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Articles 121 - 150 of 441
Full-Text Articles in Electrical and Electronics
Guest Editorial: Edge Intelligence For Beyond 5g Networks, Yan Zhang, Zhiyong Feng, Hassnaa Moustafa, Feng Ye, Usman Javaid, Chunfen Cui
Guest Editorial: Edge Intelligence For Beyond 5g Networks, Yan Zhang, Zhiyong Feng, Hassnaa Moustafa, Feng Ye, Usman Javaid, Chunfen Cui
Electrical and Computer Engineering Faculty Publications
Beyond fifth-generation (B5G) networks, or so-called "6G", is the next-generation wireless communications systems that will radically change how Society evolves. Edge intelligence is emerging as a new concept and has extremely high potential in addressing the new challenges in B5G networks by providing mobile edge computing and edge caching capabilities together with Artificial Intelligence (AI) to the proximity of end users. In edge intelligence empowered B5G networks, edge resources are managed by AI systems for offering powerful computational processing and massive data acquisition locally at edge networks. AI helps to obtain efficient resource scheduling strategies in a complex environment with …
Channel Estimation In Multi-User Massive Mimo Systems By Expectation Propagation Based Algorithms, Mohammed Rashid
Channel Estimation In Multi-User Massive Mimo Systems By Expectation Propagation Based Algorithms, Mohammed Rashid
LSU Doctoral Dissertations
Massive multiple input multiple output (MIMO) technology uses large antenna arrays with tens or hundreds of antennas at the base station (BS) to achieve high spectral efficiency, high diversity, and high capacity. These benefits, however, rely on obtaining accurate channel state information (CSI) at the receiver for both uplink and downlink channels. Traditionally, pilot sequences are transmitted and used at the receiver to estimate the CSI. Since the length of the pilot sequences scale with the number of transmit antennas, for massive MIMO systems downlink channel estimation requires long pilot sequences resulting in reduced spectral efficiency and the so-called pilot …
Color-Compressive Bilateral Filter And Nonlocal Means For High-Dimensional Images, Christina Karam, Kenjiro Sugimoto, Keigo Hirakawa
Color-Compressive Bilateral Filter And Nonlocal Means For High-Dimensional Images, Christina Karam, Kenjiro Sugimoto, Keigo Hirakawa
Electrical and Computer Engineering Faculty Publications
We propose accelerated implementations of bilateral filter (BF) and nonlocal means (NLM) called color-compressive bilateral filter (CCBF) and color-compressive nonlocal means (CCNLM). CCBF and CCNLM are random filters, whose Monte-Carlo averaged output images are identical to the output images of conventional BF and NLM, respectively. However, CCBF and CCNLM are considerably faster because the spatial processing of multiple color channels are combined into a single random filtering process. This implies that the complexity of CCBF and CCNLM is less sensitive to color dimension (e.g., hyperspectral images) relatively to other BF and NLM methods. We experimentally verified that the execution time …
Deep Learning For Anisoplanatic Optical Turbulence Mitigation In Long-Range Imaging, Matthew A. Hoffmire, Russell C. Hardie, Michael A. Rucci, Richard Van Hook, Barry K. Karch
Deep Learning For Anisoplanatic Optical Turbulence Mitigation In Long-Range Imaging, Matthew A. Hoffmire, Russell C. Hardie, Michael A. Rucci, Richard Van Hook, Barry K. Karch
Electrical and Computer Engineering Faculty Publications
We present a deep learning approach for restoring images degraded by atmospheric optical turbulence. We consider the case of terrestrial imaging over long ranges with a wide field-of-view. This produces an anisoplanatic imaging scenario where turbulence warping and blurring vary spatially across the image. The proposed turbulence mitigation (TM) method assumes that a sequence of short-exposure images is acquired. A block matching (BM) registration algorithm is applied to the observed frames for dewarping, and the resulting images are averaged. A convolutional neural network (CNN) is then employed to perform spatially adaptive restoration. We refer to the proposed TM algorithm as …
Dales Objects: A Large Scale Benchmark Dataset For Instance Segmentation In Aerial Lidar, Nina M. Singer, Vijayan K. Asari
Dales Objects: A Large Scale Benchmark Dataset For Instance Segmentation In Aerial Lidar, Nina M. Singer, Vijayan K. Asari
Electrical and Computer Engineering Faculty Publications
We present DALES Objects, a large-scale instance segmentation benchmark dataset for aerial lidar. DALES Objects contains close to half a billion hand-labeled points, including semantic and instance segmentation labels. DALES Objects is an extension of the DALES (Varney et al., 2020) dataset, adding additional intensity and instance segmentation annotation. This paper provides an overview of the data collection, preprocessing, hand-labeling strategy, and final data format. We propose relevant evaluation metrics and provide insights into potential challenges when evaluating this benchmark dataset. Finally, we provide information about how researchers can access the dataset for their use at go.udayton.edu/dales3d.
Coordinated Control For Dc Energy Hubs Involving Ders, Evs, And Subway Systems, Rohama Ahmad
Coordinated Control For Dc Energy Hubs Involving Ders, Evs, And Subway Systems, Rohama Ahmad
Dissertations and Theses
No abstract provided.
A General Framework For Characterizing And Evaluating Attacker Models For Cps Security Assessment, Christopher S. Deloglos, Christopher Deloglos
A General Framework For Characterizing And Evaluating Attacker Models For Cps Security Assessment, Christopher S. Deloglos, Christopher Deloglos
Theses and Dissertations
Characterizing the attacker’s perspective is essential to assessing the security posture and resilience of cyber-physical systems. The attacker’s perspective is most often achieved by cyber-security experts (e.g., red teams) who critically challenge and analyze the system from an adversarial stance. Unfortunately, the knowledge and experience of cyber-security experts can be inconsistent leading to situations where there are gaps in the security assessment of a given system. Structured security review processes (such as TAM, Mission Aware, STPA-SEC, and STPA-SafeSec) attempt to standardize the review processes to impart consistency across an organization or application domain. However, with most security review processes, the …
Ieee Access Special Section Editorial: Trends And Advances In Bio-Inspired Image-Based Deep Learning Methodologies And Applications, Peter Peer, Carlos M. Travieso-Gonzalez, Vijayan K. Asari, Malay Kishore Dutta
Ieee Access Special Section Editorial: Trends And Advances In Bio-Inspired Image-Based Deep Learning Methodologies And Applications, Peter Peer, Carlos M. Travieso-Gonzalez, Vijayan K. Asari, Malay Kishore Dutta
Electrical and Computer Engineering Faculty Publications
Many of the technological advances we enjoy today have been inspired by biological systems due to their ease of operation and outstanding efficiency. Designing technological solutions based on biological inspiration has become a cornerstone of research in a variety of areas ranging from control theory and optimization to computer vision, machine learning, and artificial intelligence. Especially in the latter few areas, biologically relevant solutions are becoming increasingly important as we look for new ways to make artificial systems more efficient, intelligent, and overall effective.
Integration Of Robotic And Electro-Pneumatic Systems Using Advanced Control And Communication Schemes, Chinmay Kondekar
Integration Of Robotic And Electro-Pneumatic Systems Using Advanced Control And Communication Schemes, Chinmay Kondekar
Dissertations, Master's Theses and Master's Reports
Modern industrial automation systems are designed by interconnecting various subsystems which work together to perform a process. The thesis project aims to integrate fragmented subsystems into a flexible and reconfigurable system through advanced communication protocols and perform a process to demonstrate the effectiveness of interconnected systems.
The system consists of three six-axis robots, one electro-pneumatic robot, and two conveyors connected using EthernetIP communication and hardwired connections. The interconnected system works together to perform machining of a workpiece using advanced control methods of CAD to robot path generation, central control through a PLC, and process control through HMI.
Standardized programming blocks …
A Two-Level Information Modelling Translation Methodology And Framework To Achieve Semantic Interoperability In Constrained Geoobservational Sensor Systems, Paul Stacey
Doctoral
As geographical observational data capture, storage and sharing technologies such as in situ remote monitoring systems and spatial data infrastructures evolve, the vision of a Digital Earth, first articulated by Al Gore in 1998 is getting ever closer. However, there are still many challenges and open research questions. For example, data quality, provenance and heterogeneity remain an issue due to the complexity of geo-spatial data and information representation.
Observational data are often inadequately semantically enriched by geo-observational information systems or spatial data infrastructures and so they often do not fully capture the true meaning of the associated datasets. Furthermore, data …
Hard Hat Ambient Liability Observer (Halo), Hunter Hykes, Nathan Kish, Brian Thomson
Hard Hat Ambient Liability Observer (Halo), Hunter Hykes, Nathan Kish, Brian Thomson
Williams Honors College, Honors Research Projects
Capturing workplace incident information is a growing area of concern for most companies. To assist with this, the design team proposed the H.A.L.O. This design uses time-of-flight sensors connected to LEDs to create a proximity-based hazard warning system. It also records incident data using an accelerometer and micro-SD card. This helps workers avoid some of the most common workplace injuries, slips, trips, and falls and accidental collisions.
Students have created a design with engineering, and marketing requirements that accomplish this task. The proposed design allows for this monitoring and mitigation systems to be attached to hard hats. Team members developed …
Design Project: Smart Headband, John Michel, Jack Durkin, Noah Lewis
Design Project: Smart Headband, John Michel, Jack Durkin, Noah Lewis
Williams Honors College, Honors Research Projects
Concussion in sports is a prevalent medical issue. It can be difficult for medical professionals to diagnose concussions. With the fast pace nature of many sports, and the damaging effects of concussions, it is important that any concussion risks are assessed immediately. There is a growing trend of wearable technology that collects data such as steps and provides the wearer with in-depth information regarding their performance. The Smart Headband project created a wearable that can record impact data and provide the wearer with a detailed analysis on their risk of sustaining a concussion. The Smart Headband uses accelerometers and gyroscopes …
Automated Blind Control, Daniel Nahra, Matthew Lacek, Timothy Kurczewski, William Daulton Baksa
Automated Blind Control, Daniel Nahra, Matthew Lacek, Timothy Kurczewski, William Daulton Baksa
Williams Honors College, Honors Research Projects
The objective of this project would be to design and prototype an automated, light and temperature sensing window blinds system. The device would detect temperature, both inside and outside, and incoming sunlight to determine proper window blind position for maximum energy savings. The user would also have the ability to change the settings of the blind from a remote device to a setting that they desire at any given time
Deep Models For Improving The Performance And Reliability Of Person Recognition, Sobhan Soleymani
Deep Models For Improving The Performance And Reliability Of Person Recognition, Sobhan Soleymani
Graduate Theses, Dissertations, and Problem Reports (ETD)
Deep models have provided high accuracy for different applications such as person recognition, image segmentation, image captioning, scene description, and action recognition. In this dissertation, we study the deep learning models and their application in improving the performance and reliability of person recognition. This dissertation focuses on five aspects of person recognition: (1) multimodal person recognition, (2) quality-aware multi-sample person recognition, (3) text-independent speaker verification, (4) adversarial iris examples, and (5) morphed face images. First, we discuss the application of multimodal networks consisting of face, iris, fingerprint, and speech modalities in person recognition. We propose multi-stream convolutional neural network architectures …
Re-Design Of Precision Signal Conditioning Circuit For Detecting Schumann Resonance, Rohith Bikkina
Re-Design Of Precision Signal Conditioning Circuit For Detecting Schumann Resonance, Rohith Bikkina
Graduate Theses, Dissertations, and Problem Reports (ETD)
Extremely low frequencies signals are waves between 3 to 30Hz and corresponding wavelengths between 10,000 to 100,000 kilometers. The specific signals used here are generated from lightning and are excited at frequencies around 8Hz, 14Hz, 20Hz. These are often called Schumann Resonance frequencies. Several stations have been built around the world for identifying ELF waves. All of those required a sparsely populated area that was far away from electric power lines because of interference from electric noise at 50 Hz and 60Hz. This project develops and tests an amplifier and filter circuit that should assist in identifying the Schumann Resonance …
Analysis Of Millimeter-Wave Networks: Blockage, Antenna Directivity, Macrodiversity, And Interference, Enass Hriba
Analysis Of Millimeter-Wave Networks: Blockage, Antenna Directivity, Macrodiversity, And Interference, Enass Hriba
Graduate Theses, Dissertations, and Problem Reports (ETD)
Due to its potential to support high data rates at low latency with reasonable interference isolation because of signal blockage at these frequencies, millimeter-wave (mmWave) communications has emerged as a promising solution for next-generation wireless networks. MmWave systems are characterized by the use of highly directional antennas and susceptibility to signal blockage by buildings and other obstructions, which significantly alter the propagation environment. The received power of each transmission depends on the direction the corresponding antennas point and whether the signal’s path is line-of-sight (LOS), non-LOS (i.e., partially blocked), or completely blocked. A key challenge in modeling blocking in mmWave …
Comparative Analysis Of Multiplicative And Additive Noise Based Automated Regularizations In Non-Linear Diffusion Image Reconstruction, Chiza Christophe
Comparative Analysis Of Multiplicative And Additive Noise Based Automated Regularizations In Non-Linear Diffusion Image Reconstruction, Chiza Christophe
Tanzania Journal of Engineering and Technology (TJET)
Multiplicative and additive noises are often introduced in image signals during the image acquisition process and result into degradation of image features. The work done by Perona and Malik in 1990 and its modified versions revolutionized the way through which noises or speckles are removed. The Perona-Malik model requires tuning of the regularization parameter to control and prevent staircase artifacts in restored images. The current manual tuning is a challenging and time consuming practice when a long queue of images is registered for processing. Attempt to automate the regularization parameter appeared in Perona-Malik model with self-adjusting shape-defining constant. Although both …
Mimo Antenna For Fifth Generation Mm-Wave Applications: A Bibliometric Survey, Rajeshwari R. Malekar, Laxmikant K. Shevada, Hema D. Raut, Amruta S. Dixit, Sumit Kumar
Mimo Antenna For Fifth Generation Mm-Wave Applications: A Bibliometric Survey, Rajeshwari R. Malekar, Laxmikant K. Shevada, Hema D. Raut, Amruta S. Dixit, Sumit Kumar
Library Philosophy and Practice (e-journal)
Nowadays most discussed technology is mm-wave and 5G communication. The requirement of 5G technology is high bandwidth, high data rate, and low latency. To fulfil these requirements for the current growth in mobile communication multiple input multiple output antenna is used. This bibliometric paper throws light on the various methods used to improve mutual coupling between multiple antennas. Various mutual coupling reduction techniques that are used in MIMO antennas like Dielectric resonator antenna, Electromagnetic Bandgap Structure, Neutralization lines, Defected Ground Structures, Metamaterial, etc. are explained. Scopus database is used for this bibliometric review on mm-wave MIMO 5G technology from the …
Multibeam Array Antenna For Base Station In The Fifth-Generation Mobile Communication System, Intan Izafina Idrus
Multibeam Array Antenna For Base Station In The Fifth-Generation Mobile Communication System, Intan Izafina Idrus
Student Works (2020-2029)
Research on the fifth-generation (5G) mobile communication system has been accelerated to meet the standardization of the International Telecommunications Union for higher data traffic and higher data rates. The main requirements of the 5G mobile communication systems are the utilization of millimeter waves, the deployment of small cells, and the use of multibeam array antennas for multiple-input multiple-output schemes. Multibeam array antennas play an important role in developing a new base station to enhance system capacity, improve network coverage, and reduce co-channel interference. The main objective of this thesis is to design a single-layer multibeam array antenna at 28 GHz …
Conditional Generative Adversarial Network Demosaicing Strategy For Division Of Focal Plane Polarimeters, Garrett Sargent, Bradley M. Ratliff, Vijayan K. Asari
Conditional Generative Adversarial Network Demosaicing Strategy For Division Of Focal Plane Polarimeters, Garrett Sargent, Bradley M. Ratliff, Vijayan K. Asari
Electrical and Computer Engineering Faculty Publications
Division of focal plane (DoFP), or integrated microgrid polarimeters, typically consist of a 2 × 2 mosaic of linear polarization filters overlaid upon a focal plane array sensor and obtain temporally synchronized polarized intensity measurements across a scene, similar in concept to a Bayer color filter array camera. However, the resulting estimated polarimetric images suffer a loss in resolution and can be plagued by aliasing due to the spatially-modulated microgrid measurement strategy. Demosaicing strategies have been proposed that attempt to minimize these effects, but result in some level of residual artifacts. In this work we propose a conditional generative adversarial …
Transfer-To-Transfer Learning Approach For Computer Aided Detection Of Covid-19 In Chest Radiographs, Barath Narayanan Narayanan, Russell C. Hardie, Vignesh Krishnaraja, Christina Karam, Venkata Salini Priyamvada Davuluru
Transfer-To-Transfer Learning Approach For Computer Aided Detection Of Covid-19 In Chest Radiographs, Barath Narayanan Narayanan, Russell C. Hardie, Vignesh Krishnaraja, Christina Karam, Venkata Salini Priyamvada Davuluru
Electrical and Computer Engineering Faculty Publications
The coronavirus disease 2019 (COVID-19) global pandemic has severely impacted lives across the globe. Respiratory disorders in COVID-19 patients are caused by lung opacities similar to viral pneumonia. A Computer-Aided Detection (CAD) system for the detection of COVID-19 using chest radiographs would provide a second opinion for radiologists. For this research, we utilize publicly available datasets that have been marked by radiologists into two-classes (COVID-19 and non-COVID-19). We address the class imbalance problem associated with the training dataset by proposing a novel transfer-to-transfer learning approach, where we break a highly imbalanced training dataset into a group of balanced mini-sets and …
Iot Camera System For Monitoring Strawberry Fields, Simon Schoennauer
Iot Camera System For Monitoring Strawberry Fields, Simon Schoennauer
Master's Theses
A wireless imaging system for monitoring strawberry fields provides enough quality image data for computer vision algorithms to make meaningful yield predictions. This report contains a design for a wireless sensor network modified with mesh networking techniques to extend coverage range and a solar energy harvesting system to improve sensor node lifetime. A two hop system with six nodes is implemented in a laboratory environment validating the communication systems integrity over an 800’ range. Moving from a primary battery system to solar energy harvesting increases the module lifetime indefinitely.
Simulation Of An Sp8t 18 Ghz Rf Switch Using Smt Pin Diodes, Andre De Souza Vigano
Simulation Of An Sp8t 18 Ghz Rf Switch Using Smt Pin Diodes, Andre De Souza Vigano
Master's Theses
Radio frequency (RF) and microwave switches are widely used in several different applications including radar, measurement systems, telecommunications, and other areas. An RF switch can control a radar’s transmit vs. receive mode, select the operating band, or direct an RF signal to different paths. In this study, a single pole eight throw (SP8T) switch using only Surface Mount (SMT) components is designed and simulated in Keysight’s Advanced Design System (ADS). Single pole eight throw is defined as one input and eight possible outputs. A star network configuration with series-shunt PIN diode switches is used to create the 8-way RF switch. …
Predicting Quality Of Delivery Metrics For Adaptive Video Codec Sessions, Obinna Izima, Ruairí De Fréin, Mark Davis
Predicting Quality Of Delivery Metrics For Adaptive Video Codec Sessions, Obinna Izima, Ruairí De Fréin, Mark Davis
Conference papers
Predicting video quality will continue to be an active area of research given the dominance of video traffic for years to come. Network service practitioners that are poised to handle the strain on the existing limited bandwidth constraints are better placed to be SLA-compliant. The dynamic and time-varying nature of cloud-hosted services require improved techniques to realize accurate models of the systems. To address this challenge: (1) we propose Codec-aware Network Adaptation Agent (cNAA), an online light-weight data learning engine that achieves accurate and correct predictions of quality of delivery (QoD) metrics, namely jitter for video services. cNAA achieves this …
Iot Asset Tracker, Jonny M. Erickson, Matt A. Murray
Iot Asset Tracker, Jonny M. Erickson, Matt A. Murray
Electrical Engineering
This senior project will be the completion of an IoT asset Tracker. In today’s day and age, technology is weaving its way into every aspect of life. Because of this, we demand to know more and more information about everything that is going on in our lives. One of these needed pieces of information is knowing the location of our most valuable assets. This is the main goal of this project: to build a portable SMS driven GNSS tracking device. The device is designed to provide two methods of tracking for any mobile asset. The device will utilize a large …
Cooperative Spectrum Sensing Using Maximum A Posteriori As A Detection Technique For Dynamic Spectrum Access Networks, Mohammad Abdellatif, Ahmed Tohamy, Usama Sayed Mohamed, Taha A. Khalaf, Mohamed Abdelraheem
Cooperative Spectrum Sensing Using Maximum A Posteriori As A Detection Technique For Dynamic Spectrum Access Networks, Mohammad Abdellatif, Ahmed Tohamy, Usama Sayed Mohamed, Taha A. Khalaf, Mohamed Abdelraheem
Electrical Engineering
Over the past few years, dynamic spectrum access has been gaining an increasing attention as a solution to the spectrum scarcity problem. In this paper, a primary user detection technique based on Maximum A Posteriori estimation is proposed for dynamic spectrum access networks. In the proposed technique, a set of secondary users acting as sensing nodes send their individual decisions about the existence of the primary user to a central fusion center. The fusion center uses the received data to form a codeword then, applies the maximum a posteriori estimation rule to make a final decision regarding the presence of …
Model-Based And Data-Driven Situational Awareness For Distribution System Monitoring And Control, Ying Zhang
Model-Based And Data-Driven Situational Awareness For Distribution System Monitoring And Control, Ying Zhang
Electrical Engineering Theses and Dissertations
Electric power systems are undergoing a dramatic change. The penetration of distributed energy resources (DERs) such as wind turbine generators and photovoltaic panels is turning a traditional power system into the active distribution network. Power system situational awareness, which provides critical information for system monitoring and control, is being challenged by multiple sources of uncertainties such as random meter errors, stochastic power output of DERs, and imprecise network parameters. On the other hand, cyber-physical power system operation is vulnerable to cyberattacks against effective state estimation, such as false data injection attacks (FDIAs). To construct next-generation smart grids, this dissertation develops …
Development Of A Reference Design For A Cyber-Physical System, Nicholas Paul Blair
Development Of A Reference Design For A Cyber-Physical System, Nicholas Paul Blair
Graduate Theses and Dissertations
The purpose of this thesis is to develop a reference design to assist in the selection of security practices in power electronics design. A prototype will be developed from this reference design for evaluation. This evaluation will include a brief cost/benefit analysis to gauge the efficacy of implementing each layer of security throughout the power electronics design process. This thesis will also describe the obstacles and effectiveness of integrating a Trusted Platform Module (TPM) into a cyber-hardened grid-connected device. The TPM device is a secured crypto processor that assists in generating, storing, and restricting the use of cryptographic keys. The …
Telemedicine: An Iot Based Remote Healthcare System., Mohammad Abdellatif, Walaa Mohamed
Telemedicine: An Iot Based Remote Healthcare System., Mohammad Abdellatif, Walaa Mohamed
Electrical Engineering
This paper proposes a remote healthcare system which is referred to as Telemedicine. Telemedicine is a platform that establishes a connection be-tween the patient and the doctor. This platform belongs to the internet of medical things (IoMT) by enabling multiple medical sensors to connect to a server either using multiple communication technologies such as Wi-Fi, Bluetooth or GSM technologies. The system collects data from several sensors and sends them using one of the aforementioned technologies using an Arduino Board, while the inter-face is made with matlab and C#. Additionally, a comparative study between the three communications technologies used to connect …
Distance Estimation Using Ofdm Signals For Ultrasonic Positioning, Kyman Huang
Distance Estimation Using Ofdm Signals For Ultrasonic Positioning, Kyman Huang
Master's Theses
This paper describes a method of estimating distance via Time-of-Flight (TOF) measurement using ultrasonic Orthogonal Frequency Division Multiplexing (OFDM) signals. Using OFDM signals allows the signals and their sub-carriers to remain orthogonal to each other while continuously transmitting. This estimation method is based on the change of phase of a traveling wave as it propagates through a medium (air for ultrasonic signals). By using signals containing multiple tones, the phase change between each frequency component is slightly different. This phase difference is dependent on the distance traveled and can thus be used to estimate distance. This paper studies the impact …