Study On The Pattern Recognition Enhancement For Matrix Factorizations With Automatic Relevance Determination, 2018 California State University, San Bernardino
Study On The Pattern Recognition Enhancement For Matrix Factorizations With Automatic Relevance Determination, Hau Tao
Electronic Theses, Projects, and Dissertations
Learning the parts of objects have drawn more attentions in computer science recently, and they have been playing the important role in computer applications such as object recognition, self-driving cars, and image processing, etc… However, the existing research such as traditional non-negative matrix factorization (NMF), principal component analysis (PCA), and vector quantitation (VQ) has not been discovering the ground-truth bases which are basic components representing objects. On this thesis, I am proposed to study on pattern recognition enhancement combined non-negative matrix factorization (NMF) with automatic relevance determination (ARD). The main point of this research is to propose a new technique ...
Transcribing Braille Code: Learning Equations Across Platforms, 2018 Purdue University
Transcribing Braille Code: Learning Equations Across Platforms, Deegan Atha, Courtney Balogh
Purdue Journal of Service-Learning and International Engagement
Deegan Atha, a graduating senior in electrical engineering and a future engineer, is interested in human-centered design and developing technology that helps students engage and be successful in STEM.
Courtney Balogh, a junior in mechanical engineering, is interested in human-centered design and the importance it plays in product development. Deegan and Courtney are members of the Purdue EPICS project, Learning Equations Across Platforms (LEAP). They partnered with the Indiana School for the Blind and Visually Impaired (ISBVI) to develop a braille transcription device and web application that converts braille to print in real time.
Erasure Coding For Distributed Matrix Multiplication For Matrices With Bounded Entries, 2018 Iowa State University
Erasure Coding For Distributed Matrix Multiplication For Matrices With Bounded Entries, Li Tang, Konstantinos Konstantinidis, Aditya Ramamoorthy
Electrical and Computer Engineering Publications
Distributed matrix multiplication is widely used in several scientific domains. It is well recognized that computation times on distributed clusters are often dominated by the slowest workers (called stragglers). Recent work has demonstrated that straggler mitigation can be viewed as a problem of designing erasure codes. For matrices A and B, the technique essentially maps the computation of ATB into the multiplication of smaller (coded) submatrices. The stragglers are treated as erasures in this process. The computation can be completed as long as a certain number of workers (called the recovery threshold) complete their assigned tasks. We present a novel ...
End-To-End Deep Learning Systems For Scene Understanding, Path Planning And Navigation In Fire Fighter Teams, 2018 University of New Mexico
End-To-End Deep Learning Systems For Scene Understanding, Path Planning And Navigation In Fire Fighter Teams, Manish Bhattarai
Shared Knowledge Conference
Firefighting is a dynamic activity with many operations occurring simultaneously. Maintaining situational awareness, defined as knowledge of current conditions and activities at the scene, are critical to accurate decision making. Firefighters often carry various sensors in their personal equipment, namely thermal cameras, gas sensors, and microphones. Improved data processing techniques can mine this data more effectively and be used to improve situational awareness at all times thereby improving real-time decision making and minimizing errors in judgment induced by environmental conditions and anxiety levels. This objective of this research employs state of the art Machine Learning (ML) techniques to create an ...
1 - A Comprehensive Study Of Motor Imagery Eeg-Based Classification Using Computational Analysis, 2018 Georgia Southern University
1 - A Comprehensive Study Of Motor Imagery Eeg-Based Classification Using Computational Analysis, Justin Mccorkle, Andrew Kalaani
Georgia Undergraduate Research Conference (GURC)
Brain computer interfaces (BCI) are systems that integrate a user’s neural features with robotic machines to perform tasks. BCI systems are very unstable still due to Electroencephalography (EEG) having interference from unanticipated noise. Using Independent Component Analysis (ICA), a novel variable threshold model for noise feature extraction. The de-noised EEG data is classified with a high accuracy of more than 94% when using artificial neural networks. The effectiveness of the proposed variable threshold model is validated by the significant reduction in the variance of user classification accuracy across multiple sessions. Nonetheless, based on the variance and classification, subjects are ...
A Deep Learning-Based Approach For Fault Diagnosis Of Roller Element Bearings, 2018 Iowa State University
A Deep Learning-Based Approach For Fault Diagnosis Of Roller Element Bearings, Mohammakazem Sadoughi, Austin Downey, Garrett Bunge, Aditya Ranawat, Chao Hu, Simon Laflamme
Civil, Construction and Environmental Engineering Conference Presentations and Proceedings
Condition monitoring and fault detection of roller element bearings is of vital importance to ensuring safe and reliable operation of rotating machinery systems. Over the past few years, convolutional neural network (CNN) has been recognized as a useful tool for fault detection of roller element bearings. Unlike the traditional fault diagnosis approaches, CNN does not require manually extracting the fault-related features from the raw sensor data and most CNN-based fault diagnosis approaches feed the raw or shallowly pre-processed data as the training/testing inputs to a CNN model, thereby avoiding the need for manual feature extraction. As such, these approaches ...
Signal Identification In Discrete-Time Based On Internal-Model-Principle, 2018 The University of Western Ontario
Signal Identification In Discrete-Time Based On Internal-Model-Principle, Jie Chen
Electronic Thesis and Dissertation Repository
This work presents an implementation of a signal identification algorithm which is based on the internal model principle. By using several internal models in feedback with a tuning function, this algorithm can decompose a signal into narrow-band signals and identify the frequencies, amplitudes and relative phases. A desired band-pass filter response can be achieved by selecting appropriate coefficients of the controllers and tuning functions, which can reject the noise and improve the performance. To achieve a result with fast transient characteristics, this system is then modified by adding a low-pass filter. This work is based on the previous work in ...
The Hilbert-Huang Transform: A Theoretical Framework And Applications To Leak Identification In Pressurized Space Modules, Kenneth R. Bundy
Electronic Theses and Dissertations
Any manned space mission must provide breathable air to its crew. For this reason, air leaks in spacecraft pose a danger to the mission and any astronauts on board. The purpose of this work is twofold: the first is to address the issue of air pressure loss from leaks in spacecraft. Air leaks present a danger to spacecraft crew, and so a method of finding air leaks when they occur is needed. Most leak detection systems localize the leak in some way. Instead, we address the identification of air leaks in a pressurized space module, we aim to determine the ...
Remote Sensing Using I-Band And S-Band Signals Of Opportunity, 2018 Purdue University
Remote Sensing Using I-Band And S-Band Signals Of Opportunity, Kadir Efecik, Benjamin R. Nold, James L. Garrison
The Summer Undergraduate Research Fellowship (SURF) Symposium
Measurement of soil moisture, especially the root zone soil moisture, is important in agriculture, meteorology, and hydrology. Root zone soil moisture is concerned with the first meter down the soil. Active and passive remote sensing methods used today utilizing L-band(1-2GHz) are physically limited to a sensing depth of about 5 cm or less. To remotely sense the soil moisture in the deeper parts of the soil, the frequency should be lowered. Lower frequencies cannot be used in active spaceborne instruments because of their need for larger antennas, radio frequency interference (RFI), and frequency spectrum allocations. Ground-based passive remote sensing ...
Deep Neural Network Architectures For Modulation Classification Using Principal Component Analysis, Sharan Ramjee, Shengtai Ju, Diyu Yang, Aly El Gamal
The Summer Undergraduate Research Fellowship (SURF) Symposium
In this work, we investigate the application of Principal Component Analysis to the task of wireless signal modulation recognition using deep neural network architectures. Sampling signals at the Nyquist rate, which is often very high, requires a large amount of energy and space to collect and store the samples. Moreover, the time taken to train neural networks for the task of modulation classification is large due to the large number of samples. These problems can be drastically reduced using Principal Component Analysis, which is a technique that allows us to reduce the dimensionality or number of features of the samples ...
High Dynamic Range Optical Devices And Applications., 2018 University of Louisville
High Dynamic Range Optical Devices And Applications., Elijah Robert Jensen
Electronic Theses and Dissertations
Much of what we know about fundamental physical law and the universe derives from observations and measurements using optical methods. The passive use of the electromagnetic spectrum can be the best way of studying physical phenomenon in general with minimal disturbance of the system in the process. While for many applications ambient visible light is sufficient, light outside of the visible range may convey more information. The signals of interest are also often a small fraction of the background, and their changes occur on time scales so quickly that they are visually imperceptible. This thesis reports techniques and technologies developed ...
Hand Movement Detection In Collaborative Learning Environment Videos, 2018 University of New Mexico
Hand Movement Detection In Collaborative Learning Environment Videos, Callie J. Darsey
Electrical and Computer Engineering ETDs
Human activity detection in digital videos is currently attracting significant research interest. This problem is especially challenging for video datasets that have a lot of human activity, illumination noise, and structural noise. The video dataset associated with the Advancing Out of School Learning in Mathematics and Engineering (AOLME) project has these challenges. ALOME videos have been used in the study of human activities “in the wild”.
This thesis explores detection of hand movement using color and optical flow. Exploratory analysis considered the problem component wise on components created from thresholds applied to motion and color. The proposed approach uses patch ...
Mitigating Interference With Knowledge-Aided Subarray Pattern Synthesis And Space Time Adaptive Processing, 2018 Air Force Institute of Technology
Mitigating Interference With Knowledge-Aided Subarray Pattern Synthesis And Space Time Adaptive Processing, Yongjun Yoon
Theses and Dissertations
Phased arrays are essential to airborne ground moving target indication (GMTI), as they measure the spatial angle-of-arrival of the target, clutter, and interference signals. The spatial and Doppler (temporal) frequency is utilized by space-time adaptive processing (STAP) to separate and filter out the interference from the moving target returns. Achieving acceptable airborne GMTI performance often requires fairly large arrays, but the size, weight and power (SWAP) requirements, cost and complexity considerations often result in the use of subarrays. This yields an acceptable balance between cost and performance while lowering the system’s robustness to interference. This thesis proposes the use ...
New Algorithms For Compressed Sensing Of Mri: Wtwts, Dwts, Wdwts, 2018 Kennesaw State University
New Algorithms For Compressed Sensing Of Mri: Wtwts, Dwts, Wdwts, Srivarna Settisara Janney
Master of Science in Computer Science Theses
Magnetic resonance imaging (MRI) is one of the most accurate imaging techniques that can be used to detect several diseases, where other imaging methodologies fail. MRI data takes a longer time to capture. This is a pain taking process for the patients to remain still while the data is being captured. This is also hard for the doctor as well because if the images are not captured correctly then it will lead to wrong diagnoses of illness that might put the patients lives in danger. Since long scanning time is one of most serious drawback of the MRI modality, reducing ...
"Dual Peaks" Analog Distortion Guitar Effects Pedal, 2018 California Polytechnic State University, San Luis Obispo
"Dual Peaks" Analog Distortion Guitar Effects Pedal, Dave Raul Breuer
No abstract provided.
Fpga-Based Dsp System, 2018 California Polytechnic State University, San Luis Obispo
Fpga-Based Dsp System, Aaron Nguyen
The purpose of this project is to create a modular FPGA-based filtering system for audio in VHDL. The final implementation has a working input, output, and filtering system but the filtering system still must be fine-tuned.
2018 Ieee Signal Processing Cup: Forensic Camera Model Identification Challenge, 2018 Union College
2018 Ieee Signal Processing Cup: Forensic Camera Model Identification Challenge, Michael Geiger
The goal of this Senior Capstone Project was to lead Union College’s first ever Signal Processing Cup Team to compete in IEEE’s 2018 Signal Processing Cup Competition. This year’s competition was a forensic camera model identification challenge and was divided into two separate stages of competition: Open Competition and Final Competition. Participation in the Open Competition was open to any teams of undergraduate students, but the Final Competition was only open to the three finalists from Open Competition and is scheduled to be held at ICASSP 2018 in Calgary, Alberta, Canada. Teams that make it to the ...
Collision Avoidance Smartphone, 2018 California Polytechnic State University, San Luis Obispo
Collision Avoidance Smartphone, Aaron Parisi, Luis Wong, Joey Schnecker, Matt Columbres
There are many instances in day-to-day life where people cannot or would rather not pay full attention to their surroundings. Walking while preoccupied with a smartphone or walking while blind are excellent examples where technology could be used to make the task of avoiding 2collisions reactive, instead of proactive. A device which monitors a user’s surroundings and notifies the user when a potential collision is detected (and, additionally, notifying them as to where the obstacle is with respect to them) could be used to make walking distracted less of a hazard for the user and those around the user ...
Portable High-Definition Audio Spectrum Analyzer, 2018 California Polytechnic State University, San Luis Obispo
Portable High-Definition Audio Spectrum Analyzer, Alex Zahn, Jamie Corr
The Portable High-definition Audio Spectrum Analyzer (PHASA) allows the user to visualize the audio frequency spectrum of an incoming line-level stereo audio signal. Upon pressing the touch screen spectrum graph, the PHASA displays the corresponding frequency and volume levels as well as crosshairs at the touched location. The PHASA features multiple left/right channel display modes— Left channel only, right channel only, both channels simultaneously, and the average between the two channels. The PHASA features multiple resolution display modes (standard-resolution and high-resolution) and multiple dynamics display modes (standard dynamics, averaging, and peak/hold). The PHASA accepts input audio via a ...
The Design, Building, And Testing Of A Constant On Discreet Jammer For The Ieee 802.15.4/Zigbee Wireless Communication Protocol, 2018 ter California Polytechnic State University – San Luis Ob
The Design, Building, And Testing Of A Constant On Discreet Jammer For The Ieee 802.15.4/Zigbee Wireless Communication Protocol, Alexandre J. Marette
Master's Theses and Project Reports
As wireless protocols become easier to implement, more products come with wireless connectivity. This latest push for wireless connectivity has left a gap in the development of the security and the reliability of some protocols. These wireless protocols can be used in the growing field of IoT where wireless sensors are used to share information throughout a network. IoT is being implemented in homes, agriculture, manufactory, and in the medical field. Disrupting a wireless device from proper communication could potentially result in production loss, security issues, and bodily harm. The 802.15.4/ZigBee protocol is used in low power ...