Computer Engineering Commons^™

Energy Efficient Computing Using Scalable General Purpose Analog Processors, Ethan Paul Palisoc De Guzman

Master's Theses

Due to fundamental physical limitations, conventional digital circuits have not been able to scale at the pace expected from Moore’s law. In addition, computationally intensive applications such as neural networks and computer vision demand large amounts of energy from digital circuits. As a result, energy efficient alternatives are needed in order to provide continued performance scaling. Analog circuits have many well known benefits: the ability to store more information onto a single wire and efficiently perform mathematical operations such as addition, subtraction, and differential equation solving. However, analog computing also comes with drawbacks such as its sensitivity to process variation …

Scalable Cognitive Radio Network Testbed In Real Time, Kevin Z. Yu

Master's Theses

Modern society places an increasingly high demand on data transmission. Much of that data transmission takes place through communication over the frequency spectrum. The channels on the spectrum are limited resources. Researchers realize that at certain times of day some channels are overloaded, while others are not being fully utilized. A spectrum management system may be beneficial to remedy this efficiency issue. One of the proposed systems, Cognitive Radio Network (CRN), has progressed over the years thanks to studies on a wide range of subjects, including geolocation, data throughput rate, and channel handoff selection algorithm, which provide fundamental support for …

Intelligent And Secure Fog-Aided Internet Of Drones, Jingjing Yao

Dissertations

Internet of drones (IoD), which utilize drones as Internet of Things (IoT) devices, deploys several drones in the air to collect ground information and send them to the IoD gateway for further processing. Computing tasks are usually offloaded to the cloud data center for intensive processing. However, many IoD applications require real-time processing and event response (e.g., disaster response and virtual reality applications). Hence, data processing by the remote cloud may not satisfy the strict latency requirement. Fog computing attaches fog nodes, which are equipped with computing, storage and networking resources, to IoD gateways to assume a substantial amount of …

Characterization Of Time-Variant And Time-Invariant Assessment Of Suicidality On Reddit Using C-Ssrs, Manas Gaur, Vamsi Aribandi, Amanuel Alambo, Ugur Kursuncu, Krishnaprasad Thirunarayan, Jonathan Beich, Jyotishman Pathak, Amit Sheth

Publications

Suicide is the 10th leading cause of death in the U.S (1999-2019). However, predicting when someone will attempt suicide has been nearly impossible. In the modern world, many individuals suffering from mental illness seek emotional support and advice on well-known and easily-accessible social media platforms such as Reddit. While prior artificial intelligence research has demonstrated the ability to extract valuable information from social media on suicidal thoughts and behaviors, these efforts have not considered both severity and temporality of risk. The insights made possible by access to such data have enormous clinical potential - most dramatically envisioned as a trigger …

Bibliometric Analysis On Dynamic Target Tracking By Mobile Robot, Gaurav Atha Mr., Siddhant Chaturvedi Mr., Atishraj Desai Mr., Dhrumil Desai Mr., Shripad V. Deshpande Mr.

Library Philosophy and Practice (e-journal)

The survey and bibliometric research on dynamic target tracking by a mobile robot are discussed in this paper. The primary goal of this bibliometric analysis is to comprehend and analyze the scope of the literature in the field of mobile robots for obstacle avoidance, path planning and target tracking using Robot Operating System (ROS). The ROS contains various tools for data analysis, incorporates multiple robots and their sensors, and supports devices interaction for target seeking and localization in mobile robots. This detailed review was performed on various research publications about the mapping of the unknown field/environment by the ROS based …

Arm-Hand Systems As Hybrid Parallel-Serial Systems: A Novel Inverse Kinematics Solution, Shuwei Qiu, Mehrdad Kermani Ph.D., P.Eng.

Electrical and Computer Engineering Publications

No abstract provided.

Impact Assessment, Detection, And Mitigation Of False Data Attacks In Electrical Power Systems, Sagnik Basumallik

Dissertations - ALL

The global energy market has seen a massive increase in investment and capital flow in the last few decades. This has completely transformed the way power grids operate - legacy systems are now being replaced by advanced smart grid infrastructures that attest to better connectivity and increased reliability. One popular example is the extensive deployment of phasor measurement units, which is referred to PMUs, that constantly provide time-synchronized phasor measurements at a high resolution compared to conventional meters. This enables system operators to monitor in real-time the vast electrical network spanning thousands of miles. However, a targeted cyber attack on …

Person Re-Identification And An Adversarial Attack And Defense For Person Re-Identification Networks, Yu Zheng

Dissertations - ALL

Person re-identification (ReID) is the task of retrieving the same person, across different camera views or on the same camera view captured at a different time, given a query person of interest. There has been great interest and significant progress in person ReID, which is important for security and wide-area surveillance applications as well as human computer interaction systems. In order to continuously track targets across multiple cameras with disjoint views, it is essential to re-identify the same target across different cameras. This is a challenging task due to several reasons including changes in illumination and target appearance, and variations …

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 …

Smart E-Bike Conversion Kit And Helmet, Megan West, Marena Trujillo, Hossein Asghari

Honors Thesis

With many state governments across the United States implementing shutdowns to prevent the spread of COVID-19, many bike retailers have seen dramatic increases in bike sales. Electric bicycles (e-bikes) have become increasingly popular as the public searches for alternatives to public transportation. Unfortunately, e-bike users assume some risk by riding bikes that are faster than conventional bicycles. While kits to convert conventional bicycles to e-bikes exist, no “smart” e-bike/helmet kit specifically designed to keep the user safe is currently available on the market. To mitigate risks, a smart e-bike conversion kit with multiple novel safety features, including auditory and visual …

Malicious Hardware & Its Effects On Industry, Gustavo Perez

Computer Science and Computer Engineering Undergraduate Honors Theses

In recent years advancements have been made in computer hardware security to circumnavigate the threat of malicious hardware. Threats come in several forms during the development and overall life cycle of computer hardware and I aim to highlight those key points. I will illustrate the various ways in which attackers exploit flaws in a chip design, or how malicious parties take advantage of the many steps required to design and fabricate hardware. Due to these exploits, the industry and consumers have suffered damages in the form of financial loss, physical harm, breaches of personal data, and a multitude of other …

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 …

Automated Bottling Station - Packaging System, Lauren Nicole Zinzilieta

Honors College Theses

This report focuses on the packaging system used at the end of the FESTO bottling station that is located in EP 2355. The system will be made up of an x-y 300 mm x 300 mm gantry system, an Arduino, two micro-stepping stepper drivers, and two 152.4 mm (6 in) single acting cylinders with a 3D printed bracket attached to both. The gantry system will be located at the end of the conveyor belt and will be programmed to pick up three bottles at a time and then will move a specified number of steps in both the x and …

Stand-Alone Direct Current Power Network Based On Photovoltaics And Lithium-Ion Batteries For Reverse Osmosis Desalination Plant, Vishwas Powar, Rajendra Singh

Publications

Plummeting reserves and increasing demand of freshwater resources have culminated into a global water crisis. Desalination is a potential solution to mitigate the freshwater shortage. However, the process of desalination is expensive and energy-intensive. Due to the water-energy-climate nexus, there is an urgent need to provide sustainable low-cost electrical power for desalination that has the lowest impact on climate and related ecosystem challenges. For a large-scale reverse osmosis desalination plant, we have proposed the design and analysis of a photovoltaics and battery-based stand-alone direct current power network. The design methodology focusses on appropriate sizing, optimum tilt and temperature compensation techniques …

The Future Of Artificial Intelligence, Alex Guerra

Emerging Writers

Whether we like it or not Artificial Intelligence (AI) is coming, and we are not ready for it. AI has unimaginable potential and will revolutionize the world over the next few decades, but with this great potential we are faced with choices that could prove detrimental to humanity. This article examines the challenges AI presents and explores possible solutions to make AI align with human interests.

A Framework To Detect The Susceptibility Of Employees To Social Engineering Attacks, Hashim H. Alneami

Doctoral Dissertations and Master's Theses

Social engineering attacks (SE-attacks) in enterprises are hastily growing and are becoming increasingly sophisticated. Generally, SE-attacks involve the psychological manipulation of employees into revealing confidential and valuable company data to cybercriminals. The ramifications could bring devastating financial and irreparable reputation loss to the companies. Because SE-attacks involve a human element, preventing these attacks can be tricky and challenging and has become a topic of interest for many researchers and security experts. While methods exist for detecting SE-attacks, our literature review of existing methods identified many crucial factors such as the national cultural, organizational, and personality traits of employees that enable …

Path Planning With Deep Neural Networks, Paul Simmerling, Brendan Sayers, Paulo Alcantara Silva

Honors Scholar Theses

This report will cover the work and plans of the ECE 2107 Senior design team. The goal of the project is to design and build a fully autonomous self-driving car. This car will have a complete sensor suite including LIDAR, an IMU, a camera, and encoders. It will be based on a multi-level system where the highest level uses a neural network for advanced signal processing and analysis. The current state of the project is discussed as well as the final results. Project management and other constraints will be briefly investigated. This team is building a self driving car testbed …

A Study Of Deep Reinforcement Learning In Autonomous Racing Using Deepracer Car, Mukesh Ghimire

Honors Theses

Reinforcement learning is thought to be a promising branch of machine learning that has the potential to help us develop an Artificial General Intelligence (AGI) machine. Among the machine learning algorithms, primarily, supervised, semi supervised, unsupervised and reinforcement learning, reinforcement learning is different in a sense that it explores the environment without prior knowledge, and determines the optimal action. This study attempts to understand the concept behind reinforcement learning, the mathematics behind it and see it in action by deploying the trained model in Amazon's DeepRacer car. DeepRacer, a 1/18^th scaled autonomous car, is the agent which is trained …

Demo Abstract: Porting And Execution Of Anomalies Detection Models On Embedded Systems In Iot, Bharath Sudharsan, Pankesh Patel, Abdul Wahid, Muhammad Yahya, John G. Breslin, Muhammad Intizar Ali

Publications

In the Industry 4.0 era, Microcontrollers (MCUs) based tiny embedded sensor systems have become the sensing paradigm to interact with the physical world. In 2020, 25.6 billion MCUs were shipped, and over 250 billion MCUs are already operating in the wild. Such low-power, low-cost MCUs are being used as the brain to control diverse applications and soon will become the global digital nervous system. In an Industrial IoT setup, such tiny MCU-based embedded systems are equipped with anomaly detection models and mounted on production plant machines for monitoring the machine’s health/condition. These models process the machine’s health data (from temperature, …

A New Configuration Of Paralleled Modular Anpc Multilevel Converter Controlled By An Improved Modulation Method For 1 Mhz, 1 Mw Ev Charger, Mostafa Abarzadeh, Waqar A. Khan, Nathan Weise, Kamal Al-Haddad, Ayman M. El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

In this article, a new configuration of the modular multilevel converter (MLC) based on the parallel connection of three-level active-neutral-point-clamped (3L-ANPC) cells as well as its improved modulation method is proposed for 1 MHz, 1 MW electric vehicle (EV) megacharger. In the proposed paralleled modular ANPC-MLC, only six high-frequency silicon carbide (SiC) power switches operating at 333 kHz are required to generate 1 MHz switching frequency spectrum. Moreover, the operating voltage of all power devices is halved, the magnitude of the first switching frequency harmonic cluster is decreased by the factor of five, and the load current is equally distributed …

Reliability And Performance Improvement Of Puc Converter Using A New Single-Carrier Sensor-Less Pwm Method With Pseudo Reference Functions, Mostafa Abarzadeh, Saeed Peyghami, Kamal Al-Haddad, Nathan Weise, Liuchen Chang, Frede Blaabjerg

Electrical and Computer Engineering Faculty Research and Publications

A new single-carrier sensor-less pulsewidth modulation (PWM) method using suggested pseudo reference functions is proposed for packed U-cell (PUC) converter to improve performance and reliability of the PUC converter. It is composed of one PWM carrier signal and two suggested pseudo reference functions. By employing the proposed modulation method, the PUC dc capacitor voltage ripple is substantially decreased, and faster sensor-less capacitor voltage balancing is obtained. Moreover, the power losses are evenly distributed among all power switches. Consequently, notable reduction of the PUC dc capacitor voltage ripple and even distribution of the power loss among switches enhance the PUC converter's …

Bibliometric Analysis On Hand Gesture Controlled Robot, Karthik Bankapur, Himmat Singh, Akshit Gupta, Hritik Mathur, Harikrishnan R, Shivali Amit Wagle

Library Philosophy and Practice (e-journal)

This paper discusses about the survey and bibliometric analysis of hand gesture-controlled robot using Scopus database in analyzing the research by area, influential authors, countries, institutions, and funding agencies. The 293 documents are extracted from the year 2016 till 6^th March 2021 from the database. Bibliometric analysis is the statistical analysis of the research published as articles, conference papers, and reviews, which helps in understanding the impact of publication in the research domain globally. The visualization analysis is done with open-source tools namely GPS Visualizer, Gephi, VOS viewer, and ScienceScape. The visualization aids in a quick and clear understanding …

Bibliometric Analysis Of Particle Swarm Optimization Techniques Used To Enhance Low-Energy Adaptive Clustering Hierarchy Protocol For Wireless Sensor Networks, Anupkumar M. Bongale Dr.

Library Philosophy and Practice (e-journal)

Wireless Sensor Network (WSN) is a network of tiny wireless sensor nodes. The sensor nodes sense information and transmit the sensed information to a data collection point known as Base Station. WSNs have gained massive popularity due to their incredible benefits, and active research is ongoing for the past two decades. The primary concern with WSN is that the sensor operates on a limited power supply. Due to the nature of applications of WSNs and the hostile environment where the sensors are deployed, providing unlimited power or energy supply is not an option. Hence, the research work mainly focuses on …

Project Blipper, Peter Jacobs, Preston Delaware, Ryan Foster

Senior Design Project For Engineers

This project was sponsored by Clorox to design and create an automatic bottle-unscrambling system for possible implementation at their bottling plant in Chile. The objective was to use a robotic arm to unscramble bottles from an incoming conveyor belt and place them upright on an outbound conveyor belt. Throughout the research, design, and testing of solutions for this project, several design alternatives were found for each discipline, and will be presented to Clorox so that they can make an informed decision for how and if they want to move forward with implementation of this project.

The project was split into …

Spontaneous Formation Of Multilayer Refractory Carbide Coatings In A Molten Salt Media, Loic Constantin, Lisha Fan, Mathilde Pouey, Jérôme Roger, Bai Cui, Jean-François Silvain, Yongfeng Lu

Department of Electrical and Computer Engineering: Faculty Publications

Refractory materials hold great promise to develop functional multilayer coating for extreme environments and temperature applications but require high temperature and complex synthesis to overcome their strong atomic bonding and form a multilayer structure. Here, a spontaneous reaction producing sophisticated multilayer refractory carbide coatings on carbon fiber (CF) is reported. This approach utilizes a relatively low-temperature (950 °C) moltensalt process for forming refractory carbides. The reaction of titanium (Ti), chromium (Cr), and CF yields a complex, high-quality multilayer carbide coating composed of 1) Cr carbide (Cr₃C₂), 2) Ti carbide, and 3) Cr₃C₂ layers. …

Owsnet: Towards Real-Time Offensive Words Spotting Network For Consumer Iot Devices, Bharath Sudharsan, Sweta Malik, Peter Corcoran, Pankesh Patel, John G. Breslin, Muhammad Intizar Ali

Publications

Every modern household owns at least a dozen of IoT devices like smart speakers, video doorbells, smartwatches, where most of them are equipped with a Keyword spotting(KWS) system-based digital voice assistant like Alexa. The state-of-the-art KWS systems require a large number of operations, higher computation, memory resources to show top performance. In this paper, in contrast to existing resource-demanding KWS systems, we propose a light-weight temporal convolution based KWS system named OWSNet, that can comfortably execute on a variety of IoT devices around us and can accurately spot multiple keywords in real-time without disturbing the device's routine functionalities.

When OWSNet …

Cognitive Digital Twins For Smart Manufacturing, Muhammad Intizar Ali, Pankesh Patel, John G. Breslin, Ramy Harik, Amit Sheth

Publications

Smart manufacturing or Industry 4.0, a trend initiated a decade ago, aims to revolutionize traditional manufacturing using technology-driven approaches. Modern digital technologies such as the Industrial Internet of Things (IIoT), Big Data Analytics, Augmented/Virtual Reality, and Artificial Intelligence (AI) are the key enablers of new smart manufacturing approaches. The digital twin is an emerging concept whereby a digital replica can be built of any physical object. Digital twins are becoming mainstream; many organizations have started to rely on digital twins to monitor, analyze, and simulate physical assets and processes. The current use of digital twins for smart manufacturing is largely …