Electrical and Electronics Commons^™

Weight Controlled Electric Skateboard, Zachary Barram, Carson Bertozzi, Vishnu Dodballapur

Computer Engineering

Technology and the way that humans interact is becoming more vital and omnipresent with every passing day. However, human interface device designers suffer from the increasingly popular “designed for me or people like me” syndrome. This design philosophy inherently limits accessibility and usability of technology to those like the designer. This places severe limits of usability to those who are not fully able as well as leaves non-traditional human interface devices unexplored. This project set out to explore a previously uncharted human interface device, on an electric skateboard, and compare it send user experience with industry leading human interface devices.

Analog Single Sideband-Pulse Width Modulation Processor For Parametric Acoustic Arrays, Vikrant A. Marathe

Master's Theses

Parametric acoustic arrays are ultrasonic-based loudspeakers that produce highly directive audio. The audio must first be preprocessed and modulated into an ultrasonic carrier before being emitted into the air, where it will self-demodulate in the far field. The resulting audio wave is proportional to the double time-derivative of the square of the modulation envelope. This thesis presents a fully analog processor which encodes the audio into two Pulse Width Modulated (PWM) signals in quadrature phase and sums them together to produce a Single Sideband (SSB) spectrum around the fundamental frequency of the PWM signals. The two signals are modulated between …

A State-Of-The-Art Survey On Deep Learning Theory And Architectures, Md Zahangir Alom, Tarek M. Taha, Christopher Yakopcic, Stefan Westberg, Paheding Sidike, Mst Shamima Nasrin, Mahmudul Hasan, Brian C. Van Essen, Abdul A. S. Awwal, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

In recent years, deep learning has garnered tremendous success in a variety of application domains. This new field of machine learning has been growing rapidly and has been applied to most traditional application domains, as well as some new areas that present more opportunities. Different methods have been proposed based on different categories of learning, including supervised, semi-supervised, and un-supervised learning. Experimental results show state-of-the-art performance using deep learning when compared to traditional machine learning approaches in the fields of image processing, computer vision, speech recognition, machine translation, art, medical imaging, medical information processing, robotics and control, bioinformatics, natural language …

Development Of A Myoelectric Detection Circuit Platform For Computer Interface Applications, Nickolas Andrew Butler

Master's Theses

Personal computers and portable electronics continue to rapidly advance and integrate into our lives as tools that facilitate efficient communication and interaction with the outside world. Now with a multitude of different devices available, personal computers are accessible to a wider audience than ever before. To continue to expand and reach new users, novel user interface technologies have been developed, such as touch input and gyroscopic motion, in which enhanced control fidelity can be achieved. For users with limited-to-no use of their hands, or for those who seek additional means to intuitively use and command a computer, novel sensory systems …

Fall Detection Using Channel State Information From Wifi Devices, D.M Sameera Palipana

PhDs

Falls among the independently living elderly population are a major public health worry, leading to injuries, loss of confidence to live independently and even to death. Each year, one in three people aged 65 and older falls and one in five of them suffers fatal or non fatal injuries. Therefore, detecting a fall early and alerting caregivers can potentially save lives and increase the standard of living. Existing solutions, e.g. push-button, wearables, cameras, radar, pressure and vibration sensors, have limited public adoption either due to the requirement for wearing the device at all times or installing specialized and expensive infrastructure. …

Submerged Solar Energy Harvesters Performance For Underwater Applications, Mohammad Abdellatif, Salsabeel Kamal, Ghazal M. Al-Sayyad, Rana Abdelmoteleb, Sameh O. Abdellatif

Electrical Engineering

underwater communications is the transmission of data in an unguided water medium through wireless carriers such as; optical waves, radio-frequency waves and acoustic waves. Such type of communication system is utilized to enable the realization of the ocean exploration system and other marine monitoring/exploration systems. Seeking for a sustainable setup, the enrolment of energy harvesting sources in these wireless nodes have been presented as a replacement of the short-life-time battery sources. In this paper, there are experimental measurements as well as theoretical studies for two different light harvesters have been conducted underwater with considering the air measurements as a reference. …

Active Recall Networks For Multiperspectivity Learning Through Shared Latent Space Optimization, Theus Aspiras, Ruixu Liu, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Given that there are numerous amounts of unlabeled data available for usage in training neural networks, it is desirable to implement a neural network architecture and training paradigm to maximize the ability of the latent space representation. Through multiple perspectives of the latent space using adversarial learning and autoencoding, data requirements can be reduced, which improves learning ability across domains. The entire goal of the proposed work is not to train exhaustively, but to train with multiperspectivity. We propose a new neural network architecture called Active Recall Network (ARN) for learning with less labels by optimizing the latent space. This …

Deep Temporal Convolutional Networks For Short-Term Traffic Flow Forecasting, Wentian Zhao, Yanyun Gao, Tingxiang Ji, Xili Wan, Feng Ye, Guangwei Bai

Electrical and Computer Engineering Faculty Publications

To reduce the increasingly congestion in cities, it is essential for intelligent transportation system (ITS) to accurately forecast the short-term traffic flow to identify the potential congestion sites. In recent years, the emerging deep learning method has been introduced to design traffic flow predictors, such as recurrent neural network (RNN) and long short-term memory (LSTM), which has demonstrated its promising results. In this paper, different from existing work, we study the temporal convolutional network (TCN) and propose a deep learning framework based on TCN model for short-term city-wide traffic forecast to accurately capture the temporal and spatial evolution of traffic …

Dual Graphene Patch Antenna For Ka Band Satellite Applications, Mohammed Amin Rabah, Mohammed Bekhti

International Journal of Aviation, Aeronautics, and Aerospace

Currently; grapheme offers a new opportunity to use in space technology and this is due to its amazing properties like conductivity, strength, flexibility and transparency which allows us to exploit new generation of ultra-fast nanoscale components; Since future wireless communication techniques are geared towards the use of the high frequency spectrum and many recent research prove this trend. This letter presents a proposal for design of a dual graphene-based antenna to use in new communication techniques in Ka band, where the proposed antenna can work for uplink and dowlink frequencies at same time since it has return loss less then …

Recurrent Residual U-Net For Medical Image Segmentation, Md Zahangir Alom, Christopher Yakopcic, Mahmudul Hasan, Tarek M. Taha, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Deep learning (DL)-based semantic segmentation methods have been providing state-of-the-art performance in the past few years. More specifically, these techniques have been successfully applied in medical image classification, segmentation, and detection tasks. One DL technique, U-Net, has become one of the most popular for these applications. We propose a recurrent U-Net model and a recurrent residual U-Net model, which are named RU-Net and R2U-Net, respectively. The proposed models utilize the power of U-Net, residual networks, and recurrent convolutional neural networks. There are several advantages to using these proposed architectures for segmentation tasks. First, a residual unit helps when training deep …

A Survey Of Techniques For Mobile Service Encrypted Traffic Classification Using Deep Learning, Pan Wang, Xuejiao Chen, Feng Ye, Zhixin Sun

Electrical and Computer Engineering Faculty Publications

The rapid adoption of mobile devices has dramatically changed the access to various net- working services and led to the explosion of mobile service traffic. Mobile service traffic classification has been a crucial task that attracts strong interest in mobile network management and security as well as machine learning communities for past decades. However, with more and more adoptions of encryption over mobile services, it brings a lot of challenges about mobile traffic classification. Although classical machine learning approaches can solve many issues that port and payload-based methods cannot solve, it still has some limitations, such as time-consuming, costly handcrafted …

Autonomous Combat Robot, Andrew J. Szabo Ii, Chris Heldman, Tristin Weber, Tanya Tebcherani, Holden Leblanc, Fabian Ardeljan

Williams Honors College, Honors Research Projects

This honors project will also serve as an engineering senior design project.

The objective is to design and build the software and electrical systems for a 60 lb weight class combat robot that will function autonomously and outperform manually driven robots during competition.

While running autonomously, the robot will use LiDAR sensors to detect and attack opponent robots. This robot will also be able to be remote controlled in manual mode. This will mitigate the risk in case the autonomy or sensors fail. LED lights on the robot will indicate whether it is in autonomous or manual mode. The system …

Smart Garage Opener, Jacob Wasson

Williams Honors College, Honors Research Projects

The purpose of this research project was to design an anti-theft device that interfaces with a standard garage door opener to allow packages to easily be delivered into a garage in a safe and secure manner. Primary functionality of the device is to use a package’s tracking number and corresponding barcode to open and close a garage door to a preset height so that a package can be delivered inside the garage before it closes. My contribution to the project revolved around the programming and board design of the microcontroller circuit that controls the input and output signals of the …

Cycle Assist, Tyler Matthews

Williams Honors College, Honors Research Projects

The senior engineering design project presented in the paper that succeeds this, outlines the steps taken to design and implement an electronic bicycle that is able to keep a user’s heart-rate in a selected “intensity zone” though the use of an electronic motor and custom control circuitry. My portion of this project was to allow for safe and consistent power delivery to the rest of the electronics. That is to say, I built a battery pack and battery management system (BMS) to safely supply sufficient power to the rest of the electronics that were required for this project. In order …

S.A.V.E. M.E., Taylor Davis, Kelly Nicole O'Neill, Adrianna M. Dunlap, Parsa Esshaghi Bayat

Williams Honors College, Honors Research Projects

S.A.V.E. M.E. stands for Submerged Automated Vehicular Elevation Minor Extraction or alternatively a Home Swimming Pool Rescue Device. The objective of this project is to design and prototype a system that will make unattended swimming pools through detecting a victim’s presence, deploying a means to save the victim, and alerting others nearby of the situation. This system encompasses sensors and devices within the pool and an alarm system outside of the pool. Upon detection of a sufficiently sized object entering the pool when the system is armed, a device will maneuver to the victim and deploy a flotation device that …

Compact Broadband Triple-Ring Five-Port Reflectometer For Microwave Brain Imaging Applications, Toufiq Md Hossain, Mohd Faizal Jamlos, Mohd Aminudin Jamlos, Ping Jack Shoh, Siti Zuraidah Ibrahim, Muammar Mohamad Isa, Dominque M.M.-P. Schreurs, Adam Narbudowicz, Mohd Fairusham Ghazali

Articles

The broadband five-port refectometer (FPR) is proposed using a triple-ring based technique. The design introduces a tapering in the inter-ring transmission lines (TLs), which provides additional degrees of freedom for optimization and contributes to increased bandwidth. The miniaturization strategy allows incorporating the third ring without signifcant size increase. In addition, a method for expressing the effective physical dimension of a planar symmetric FPR is also presented in an easily comprehensible way, which can be implemented for other symmetric planar junctions with more than four ports. The proposed design comprises three concentric rings with phase-shifting arrangements between the inter-ring TLs and …

Ict-Enabled Control And Energy Management Of Community Microgrids For Resilient Smart Grid Operation, Mahmoud Saleh

Dissertations and Theses

Our research has focused on developing novel controllers and algorithms to enhance the resilience of the power grid and increase its readiness level against major disturbances.

The U.S. power grid currently encounters two main challenges: (1) the massive and extended blackouts caused by natural disasters, such as hurricane Sandy. These blackouts have raised a national call to explore innovative approaches for enhanced grid resiliency. Scrutinizing how previous blackouts initiated and propagated throughout the power grid, the major reasons are lack of situational awareness, lack of real-time monitoring and control, underdeveloped controllers at both the transmission and distribution levels, and lack …

Software Defined Radio For Hybrid Beamforming Applications, Jianyet Lee

Dissertations and Theses

Beamforming techniques have been deployed in both licensed networks such as LTE network and unlicensed network such as IEEE802.11ac WiFi. The scope of work for this thesis is to leverage the benefits of beamforming techniques and software defined radio platform in developing a fully functioning LTE testbed. The testbed can be further developed to specific application for drone-to-drone or D2D communication independent of intervention from base stations. Applying beamforming techniques to devices such as drones can solve poor quality signal detection at the receivers due to the interference signals generated by other devices in the attempt to communicate with the …

Distance-Based Cluster Head Election For Mobile Sensing, Ruairí De Fréin, Liam O'Farrell

Conference papers

Energy-efficient, fair, stochastic leader-selection algorithms are designed for mobile sensing scenarios which adapt the sensing strategy depending on the mobile sensing topology. Methods for electing a cluster head are crucially important when optimizing the trade-off between the number of peer-to- peer interactions between mobiles and client-server interactions with a cloud-hosted application server. The battery-life of mobile devices is a crucial constraint facing application developers who are looking to use the convergence of mobile computing and cloud computing to perform environmental sensing. We exploit the mobile network topology, specifically the location of mobiles with respect to the gateway device, to stochastically …

3d Signal Strength Mapping Of 2.4ghz Wifi Networks, Brett D. Glidden

Electrical Engineering

Many commercial businesses operate out of multi-story office buildings. These companies often use many Wi-Fi access points to set up their own wireless network. IT personnel determine proper Wi-Fi access point placement using Wi-Fi strength maps. Conventional Wi-Fi strength maps only provide a two-dimensional view representing the wireless access point's effective range. The signal quality and strength measurements do not include changing vertical elevation. Efficient network layout in a multi-story building requires a system calculating signal quality metrics in three dimensions.

This project involves designing and prototyping a system to achieve 2.4GHz Wi-Fi signal quality measurements in a three-dimensional reference …

Effect Of Wireless Communication Delay On Dc Microgrids Performance, Mahmoud Saleh, Yusef Esa, Ahmed Mohamed

Publications and Research

This paper investigates the effect of wireless communication technologies latency on the converters and the bus voltage of centrally communication based controlled DC microgrids (MGs) during islanding. A DC microgrid with its communication based control scheme was modeled to show the impact of latency. Simulation results show that the impact may be severe depending on the design, and the operational condition of the microgrid before latency occurs.

Impact Of Communication Latency On The Bus Voltage Of Centrally Controlled Dc Microgrid During Islanding, Mahmoud Saleh, Yusef Esa, Ahmed Mohamed

Publications and Research

Maintaining a sustainable and reliable source of energy to supply critical loads within a renewable energy based microgrid (MG) during blackouts is directly related to its bus voltage variations. For example, voltage variation might trigger protection devices and disconnect DERs within the MG. Centrally controlled MGs (CCMGs) type is dependent on communication. Therefore, it is very important to analyze the impact of communication networks performance degradation, such as latency, on the bus voltage of CCMGs. This paper investigates the effect of wireless communication technologies latency on the bus voltage and performance of centralized DC MGs. Two mathematical models were developed …

Wireless Sensor Networks For Smart Communications, Mu Zhou, Qilian Liang, Hongyi Wu, Weixiao Meng, Kunjie Xu

Electrical & Computer Engineering Faculty Publications

(First paragraph) In the first edition of the special issue titled “Wireless Sensor Networks for Smart Communications”, a total of 22 manuscripts were received and 6 of these were accepted. This issue demonstrated that network congestion, user mobility, and adjacent spectrum interference are the main reasons for the degradation ofcommunication quality inWireless Sensor Networks (WSNs).

Cmos Radioactive Isotope Identification With Multichannel Analyzer And Embedded Neural Network, Samuel Murray

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

A radiation detection and identification system is designed and implemented to perform gamma ray spectroscopy on radioactive sources and identify which isotopes are present in the sources. A multichannel analyzer is implemented on an ASIC to process the signal produced from gamma rays detected by a scintillator and photomultiplier tube and to quantize the gamma ray energies to build a histogram. A fast, low memory embedded neural network is implemented on a microcontroller ASIC to identify the isotopes present in the gamma ray histogram produced by the multichannel analyzer in real time.

Advisors: Sina Balkir and Michael W. Hoffman

Wireless Sensors For Health Monitoring Of Marine Structures And Machinery, Francisco David Rojas Calvente

PhDs

Remote structural and machinery health monitoring (SMHM) of marine structures such as ships, oil and gas rigs, freight container terminals, and marine energy platforms can ensure their reliability. However, the wired sensors currently used in these applications are difficult and expensive to install and maintain. Wireless Sensor Networks (WSN) can potentially replace them but there are significant capability gaps that currently prevent their long-term deployment in the harsh marine environment and the structurally-complex, compartmentalised, all-metal scenarios with high volume occupancy of piping, ducting and operational machinery represented by marine structures. These gaps are in sensing, processing and communication hardware and …

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

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, low data rate, …

High-Bandwidth Iop Sensing Backscatter Transceiver, Mark Manuel

Electrical Engineering

This document describes the design and build of a mobile phone attachment that communicates with an ASIC embedded smart contact lens. The portable device enables patients and clinicians to conveniently and instantaneously measure intraocular pressure (IOP). The device replaces bulky and expensive benchtop RF synthesizer and signal analyzer machines required for communication to the smart contact lens into a portable and convenient device. The transceiver transmits VHF ISM band radio and can capture reflected backscatter On-Off-Keying modulated message signals at bandwidths from DC to 130MHz.

Performance Evaluation Of Energy-Autonomous Sensors Using Power-Harvesting Beacons For Environmental Monitoring In Internet Of Things (Iot), George Dan Moiş, Teodora Sanislav, Silviu Corneliu Folea, Sherali Zeadally

Information Science Faculty Publications

Environmental conditions and air quality monitoring have become crucial today due to the undeniable changes of the climate and accelerated urbanization. To efficiently monitor environmental parameters such as temperature, humidity, and the levels of pollutants, such as fine particulate matter (PM2.5) and volatile organic compounds (VOCs) in the air, and to collect data covering vast geographical areas, the development of cheap energy-autonomous sensors for large scale deployment and fine-grained data acquisition is required. Rapid advances in electronics and communication technologies along with the emergence of paradigms such as Cyber-Physical Systems (CPSs) and the Internet of Things (IoT) have led to …

A Lightweight Classification Algorithm For Human Activity Recognition In Outdoor Spaces, Graham Mccalmont, Huiru Zheng, Haiying Wang, S. I. Mcclean, Matteo Zallio, Damon Berry

Conference Papers

The aim of this paper is to discuss the development of a lightweight classification algorithm for human activity recognition in a defined setting. Current techniques to analyse data such as machine learning are often very resource intensive meaning they can only be implemented on machines or devices that have large amounts of storage or processing power. The lightweight algorithm uses Euclidean distance to measure the difference between two points and predict the class of new records.

The results of the algorithm are largely positive achieving accuracy of 100% when classifying records taken from the same sensor position and accuracy of …

Low-Cost Multimode Patch Antenna For Dual Mimo And Enhanced Localization Use, Adam Narbudowicz, Max Ammann

Articles

This paper proposes a simple, low-cost multi-mode patch antenna combining good MIMO performance with precise Angle of Arrival (AoA) estimation. The AoA is based on the monopulse antenna concept, however, unlike in radar applications, the necessity for complex circuitry is replaced by the intrinsic properties of even and odd resonant patch modes. This capability is advantageous for future “Internet of Things” antennas, embedded into low-cost and size-constrained devices. The envelope correlation coefficient, measured in an anechoic chamber, is below 1.5 %, ensuring good MIMO performance. An exemplary addition to localization algorithm exploiting antenna properties is demonstrated.