VLSI and Circuits, Embedded and Hardware Systems Commons^™

Using An Embedded System For A Quality Cup Of Coffee, Evan Powers, Joshua Stermer, Tsion Yohannes

2023 Symposium

Many coffee lovers spend up to $5 on a cup of coffee everyday. To save money one could make them at home, but a quality machine with PIDs start at $1000. Using an embedded system one could spend less than $50 and a few hours implement PIDs into an existing $400 machine that will last a lifetime. microcontroller. Learning C language combined with hardware implementation applied to cheap and simple everyday objects can improve everyday quality of life and save money.

This is challenging because we have to incorporate the additional circuitry into a pre established circuit with limited space, …

Combat Robot, Wayne Lambert, Elijah Harris, Brian Eiseman, Jordan Meyer

ONU Student Research Colloquium

The senior capstone project that was tasked to the team was the decision of choosing a challenge within a national robotics competition. The group decided to compete at the National Robotics Challenge in Marion, Ohio. The idea was to participate in the combat robot competition at this NRC event. Once this decision had been made the next steps were to get an idea of what the rules and requirements of the competition were and to try and to sketch a very rough drawing of what the ideal robot should look like. From there it was decided to start a timeline …

Sabr: Development Of A Neuromorphic Balancing Robot, Alec Yen, Yaw Mensah, Mark Dean

EURēCA: Exhibition of Undergraduate Research and Creative Achievement

We discuss the development of a self-adjusted balancing robot (SABR) using a neuromorphic computing framework for control. Implementations of two-wheeled balancing robots have been achieved using traditional algorithms, often in the form of proportional-integral-derivative (PID) control. We aim to achieve the same task using a neuromorphic architecture, which offers potential for higher power efficiency than conventional processing techniques. We utilize evolutionary optimization (EO) and the second iteration of Dynamic Adaptive Neural Network Arrays (DANNA2) developed by the Laboratory of Tennesseans Exploring Neural Networks (TENNLab). For the purpose of comparison, a traditional balancing robot was first designed using PID control; the …

A Note From The Editor, Daphne Fauber

Ideas: Exhibit Catalog for the Honors College Visiting Scholars Series

This piece is a letter from Daphne Fauber, the editor of this issue of Ideas. In the letter, the editor introduces the work of Dr. Paschalis Gkoupidenis as well as the moment in time in which his Visiting Scholars talk occurs.

An Electrooculography Prosthetic Control System, Walker Arce

UNO Student Research and Creative Activity Fair

For many surface EMG (sEMG) prosthetic control systems, the muscles on the affected limb are used to trigger the control system. This can lead to fatigue in the user as they have to maintain continuous muscle activation and coactivation in order to achieve prosthetic control [3]. The crux of any prosthetic control system is the human machine interface that is developed, and at present many control systems have complicated interfaces that limit the degrees of freedom of the prosthetics. This study focuses on the development of a low-cost prosthetic control peripheral that is compatible with the prosthetics developed by Dr. …

Virtual-Source Based Accurate Model For Predicting Noise Behavior At High Frequencies In Nanoscale Pmos Soi Transistors, Vaibhav R. Ramachandran, Saeed Mohammadi, Sutton Hathorn

The Summer Undergraduate Research Fellowship (SURF) Symposium

Complementary Metal Oxide Semiconductor (CMOS) technology at the nanometre scale is an excellent platform to implement monolithically integratedsystems because of the low cost of manufacturing and ease of integration. Newly developed CMOS Silicon on Insulator (SOI) transistors that are currentlydeveloped are suitable for use in radio frequency circuits. They find applications in many areas such as 5G telecommunication systems, high speed Wi-Fi andairport body-scanners. Unfortunately, the models for CMOS SOI transistors that are currently used in these circuits are inaccurate because of their complexity.The models currently used require the optimization of more than 200 variables. This paper aims to accurately …

Occupancy Estimation In Smart Building Using Hybrid Co2/Light Wireless Sensor Network, Chen Mao, Qian Huang

ASA Multidisciplinary Research Symposium

Smart building, which delivers useful services to residents at lowest cost and maximum comfort, has gained increasing attention in recent years. A variety of emerging information technologies have been adopted in modern buildings, such as wireless sensor networks, internet of things, big data analytics, deep machine learning, etc. Most people agree that a smart building should be energy efficient, and consequently, much more affordable to building owners. Building operation accounts for major portion of energy consumption in the United States. HVAC (heating, ventilating, and air conditioning) equipment is a particularly expensive and energy consuming of building operation. As a result, …

Reward Modulated Spike Timing Dependent Plasticity Based Learning Mechanism In Spiking Neural Networks, Shrihari Sridharan, Gopalakrishnan Srinivasan, Kaushik Roy

The Summer Undergraduate Research Fellowship (SURF) Symposium

Spiking Neural Networks (SNNs) are one of the recent advances in machine learning that aim to further emulate the computations performed in the human brain. The efficiency of such networks stems from the fact that information is encoded as spikes, which is a paradigm shift from the computing model of the traditional neural networks. Spike Timing Dependent Plasticity (STDP), wherein the synaptic weights interconnecting the neurons are modulated based on a pair of pre- and post-synaptic spikes is widely used to achieve synaptic learning. The learning mechanism is extremely sensitive to the parameters governing the neuron dynamics, the extent of …

An Ant-Based Sensor Measurement Data Gathering System, Bolun Zhang, Dimitrios Peroulis

The Summer Undergraduate Research Fellowship (SURF) Symposium

Large-scale industries involved with a great amount of sensor measurements in their work are facing many challenges in data collection. Sensors are not on the same network; therefore each measurement has to be managed separately. Gathering all the measurement data to one terminal could be difficult. Once a measurement is obtained, it takes significant amount of time to process the data.The approaches our group takes here is to build a giant ANT wireless network that holds all the sensors’ measurements. To be more specific, every sensor has an ANT chip set up on its side. Each ANT chip is as …

Modeling And Architectural Simulations Of The Statistical Static Timing Analysis Of The Variation Sources For Vlsi Circuits, Abu M. Baker

College of Engineering: Graduate Celebration Programs

As CMOS technology scales down, process variation introduces significant uncertainty in power and performance to VLSI circuits and significantly affects their reliability. Although Static-Timing Analysis (STA) remains an excellent tool, current trends in process scaling have imposed significant difficulties to STA. As one of the promising solutions, Statistical static timing analysis (SSTA) has become the frontier research topic in recent years in combating such variation effects. This poster will be focusing on two aspects of SSTA and its applications in VLSI designs: (1) Statistical timing modeling and analysis; and (2) Architectural implementations of the atomic operations (max and add) using …