Signal Processing Commons^™

The Effects Of The Transient And Performance Loss Rates On Pv Output Performance, Chibuisi Chinasaokwu Okorieimoh, Brian Norton, Michael Conlon

Conference papers

Solar photovoltaic (PV) panels experience long-term performance degradation as compared to their initial performance, resulting in lower like-per-like efficiencies and performance ratios. Manufacturers of solar photovoltaic modules normally guarantee a lifespan of more than 20 years. To meet such commitments, it is important to monitor and mitigate PV module degradation during this period, as well as beyond, to recognize maintenance and repair needs. Solar PV modules degrade over time, becoming less effective, less reliable, and eventually unusable. The effects of transient and performance loss rates on the output performance of polycrystalline silicon (p-Si) solar PV modules are the focus of …

Extending Instantaneous De-Mixing Algorithms To Anechoic Mixtures, Swarnadeep Bagchi, Ruairí De Fréin

Conference papers

The AdRess algorithm separates sources that are mixed using stereo, pan-mixing in a computationally efficient way. Pan-mixing gives the sources a location in the stereo field by introducing a relative attenuation between the versions of the sources that appear on each channel. AdRess achieves separation by constructing only a frequency-attenuation matrix. We introduce a new algorithm called Delayed-AdRess (D-AdRess), where, in addition to the frequency-attenuation matrix, two other matrices namely, frequency-delay and time-delay are used to separate sources from anechoic mixtures. By anechoic mixtures, we mean mixing scenarios where both attenuation and delays are experienced by the source signals.

Design And Fabrication Of Zinc Oxide Optofluidic Laser Elements, Kyle T. Bodily

Theses and Dissertations

This thesis systematically goes through the derivation, simulation, and experimentation of Zinc Oxide optofluidic micro laser elements. Single and coupled ring resonators were simulated to show single mode transmission as well as enhanced coupling capabilities when surrounded by high refractive index liquid. Devices with diameters ranging from 100-500 µm were successfully fabricated inexpensively through standard cleanroom procedures. The devices were tested using two different pump laser systems. Testing included such factors as high pump intensity, various angles of excitation, and low temperature. In all cases PL emission was observed and recorded.

Sar Collection Planning And Data Quality Assessment, Jacob M. Brumfield

Theses and Dissertations

Radar resource management is an important research topic in the radar community. Identifying the performance of a synthetic aperture radar image early into a data processing chain can improve intelligence collection mission performance. To achieve that goal, separate flags can be presented to a radar technician along a data processing chain to identify various errors within a data collection. Toward the end, this thesis analyzes he radar image processing chain and identifies data quality checks that could be implemented. The first quality check is to identify canonical targets and the necessary Nyquist-Shannon sampling requirements. Then, observations can be made to …

Medical Signal Recognition System Based On Machine Learning, Deep Learning, And Internet Of Things, Arwa Hameed Mohammed Taqi

Theses and Dissertations

Internet of Things (IoT) technology is becoming increasingly common in the healthcare industry. The significant benefits of IoT are decreased operational costs, improved outcomes of the treatment through virtual infrastructures and accessibility of real-time information for making informed decisions, improved disease management, reduced errors, and enhanced patient experience. This enables hospitals to address the demands of the ever-growing population in this world. On the other hand, medical signal classification systems are systems that recognize normal from abnormal medical signals. These systems depend on two modes, training mode in which the system learns about the dominant features of the signals, and …

Comparison Of Hilbert Transform And Derivative Methods For Converting Ecg Data Into Cardioid Plots To Detect Heart Abnormalities, Robert George Goldie

Master's Theses

Electrocardiogram (ECG) time-domain signals contain important information about the heart. Several techniques have been proposed for creating a two-dimensional visualization of an ECG, called a Cardioid, that can be used to detect heart abnormalities with computer algorithms. The derivative method is the prevailing technique, which is popular for its low complexity, but it can introduce distortion into the Cardioid plot without additional signal processing. The Hilbert transform is an alternative method which has unity gain and phase shifts the ECG signal by 90 degrees to create the Cardioid plot. However, the Hilbert transform is seldom used and has historically been …

Synthetic Aperture Radar Image Recognition Of Armored Vehicles, Christopher Szul, Torrey J. Wagner, Brent T. Langhals

Faculty Publications

Synthetic Aperture Radar (SAR) imagery is not affected by weather and allows for day-and-night observations, however it can be difficult to interpret. This work applies classical and neural network machine learning techniques to perform image classification of SAR imagery. The Moving and Stationary Target Acquisition and Recognition dataset from the Air Force Research Laboratory was used, which contained 2,987 total observations of the BMP-2, BTR-70, and T-72 vehicles. Using a 75%/25% train/test split, the classical model achieved an average multi-class image recognition accuracy of 70%, while a convolutional neural network was able to achieve a 97% accuracy with lower model …

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 …

An Lpc Pole Processing Method For Enhancing The Identification Of Dominant Spectral Features, Jin Xu, Mark Davis, Ruairí De Fréin

Articles

This paper proposes a new time-resolved spectral analysis method based on a modification to the linear predictive coding (LPC) method for enhancing the identification of the dominant frequencies of a signal. The method described here is based on a z-plane analysis of the LPC poles. These poles are used to produce a series of reduced order filter transfer functions which can accurately identify and estimate the frequency of the dominant spectral features. The standard LPC method has been shown to suffer from a sensitivity to noise and its performance is dependent on the filter order. The proposed method can …

Framework For Collecting Data From Iot Device, Md Saiful Islam

Symposium of Student Scholars

The Internet of Things (IoT) is the most significant and blooming technology in the 21st century. IoT has rapidly developed by covering hundreds of applications in the civil, health, military, and agriculture areas. IoT is based on the collection of sensor data through an embedded system, and this embedded system uploads the data on the internet. Devices and sensor technologies connected over a network can monitor and measure data in real-time. The main challenge is to collect data from IoT devices, transmit them to store in the Cloud, and later retrieve them at any time for visualization and data analysis. …

Data Analysis Methods For Health Monitoring Sensors, Shahriar Sobhan

Symposium of Student Scholars

Innovations in health monitoring systems are fundamental for the continuous improvement of remote healthcare. With the current presence of SARS-CoV-2, better known as COVID-19, in people’s daily lives, solutions for monitoring heart and especially respiration and pulmonary functions are more needed than ever. Besides, health monitoring systems are widely used for patients who need isolated care, unconscious patients who cannot get medical attention for themselves. As it is well-known, monitoring systems rely on sensor technologies. Currently, there are multiple research studies for remote monitoring using different types of sensors. In this effort, we survey the current approaches that utilize the …

Multilayer Perceptron With Auto Encoder Enabled Deep Learning Model For Recommender Systems, Subhashini Narayan

Future Computing and Informatics Journal

In this modern world of ever-increasing one-click purchases, movie bookings, music, health- care, fashion, the need for recommendations have increased the more. Google, Netflix, Spotify, Amazon and other tech giants use recommendations to customize and tailor their search engines to suit the user’s interests. Many of the existing systems are based on older algorithms which although have decent accuracies, require large training and testing datasets and with the emergence of deep learning, the accuracy of algorithms has further improved, and error rates have reduced due to the use of multiple layers. The need for large datasets has declined as well. …

Deep Feature Learning For Fog Episodes Prediction In Patients With Pd, Hadeer Elziaat, Nashwa El-Bendary, Ramdan Mowad

Future Computing and Informatics Journal

A common symptom of Parkinson's Disease is Freezing of Gait (FoG) that causes an interrupt of the forward progression of the patient’s feet while walking. Therefore, Freezing of Gait episodes is always engaged to the patient's falls. This paper proposes a model for Freezing of Gait episodes detection and prediction in patients with Parkinson's Disease. Predicting Freezing of Gait in this paper considers as a multi-class classification problem with 3 classes namely, FoG, pre-FoG, and walking episodes. In this paper, the extracted feature scheme applied for the detection and the prediction of FoG is Convolutional Neural Network (CNN) spectrogram time-frequency …

Improving The Accuracy Of Measuring The Volume And Mass Of Liquid Product In Horizontal Cylindrical Tanks, Nodirbek Rustambekovich Yusupbekov, Azamat Alijonovich Yusupov, Bobir Alisher Ogli Boronov

Chemical Technology, Control and Management

The article is devoted to improving the accuracy of the system for measuring and controlling the level of liquid materials in horizontal cylindrical tanks. The task of ensuring continuous accurate control of the level, volume and mass of petroleum products, taking into account the shape of the bottom of the tank, is set. In order to improve the accuracy of the measuring device, a laser rangefinder is installed, which allows you to determine the distance from the tank lid to the point of the surface level of the liquid product and calculate the volume of the liquid material by determining …

Context-Aware Sensing And Fusion For Structural Health Monitoring And Night Time Traffic Surveillance, Xinxiang Zhang

Electrical Engineering Theses and Dissertations

Rapid developments in computer vision technologies have been transforming many traditional fields in engineering and science in the last few decades, especially in terms of diagnosing problems from visual images. Leveraging computer vision technologies to inspect, monitor, assess infrastructure conditions, and analyze traffic dynamics, has gained significant increase in both effectiveness and efficiency, compared to the cost of traditional instrumentation arrays to monitor, and manually inspect civil infrastructures and traffic conditions. Therefore, to construct the next-generation intelligent civil and transportation infrastructures, this dissertation develops a comprehensive computer-vision based sensing and fusion framework for structural health monitoring and intelligent transportation systems. …

Error Prevention In Sensors And Sensor Systems, Pedro J. Chacon Dominguez

LSU Doctoral Dissertations

Achievements in all fields of engineering and fabrication methods have led towards optimization and integration of multiple sensing devices into a concise system. These advances have caused significant innovation in various commercial, industrial, and research efforts. Integrations of subsystems have important applications for sensor systems in particular. The need for reporting and real time awareness of a device’s condition and surroundings have led to sensor systems being implemented in a wide variety of fields. From environmental sensors for agriculture, to object characterization and biomedical sensing, the application for sensor systems has impacted all modern facets of innovation. With these innovations, …

Data Forgery Detection In Automatic Generation Control: Exploration Of Automated Parameter Generation And Low-Rate Attacks, Yatish R. Dubasi

Computer Science and Computer Engineering Undergraduate Honors Theses

Automatic Generation Control (AGC) is a key control system utilized in electric power systems. AGC uses frequency and tie-line power flow measurements to determine the Area Control Error (ACE). ACE is then used by the AGC to adjust power generation and maintain an acceptable power system frequency. Attackers might inject false frequency and/or tie-line power flow measurements to mislead AGC into falsely adjusting power generation, which can harm power system operations. Various data forgery detection models are studied in this thesis. First, to make the use of predictive detection models easier for users, we propose a method for automated generation …

Optoelectronic Valley-Spin Qubits With Ambipolar Quantum Dots, Jeremy Tull

Electrical Engineering Undergraduate Honors Theses

The current limitations of qubit-based processors are caused by imperfections in quantum gates, leading to a lack of gate fidelity. Gate fidelity can be refined by extending the coherence of qubits and reducing logic operation speed. A potential solution is to develop a hybrid qubit that has the coherence of electrically-controlled quantum dots and the gate speed of their optically-controlled counterparts. Quantum bits that utilize ultrafast optical gating to perform gate operations require precise control of the gating pulse duration. Optical dispersion can cause adverse effects pulse duration, such as pulse broadening, so dispersion-compensation techniques must be employed; by properly …

The Linear And Non-Linear Relationships Between Peripheral Venous Pressure, Arterial Circulation, And Patient Factors, Lauren Crimmins

Biomedical Engineering Undergraduate Honors Theses

Peripheral venous pressure (PVP) can be used to measure blood volume status with a minimally invasive procedure. The pediatric cohort undergoing surgery for pyloric stenosis was studied to determine how arterial circulation and patient factors linearly impact PVP. The relationship between PVP and these confounding factors can provide valuable information for future PVP researchers.

To investigate the linear relationship between PVP and electrocardiogram (ECG) the waveforms were transformed into the frequency domain. A power spectral density was plotted, and the Pearson correlation coefficients were calculated for both preoperative and intraoperative settings. Linear regression models were computed for PVP and varying …

An 8-Bit Analog-To-Digital Converter For Battery Operated Wireless Sensor Nodes, Marvin Wayne Suggs Jr.

Graduate Theses and Dissertations

Wireless sensing networks (WSNs) collect analog information transduced into the form of a voltage or current. This data is typically converted into a digital representation of the value and transmitted wirelessly using various modulation techniques. As the available power and size is limited for wireless sensor nodes in many applications, a medium resolution Analog-to-Digital Converter (ADC) is proposed to convert a sensed voltage with moderate speeds to lower power consumption. Specifications also include a rail-to-rail input range and minimized errors associated with offset, gain, differential nonlinearity, and integral nonlinearity. To achieve these specifications, an 8-bit successive approximation register ADC is …