Electrical and Computer Engineering Commons^™

Patients Arms Segmentation And Gesture Identification Using Standalone 3d Lidar Sensors, Omar Rinchi, Nathanael Nisbett, Ahmad Alsharoa

Electrical and Computer Engineering Faculty Research & Creative Works

The intelligent and autonomous learning of patients' activities will lead to an incredible progression toward future smart e-health systems. With the recent advances in artificial intelligence, signal processing, and computational capabilities; light detection and ranging (LiDAR) technology can play a significant role in enhancing the current patients' activity recognition (PAR) systems. In this paper, we propose confidential and accurate patient arms behavior monitoring using a standalone three-dimensional (3D) LiDAR sensor. Due to the unavailability of LiDAR data, we use a computer-programmed 3D simulator to generate virtual-LiDAR (V-LiDAR) 3D point cloud data that simulates real patient movements. These virtual data are …

Chemical Classification By Monitoring Liquid Evaporation Using Extrinsic Fabry-Perot Interferometer With Microwave Photonics, Abhishek Prakash Hungund, Bohong Zhang, Anand Nambisan, Wassana Naku, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Identification of liquids is essential in chemical analysis, safety, environmental protection, quality control, and research. A novel liquid identification system based on Microwave Photonics (MWP) measured time transient evaporation signals is investigated. An extrinsic Fabry-Perot Interferometer (EFPI) based optical probe using single-mode fiber (SMF) is proposed to monitor evaporation of different liquids. The MWP system is used to measure the optical path changes during liquid evaporation due to its high sensitivity, selectivity, and Signal-to-Noise Ratio (SNR). The measured S21 continuous wave (CW) time Magnitude and Phase signals were processed to extract features such as histogram and Fast Fourier Transform (FFT) …

Cascaded Sapphire Fiber Bragg Gratings Inscribed By Femtosecond Laser For Molten Steel Studies, Dinesh Reddy Alla, Deva Prasad Neelakandan, Farhan Mumtaz, Rex E. Gerald, Laura Bartlett, Ronald J. O'Malley, Jeffrey D. Smith, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

This research reports a distributed fiber optic high-temperature sensing system tailored for applications in the steel industry and various other sectors. Recent advancements in optical sensor technology have led to the exploration of sapphire crystal fibers as a solution for sensing in harsh environments. Utilizing a femtosecond (fs) laser, cascaded fiber Bragg gratings (FBGs) were meticulously fabricated within a multimode sapphire optical fiber. These FBGs endowed the system with distributed sensing capabilities and underwent rigorous testing under extreme temperatures, reaching up to 1,800 °C. The study delves into the investigation of the FBG reflection spectrum, facilitated by the development of …

Coaxial Cable Sensing: Review And Perspective, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

The development of sensors has been a hot research topic in both scientific and industrial communities over the past decades. In recent years, a new sensing technology based on coaxial cables has emerged. Inspired by the fiber Bragg grating and motivated by the demand for structural health monitoring, coaxial cable Bragg gratings were first proposed and demonstrated with superior large strain capability ($>$ 5%). Mimicking the mature sensing modalities in fiber-optic sensors, coaxial cable sensors are developed to be promising alternatives for fiber-optic sensors in harsh-environment applications involving heavy duty, large strains, high pressures, and high temperatures. Over the …

Instantaneous Frequency Estimation Of Fm Signals Under Gaussian And Symmetric Alpha-Stable Noise: Deep Learning Versus Time-Frequency Analysis, Huda Saleem Razzaq, Zahir M. Hussain

Research outputs 2022 to 2026

Deep learning (DL) and machine learning (ML) are widely used in many fields but rarely used in the frequency estimation (FE) and slope estimation (SE) of signals. Frequency and slope estimation for frequency-modulated (FM) and single-tone sinusoidal signals are essential in various applications, such as wireless communications, sound navigation and ranging (SONAR), and radio detection and ranging (RADAR) measurements. This work proposed a novel frequency estimation technique for instantaneous linear FM (LFM) sinusoidal wave using deep learning. Deep neural networks (DNN) and convolutional neural networks (CNN) are classes of artificial neural networks (ANNs) used for the frequency and slope estimation …

Ultrasensitive Tapered Optical Fiber Refractive Index, Erem Ujah, Meimei Lai, Gymama Slaughter

Electrical & Computer Engineering Faculty Publications

Refractive index (RI) sensors are of great interest for label-free optical biosensing. A tapered optical fiber (TOF) RI sensor with micron-sized waist diameters can dramatically enhance sensor sensitivity by reducing the mode volume over a long distance. Here, a simple and fast method is used to fabricate highly sensitive refractive index sensors based on localized surface plasmon resonance (LSPR). Two TOFs (l = 5 mm) with waist diameters of 5 µm and 12 µm demonstrated sensitivity enhancement at λ = 1559 nm for glucose sensing (5-45 wt%) at room temperature. The optical power transmission decreased with increasing glucose concentration due …

Toward Real-Time, Robust Wearable Sensor Fall Detection Using Deep Learning Methods: A Feasibility Study, Haben Yhdego, Christopher Paolini, Michel Audette

Electrical & Computer Engineering Faculty Publications

Real-time fall detection using a wearable sensor remains a challenging problem due to high gait variability. Furthermore, finding the type of sensor to use and the optimal location of the sensors are also essential factors for real-time fall-detection systems. This work presents real-time fall-detection methods using deep learning models. Early detection of falls, followed by pneumatic protection, is one of the most effective means of ensuring the safety of the elderly. First, we developed and compared different data-segmentation techniques for sliding windows. Next, we implemented various techniques to balance the datasets because collecting fall datasets in the real-time setting has …

Transfer Learning Using Infrared And Optical Full Motion Video Data For Gender Classification, Alexander M. Glandon, Joe Zalameda, Khan M. Iftekharuddin, Gabor F. Fulop (Ed.), David Z. Ting (Ed.), Lucy L. Zheng (Ed.)

Electrical & Computer Engineering Faculty Publications

This work is a review and extension of our ongoing research in human recognition analysis using multimodality motion sensor data. We review our work on hand crafted feature engineering for motion capture skeleton (MoCap) data, from the Air Force Research Lab for human gender followed by depth scan based skeleton extraction using LIDAR data from the Army Night Vision Lab for person identification. We then build on these works to demonstrate a transfer learning sensor fusion approach for using the larger MoCap and smaller LIDAR data for gender classification.

A Survey Of Using Machine Learning In Iot Security And The Challenges Faced By Researchers, Khawlah M. Harahsheh, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The Internet of Things (IoT) has become more popular in the last 15 years as it has significantly improved and gained control in multiple fields. We are nowadays surrounded by billions of IoT devices that directly integrate with our lives, some of them are at the center of our homes, and others control sensitive data such as military fields, healthcare, and datacenters, among others. This popularity makes factories and companies compete to produce and develop many types of those devices without caring about how secure they are. On the other hand, IoT is considered a good insecure environment for cyber …

Development Of A Smartphone Application As An Asset To Pavement Management Engineers, Smartp3m, Damien Stephens

Electrical Engineering Theses

An application specific multi-platform smartphone application can utilize on-board accelerometer, gyroscope, and GPS sensors, along with software derived signals from the same sensors, to sample vibrational and geolocation datasets to capture pavement distresses such as potholes when mounted in a standardized configuration in a vehicle. Several observations were made with regard to the signals obtained from the accelerometer, gyroscope, and GPS sensors, and it was determined that the raw sensor outputs are capable of sampling statistically significant datasets which can be used to distinguish pavement distress from normal driving conditions. Furthermore, an approximate sensor noise margin is established, and a …

Falcon Neuro: An Event-Based Sensor On The International Space Station, Matthew G. Mcharg, Richard L. Balthazor, Matthew P. Borg, Brian J. Mcreynolds, David H. Howe, Colin J. Maloney, Daniel O'Keefe, Rayomand Bam, Gabriel Wilson, Paras Karki, Alexandre Marcireau, Gregory Cohen

Student Publications

We report on the Falcon neuro event-based sensor (EBS) instrument that is designed to acquire data from lightning and sprite phenomena and is currently operating on the International Space Station. The instrument consists of two independent, identical EBS cameras pointing in two fixed directions, toward the nominal forward direction of flight and toward the nominal Nadir direction. The payload employs stock DAVIS 240C focal plane arrays along with custom-built control and readout electronics to remotely interface with the cameras. To predict the sensor’s ability to effectively record sprites and lightning, we explore temporal response characteristics of the DAVIS 240C and …

Soft Electronics And Sensors For Wearable Healthcare Applications, Li-Wei Lo

McKelvey School of Engineering Graduate Student Theses & Dissertations

Wearable electronics are becoming increasingly essential to personalized medicine by collecting and analyzing massive amounts of biological signals from internal organs, muscles, and blood vessels. Conventional rigid electronics may lead to motion artifacts and errors in collected data due to the mismatches in mechanical properties between human skin. Instead, soft wearable electronics provide a better platform and interface that can form intimate contact and conformably adapt to human skin. In this respect, this thesis focuses on new materials formulation, fabrication, characterization of low-cost, high sensitivity and reliable sensors for wearable health monitoring applications.

More specifically, we have studied the silver …

Lifetime Maximization In Underwater Wireless Communication Networks, Kazi Yasin Islam, Iftekhar Ahmad, Daryoush Habibi, Jiong Jin, Muhammad Waqas

Research outputs 2022 to 2026

The rise in demand for underwater wireless communication networks (UWCN) has been driven by the emergence of new applications including unmanned underwater vehicles, deep-sea exploration, maritime and underwater archaeology research, and diver communications. For various applications, underwater network lifetime must be long, since unlike terrestrial sensor networks, it is a major job to change/recharge node batteries in underwater environments. In this paper, we introduce a solution where critical nodes in a UWCN are periodically recharged by small renewable energy sources. Further, a caching mechanism is introduced to relieve critical nodes of heavy workload when their residual energies run low. By …

Remote Healthcare Monitoring Using Wearable Iot Devices And Cloud Services, Mohammad Abdellatif, Menatalla Abdel-Gawad, Manar Usama, Haidy Hesham, Omar Ibrahim

Electrical Engineering

With the strain on healthcare infrastructure and healthcare workers due to the ongoing COVID'19 pandemic, the need for novel ways to simplify the interaction between patients and physicians has increased. The aim is mainly to reduce face-to-face interactions and free more time and resources for those who urgently need it. This paper presents a Telemedicine system which can be used as an alternative method to a doctor's visit. The proposed system is considered as an interface that remotely connects the patient and the doctor. The system regularly measures and uploads readings from the patient to a database which the doctor …

High-Resistance Connection Diagnosis In Five-Phase Pmsms Based On The Method Of Magnetic Field Pendulous Oscillation And Symmetrical Components, Hao Chen, Jiangbiao He, Xing Guan, Nabeel Demerdash, Ayman M. El-Refaie, Christopher H.T. Lee

Electrical and Computer Engineering Faculty Research and Publications

An online approach for diagnosing high-resistance connection (HRC) faults in five-phase permanent magnet synchronous motor drives is presented in this article. The development of this approach is based on a so-called “magnetic field pendulous oscillation (MFPO)” technique and symmetrical components method. Under HRC fault condition, a “swing-like” MFPO phenomenon is observed compared to the healthy condition. Furthermore, with the extracted current features in symmetrical components domain, different HRC fault types are successfully identified and distinguished. These fault types include single-phase faults, e.g., HRC fault in phase-A; two-phase nonadjacent faults, e.g., HRC fault in phase-A&C; and two-phase adjacent faults, e.g., HRC …

Surface Modified Hybrid Znsno3 Nanocubes For Enhanced Piezoelectric Power Generation And Wireless Sensory Application, Sk Md Ali Zaker Shawon, Zaida D. Carballo, Valeria Suarez Vega, Chen Lin, Muhammad Sufian Rafaqut, Andrew Xu Sun, James Li, Mohammed J. Uddin

School of Integrative Biological & Chemical Sciences (Formerly Dept. of Chemistry)

Piezoelectric Nanogenerators (PENGs), which can convert ambient mechanical stimuli into electrical energy, are held in high regard due to their cost-effectiveness, energy harvesting applications, and potential as self-powered sensors. We report an aluminum-doped zinc stannate (ZnSnO3) PENG that can achieve high electrical outputs with respect to the external force. In order to enrich the piezoelectric mechanics, a low-temperature solution method was adopted in our work to synthesize ZnSnO3 nanocubes with an average side length of only 30 – 55 nm. Furthermore, ZnSnO3 was doped with 1 wt% to 5 wt% of aluminum nanoparticles. We report that 2 wt% of aluminum …

Performance Of Xor Rule For Decentralized Detection Of Deterministic Signals In Bivariate Gaussian Noise, Xingjian Sun, Shailee Yagnik, Ramanarayanan Viswanathan, Lei Cao

Faculty and Student Publications

In this paper, we consider the performance of exclusive-OR (XOR) rule in detecting the presence or absence of a deterministic signal in bivariate Gaussian noise. Signals, when present at the two sensors, are assumed unequal, whereas the noise components have identical marginal distribution but are correlated. The sensors send their one-bit quantized data to a fusion center, which then employs the XOR rule to arrive at the final decision. Here we prove that, in the limit as the correlation coefficient r approaches 1, the optimum fusion rule for both parallel and tandem topologies is XOR with identical, alternating partitions (XORAP) …

Supervised Machine Learning Techniques Applied To Low-Cost Air Quality Sensor Suites, Peter Wahman

All Undergraduate Theses and Capstone Projects

Low-cost PM sensors have garnered interest for their ability to reduce the cost of investigating PM concentrations in both indoor and outdoor spaces. They perform well in high concentration lab testing with correlation coefficients greater than 0.9. In real-world applications, the correlation coefficients drop significantly because of sensing floors and adverse ambient conditions. There are plenty of supervised machine learning techniques that aim to correct the measurements ranging from linear regression to more advanced neural networks and random forests. This work aims to use those more complicated techniques to adjust the measurements using other data sets gathered by a sensor …

Formation Of Gold Nanoparticle Self-Assembling Films In Various Polymer Matrices For Sers Substrates, Ksenia A. Maleeva, Ilia E. Kaliya, Anton P. Tkach, Anton A. Babaev, Michail Baranov, Kevin Berwick, Tatiana S. Perova, Alexander V. Baranov, Kirill V. Bogdanov

Articles

Surface-enhanced Raman spectroscopy (SERS) is regarded as a versatile tool for studying the composition and structure of matter. This work has studied the preparation of a SERS substrate based on a self-assembling plasmonic nanoparticle film (SPF) in a polymer matrix. Several synthesis parameters for the SPF are investigated, including the size of the particles making up the film and the concentration and type of the self-assembling agent. The result of testing systems with different characteristics is discussed using a model substance (pseudo isocyaniniodide). These models can be useful in the study of biology and chemistry. Research results contain the optimal …

Detecting The Presence Of Electronic Devices In Smart Homes Using Harmonic Radar, Beatrice Perez, Gregory Mazzaro, Timothy J. Pierson, David Kotz

Dartmouth Scholarship

Data about users is collected constantly by phones, cameras, Internet websites, and others. The advent of so-called ‘Smart Things' now enable ever-more sensitive data to be collected inside that most private of spaces: the home. The first step in helping users regain control of their information (inside their home) is to alert them to the presence of potentially unwanted electronics. In this paper, we present a system that could help homeowners (or home dwellers) find electronic devices in their living space. Specifically, we demonstrate the use of harmonic radars (sometimes called nonlinear junction detectors), which have also been used in …

Self-Vernier Effect-Assisted Optical Fiber Sensor Based On Microwave Photonics And Its Machine Learning Analysis, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Optical Vernier Effect Has Been Recently Demonstrated as a Tool to Enhance the Sensitivity of Optical Fiber Interferometric Sensors and Has Become a Hot Topic in the Last Few Years. the Generation of the Vernier Effect Relies on the Superposition of Interferograms of Two Interferometers (A Sensing One and a Reference One) with Marginally Different Optical Path Differences (OPDs), Where an Amplitude Modulation-Like Signal is Sustained in the Output Spectrum. the Vernier Modulation Envelope Exhibits Significantly Magnified Sensitivity in Response to External Perturbations, compared to the Individual Sensing Interferometer, Providing a New Route to New Generations of Ultra-Sensitive Optical Fiber …

Distributed Fiber-Optic Temperature Sensors For Applications In The Steel Industry, Muhammad Roman

Doctoral Dissertations

"Steelmaking facilities require continuous temperature measurements throughout the manufacturing process to ensure consistent product quality and high productivity. Motivated by the limitations of conventional temperature sensors, distributed fiber-optic sensors (DFOS) were developed and deployed for various applications in the steel industry. Fiber-optic sensors offer various advantages over conventional sensors, such as the miniaturized size of the optical fiber, immunity to electromagnetic interferences, capability for multiplexing and distributed sensing, and the ability to withstand harsh environments.

Firstly, high-resolution Rayleigh backscattering based DFOS were demonstrated as potential solutions for temperature measurements in steelmaking processes by performing experimental simulations. Additionally, aluminum casting experiments …

Spectrum Sensing With Energy Detection In Multiple Alternating Time Slots, Călin Vlădeanu, Alexandru Marţian, Dimitrie C. Popescu

Electrical & Computer Engineering Faculty Publications

Energy detection (ED) represents a low complexity approach used by secondary users (SU) to sense spectrum occupancy by primary users (PU) in cognitive radio (CR) systems. In this paper, we present a new algorithm that senses the spectrum occupancy by performing ED in K consecutive sensing time slots starting from the current slot and continuing by alternating before and after the current slot. We consider a PU traffic model specified in terms of an average duty cycle value, and derive analytical expressions for the false alarm probability (FAP) and correct detection probability (CDP) for any value of K . Our …

Monitored Compression Therapy: Using Smart Technology To Optimize The Treatment Of Lower Extremity Swelling, James Skelly

UNLV Theses, Dissertations, Professional Papers, and Capstones

Chronic Venous Insufficiency (CVI) and Venous Stasis Ulcers (VSUs) are symptoms which stem from diabetes – a disease effecting over 34 million people in the United States alone as of 2020. This Thesis details the design of a pressure-sensing garment used to enhance the treatment of CVI. The garment uses small force sensors (four levels: the insole of the foot, the lower leg, the lower calf, and the upper calf) to sense the pressure applied by a compression stocking. The sensed data is transmitted wirelessly via Bluetooth to a smartphone application that was developed to display the data and interface …

Intelligent Sensors For Sustainable Food And Drink Manufacturing, Nicholas J. Watson, Alexander L. Bowler, Ahmed Rady, Oliver J. Fisher, Alessandro Simeone, Josep Escrig, Elliot Woolley, Akinbode A. Adedeji

Biosystems and Agricultural Engineering Faculty Publications

Food and drink is the largest manufacturing sector worldwide and has significant environmental impact in terms of resource use, emissions, and waste. However, food and drink manufacturers are restricted in addressing these issues due to the tight profit margins they operate within. The advances of two industrial digital technologies, sensors and machine learning, present manufacturers with affordable methods to collect and analyse manufacturing data and enable enhanced, evidence-based decision making. These technologies will enable manufacturers to reduce their environmental impact by making processes more flexible and efficient in terms of how they manage their resources. In this article, a methodology …

Advanced Organic Polymers For The Nanoscale Fabrication Of Fiber-Based Electronics Using The Electrospinning Technique, William Serrano Garcia

USF Tampa Graduate Theses and Dissertations

Electrospinning has become one of the most interesting techniques for fabricating nanofibers for multiple applications. The high surface-to-volume ratio nanofibers offer make the perfect structure for filters, sensors, and fiber-based electronics that could lead to a wide range of flexible electronics applications. This technique makes organic semiconducting polymers a promising alternative for single fiber electronics structures. Indeed, a wide variety of structures can be fabricated using electrostatic techniques for polymer manipulation from droplets, fibers, and coaxial structures. Although techniques such as electrospinning led the use of electrostatic forces to generate fibers of a precursor solution, electrospinning requires large enough polymer …

Design Of Smart Trashcan, Haoran Song

Senior Theses

A smart trashcan has been designed which can bring convenience to people for throwing their garbage away during the COVID-19 pandemic. A prototype is made from cardboard to demonstrate its function. This trashcan can sense people who are coming and leaving, and it can open and close automatically. The trashcan is powered by solar energy. A solar panel is mounted on top of the trashcan supporter. This design is specifically for use in China.

Ultrafast Thermal Modification Of Strong Coupling In An Organic Microcavity, Bin Liu, Vinod M. Menon, Matthew Y. Sfeir

Advanced Science Research Center

There is growing interest in using strongly coupled organic microcavities to tune molecular dynamics, including the electronic and vibrational properties of molecules. However, very little attention has been paid to the utility of cavity polaritons as sensors for out-of-equilibrium phenomena, including thermal excitations. Here, we demonstrate that non-resonant infrared excitation of an organic microcavity system induces a transient response in the visible spectral range near the cavity polariton resonances. We show how these optical responses can be understood in terms of ultrafast heating of electrons in the metal cavity mirror, which modifies the effective refractive index and subsequently the strong …

Deep Learning Versus Spectral Techniques For Frequency Estimation Of Single Tones: Reduced Complexity For Software-Defined Radio And Iot Sensor Communications, Hind R. Almayyali, Zahir M. Hussain

Research outputs 2014 to 2021

Despite the increasing role of machine learning in various fields, very few works considered artificial intelligence for frequency estimation (FE). This work presents comprehensive analysis of a deep-learning (DL) approach for frequency estimation of single tones. A DL network with two layers having a few nodes can estimate frequency more accurately than well-known classical techniques can. While filling the gap in the existing literature, the study is comprehensive, analyzing errors under different signal-to-noise ratios (SNRs), numbers of nodes, and numbers of input samples under missing SNR information. DL-based FE is not significantly affected by SNR bias or number of nodes. …

Ultrafast Thermal Modification Of Strong Coupling In An Organic Microcavity, Bin Liu, Vinod M. Menon, Matthew Y. Sfeir

Publications and Research

There is growing interest in using strongly coupled organic microcavities to tune molecular dynamics, including the electronic and vibrational properties of molecules. However, very little attention has been paid to the utility of cavity polaritons as sensors for out-of-equilibrium phenomena, including thermal excitations. Here, we demonstrate that non-resonant infrared excitation of an organic microcavity system induces a transient response in the visible spectral range near the cavity polariton resonances. We show how these optical responses can be understood in terms of ultrafast heating of electrons in the metal cavity mirror, which modifies the effective refractive index and subsequently the strong …