misused. The lack of morality is no clearer than with deepfake technology.
People create deepfakes by inputting data sets, most often pictures or videos into a computer. A series of neural networks attempt to mimic the original data set until they are nearly …
Bibliometric Review Of Predictive Maintenance Using Vibration Analysis, Aashna Midha Ms., Ishita Maheshwari Ms., Kaushik Ojha Mr., Kritika Gupta Ms., Shripad V. Deshpande Mr.
Bibliometric Review Of Predictive Maintenance Using Vibration Analysis, Aashna Midha Ms., Ishita Maheshwari Ms., Kaushik Ojha Mr., Kritika Gupta Ms., Shripad V. Deshpande Mr.
Library Philosophy and Practice (e-journal)
Every day the world is depending more and more on machines in almost every aspect of life. With the increasing use of machines, there also needs to be an evolution in the maintenance of these machines. Predictive maintenance is a process used to monitor the equipment and machinery during its operation to detect any damages and/or deteriorations and enable the required maintenance plan in advance, resulting in reduced operational costs and full utilization of tools and parts. The fundamental goal of this bibliometric review paper is a comprehension of the extent and sources of the literature available for predictive maintenance …
Design And Control Of A Peristaltic Pump To Simulate Left Atrial Pressure In A Conductive Silicone Model, Jeremy Collins
Design And Control Of A Peristaltic Pump To Simulate Left Atrial Pressure In A Conductive Silicone Model, Jeremy Collins
Mechanical Engineering Undergraduate Honors Theses
According to the CDC, atrial fibrillation is responsible for more than 454,000 hospitalizations and approximately 158,000 deaths per year. A common treatment for atrial fibrillation is catheter ablation, a process in which a long flexible tube is guided through the femoral artery and to the source of arrhythmia in the heart, where it measures the electrical potential at various locations and converts problematic heart tissue to scar tissue via ablation. This paper details the design and control of a low-cost ($400) peristaltic pump system using repetitive control to replicate blood pressure in the left atrium in a conductive silicone model …
Liver Segmentation And Liver Cancer Detection Based On Deep Convolutional Neural Network: A Brief Bibliometric Survey, Kiran Malhari Napte Mr., Anurag Mahajan Dr.
Liver Segmentation And Liver Cancer Detection Based On Deep Convolutional Neural Network: A Brief Bibliometric Survey, Kiran Malhari Napte Mr., Anurag Mahajan Dr.
Library Philosophy and Practice (e-journal)
Background: This study analyzes liver segmentation and cancer detection work, with the perspectives of machine learning and deep learning and different image processing techniques from the year 2012 to 2020. The study uses different Bibliometric analysis methods.
Methods: The articles on the topic were obtained from one of the most popular databases- Scopus. The year span for the analysis is considered to be from 2012 to 2020. Scopus analyzer facilitates the analysis of the databases with different categories such as documents by source, year, and county and so on. Analysis is also done by using different units of analysis such …
Time Series Data Analysis Using Machine Learning-(Ml) Approach, Mvv Prasad Kantipudi Dr., Pradeep Kumar N.S Dr., S.Sreenath Kashyap Dr., Ss Anusha Vemuri Ms
Time Series Data Analysis Using Machine Learning-(Ml) Approach, Mvv Prasad Kantipudi Dr., Pradeep Kumar N.S Dr., S.Sreenath Kashyap Dr., Ss Anusha Vemuri Ms
Library Philosophy and Practice (e-journal)
Healthcare benefits related to continuous monitoring of human movement and physical activity can potentially reduce the risk of accidents associated with elderly living alone at home. Based on the literature review, it is found that many studies focus on human activity recognition and are still active towards achieving practical solutions to support the elderly care system. The proposed system has introduced a joint approach of machine learning and signal processing technology for the recognition of human's physical movements using signal data generated by accelerometer sensors. The framework adopts the concept of DSP to select very descriptive feature sets and uses …
Atmospheric Turbulence Distortion In Video: Restoration Utilizing Sparse Analysis, Benjamin J. Sanda
Atmospheric Turbulence Distortion In Video: Restoration Utilizing Sparse Analysis, Benjamin J. Sanda
Dissertations
The removal of atmospheric turbulence (AT) distortion in long range imaging is one of the most challenging areas of research in imaging processing with an immediate need for solutions in several applications such as in military and transportation systems. AT exacerbates distortion due to non-linear geometric blur and scintillations in long-distance images and videos, severely reducing image quality and information interpretation. AT negatively impacts both human and computer vision systems, compromising visibility essential for accurate object identification and tracking.
In this dissertation, a novel sparse analysis framework is developed to address efficient AT blur and scintillation removal in video. Operating …
High Wind Alerts: A System Created With Observations From The X-Band Teaching And Research Radar, Lauren Warner
High Wind Alerts: A System Created With Observations From The X-Band Teaching And Research Radar, Lauren Warner
The Journal of Purdue Undergraduate Research
Following the August 13, 2011, Indiana State Fair stage collapse tragedy, caused by a wind gust from an approaching thunderstorm, Purdue University enforced a wind speed restriction of 30 mph (13 m s-1) for tents at outdoor events. During these events, volunteers stand outside with handheld anemometers, measuring and reporting when the wind speeds exceed this limit. In this study, we report testing of a new system to automate high-wind alerts based on observations from a Doppler radar, the X-band Teaching and Research Radar (XTRRA), near Purdue’s campus. XTRRA scans over campus at low elevations approximately every 5 minutes. Using …
How Can 5g Make Our Lives Better?, Firas Slewa Dawod
How Can 5g Make Our Lives Better?, Firas Slewa Dawod
International Programs
Our lives will be significantly improved with the advent of the new cellular wireless technology due to all its new features and applications. This Poster discusses the main features and application of 5G technology and its positive impact on society, in particular facilitating interactive and smart communities.
Exploring Effects Of Background Music In A Serious Game On Attention By Means Of Eeg Signals In Children, Fettah Kiran
Exploring Effects Of Background Music In A Serious Game On Attention By Means Of Eeg Signals In Children, Fettah Kiran
LSU Master's Theses
Music and Serious Games are separately useful alternative therapy methods for helping people with a cognitive disorder, including Attention Deficit Hyperactivity Disorder (ADHD). The goal of this thesis is to explore the effect of background music on children with and without ADHD. In this study, a simple Tetris game is designed with Beethoven, Mozart music, and no-music. There are different brainwave techniques for recording; among others, the electroencephalography (EEG) allows for the most efficient use of BCI. We recorded the EEG brain signals of the regular and ADHD subjects who played the Tetris we designed according to our protocol that …
Learning Set Representations For Lwir In-Scene Atmospheric Compensation, Nicholas M. Westing, Kevin C. Gross, Brett J. Borghetti, Jacob A. Martin, Joseph Meola
Learning Set Representations For Lwir In-Scene Atmospheric Compensation, Nicholas M. Westing, Kevin C. Gross, Brett J. Borghetti, Jacob A. Martin, Joseph Meola
Faculty Publications
Atmospheric compensation of long-wave infrared (LWIR) hyperspectral imagery is investigated in this article using set representations learned by a neural network. This approach relies on synthetic at-sensor radiance data derived from collected radiosondes and a diverse database of measured emissivity spectra sampled at a range of surface temperatures. The network loss function relies on LWIR radiative transfer equations to update model parameters. Atmospheric predictions are made on a set of diverse pixels extracted from the scene, without knowledge of blackbody pixels or pixel temperatures. The network architecture utilizes permutation-invariant layers to predict a set representation, similar to the work performed …
The Challenge For Vision Of Fluctuating Real-World Illumination, David H. Foster
The Challenge For Vision Of Fluctuating Real-World Illumination, David H. Foster
MODVIS Workshop
No abstract provided.
Multi-Sensor Data Fusion Between Radio Tomographic Imaging And Noise Radar, Christopher Vergara
Multi-Sensor Data Fusion Between Radio Tomographic Imaging And Noise Radar, Christopher Vergara
Theses and Dissertations
The lack of situational awareness within an operational environment is a problem that carries high risk and expensive consequences. Radio Tomographic Imaging (RTI) and noise radar are two proven technologies capable of through-wall imaging and foliage penetration. The intent of this thesis is to provide a proof of concept for the fusion of data from RTI and noise radar. The output of this thesis will consist of a performance comparison between the two technologies followed by the derivation of a fusion technique to produce a single image. Proposals have been made for the integration of multiple-input multiple-output (MIMO) radar with …
Non-Gnss Smartphone Pedestrian Navigation Using Barometric Elevation And Digital Map-Matching, Daniel Broyles, Kyle J. Kauffman, John F. Raquet, Piotr Smagowski
Non-Gnss Smartphone Pedestrian Navigation Using Barometric Elevation And Digital Map-Matching, Daniel Broyles, Kyle J. Kauffman, John F. Raquet, Piotr Smagowski
Faculty Publications
Pedestrian navigation in outdoor environments where global navigation satellite systems (GNSS) are unavailable is a challenging problem. Existing technologies that have attempted to address this problemoften require external reference signals or specialized hardware, the extra size,weight, power, and cost of which are unsuitable for many applications. This article presents a real-time, self-contained outdoor navigation application that uses only the existing sensors on a smartphone in conjunction with a preloaded digital elevation map. The core algorithm implements a particle filter, which fuses sensor data with a stochastic pedestrian motion model to predict the user’s position. The smartphone’s barometric elevation is then …
Detecting Suicide Risk From Wristworn Activity Tracker Data Using Machine Learning Approaches, Pallavi Atluri
Detecting Suicide Risk From Wristworn Activity Tracker Data Using Machine Learning Approaches, Pallavi Atluri
Electrical Engineering Theses
Suicide is a prevalent cause of death worldwide and depression is a primary concern of many suicidal acts. It is possible that an individual during depression never has any suicidal thoughts at all. On the other hand, some individuals in stable condition with no apparent symptoms of depression feel urges to commit suicide (suicidal ideation). Many such individuals never let anyone know what they are feeling or planning. Suicidal ideation considered an important precursor to suicidal acts.
Detecting the suicide risk in individuals with mood disorders is a major challenge. The current clinical practice to assess suicide risk in these …
Color Algebras, Jeffrey B. Mulligan
An Image-Based Model For Early Visual Processing, Heiko H. Schütt, Felix A. Wichmann
An Image-Based Model For Early Visual Processing, Heiko H. Schütt, Felix A. Wichmann
MODVIS Workshop
No abstract provided.
Automated Synthetic Scene Generation, Ryan N. Givens
Automated Synthetic Scene Generation, Ryan N. Givens
Theses and Dissertations
First principles, physics-based models help organizations developing new remote sensing instruments anticipate sensor performance by enabling the ability to create synthetic imagery for proposed sensor before a sensor is built. One of the largest challenges in modeling realistic synthetic imagery, however, is generating the spectrally attributed, three-dimensional scenes on which the models are based in a timely and affordable fashion. Additionally, manual and semi-automated approaches to synthetic scene construction which rely on spectral libraries may not adequately capture the spectral variability of real-world sites especially when the libraries consist of measurements made in other locations or in a lab. This …
Evaluation Of Video Based Pedestrian And Vehicle Detection Algorithms, Varun Bandarupalli
Evaluation Of Video Based Pedestrian And Vehicle Detection Algorithms, Varun Bandarupalli
UNLV Theses, Dissertations, Professional Papers, and Capstones
Video based detection systems rely on the ability to detect moving objects in video streams. Video based detection systems have applications in many fields like, intelligent transportation, automated surveillance etc. There are many approaches adopted for video based detection. Evaluation and selecting a suitable approach for pedestrian and vehicle detection is a challenging task. While evaluating the object detection algorithms, many factors should be considered in order to cope with unconstrained environments, non stationary background, different object motion patterns and the variation in types of object being detected.
In this thesis, we implement and evaluate different video based detection algorithms …
Measuring Variations Of Mimicry By Means Of Prosodic Cues In Task-Based Scenarios And Conversational Speech, Brian Vaughan, Celine De Looze
Measuring Variations Of Mimicry By Means Of Prosodic Cues In Task-Based Scenarios And Conversational Speech, Brian Vaughan, Celine De Looze
Other resources
Here, we address the measurement of mimicry, that is when speakers’ speech variations look like parallel patterns.
As a definition of mimicry, we often read in the literature description such as mimicry is “The situation where the observed behaviours of two inter-actants although dissimilar at the start of the interaction are moving towards behavioral matching”. These types of descriptions imply that mimicry is a linear phenomenon and that speakers tend to imitate over time. However, it can be assumed, especially when studying spontaneous speech, that there are rather phases of mimicry and non-mimicry and that mimicry should be rather …