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Full-Text Articles in Computer Engineering

The Roadmap To An Improved Braille Display Design, Emma Garofalo, Trey Alexander, Luke Shankland, Michael Smith, Michael Cheng, Michael Bishai, Lauren Sun Nov 2023

The Roadmap To An Improved Braille Display Design, Emma Garofalo, Trey Alexander, Luke Shankland, Michael Smith, Michael Cheng, Michael Bishai, Lauren Sun

Student Scholar Symposium Abstracts and Posters

Our innovative braille display, focused on affordability and education, fills a notable void in the market of refreshable braille displays, which are typically costly and not designed primarily for educational use. This product stands out as an economical educational aid for people with visual impairments. It features a system where pressing a keyboard alphabet key corresponds to specific braille pins, allowing for the display of letters or characters. Additionally, our design can represent simple geometric shapes, like circles or squares, using the braille pins. When these pins are raised, the user can feel the braille representation of the character or …


Towards Qos-Based Embedded Machine Learning, Tom Springer, Erik Linstead, Peiyi Zhao, Chelsea Parlett-Pelleriti Oct 2022

Towards Qos-Based Embedded Machine Learning, Tom Springer, Erik Linstead, Peiyi Zhao, Chelsea Parlett-Pelleriti

Engineering Faculty Articles and Research

Due to various breakthroughs and advancements in machine learning and computer architectures, machine learning models are beginning to proliferate through embedded platforms. Some of these machine learning models cover a range of applications including computer vision, speech recognition, healthcare efficiency, industrial IoT, robotics and many more. However, there is a critical limitation in implementing ML algorithms efficiently on embedded platforms: the computational and memory expense of many machine learning models can make them unsuitable in resource-constrained environments. Therefore, to efficiently implement these memory-intensive and computationally expensive algorithms in an embedded computing environment, innovative resource management techniques are required at the …


Open Hardware In Science: The Benefits Of Open Electronics, Michael Oellermann, Jolle W. Jolles, Diego Ortiz, Rui Seabra, Tobias Wenzel, Hannah Wilson, Richelle L. Tanner May 2022

Open Hardware In Science: The Benefits Of Open Electronics, Michael Oellermann, Jolle W. Jolles, Diego Ortiz, Rui Seabra, Tobias Wenzel, Hannah Wilson, Richelle L. Tanner

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Openly shared low-cost electronic hardware applications, known as open electronics, have sparked a new open-source movement, with much untapped potential to advance scientific research. Initially designed to appeal to electronic hobbyists, open electronics have formed a global “maker” community and are increasingly used in science and industry. In this perspective article, we review the current costs and benefits of open electronics for use in scientific research ranging from the experimental to the theoretical sciences. We discuss how user-made electronic applications can help (I) individual researchers, by increasing the customization, efficiency, and scalability of experiments, while improving data quantity and quality; …


Cognality Vr: Exploring A Mobile Vr App With Multiple Stakeholders To Reduce Meltdowns In Autistic Children, Louanne E. Boyd, Espen Garner, Ian Kim, Gianna Valencia Apr 2022

Cognality Vr: Exploring A Mobile Vr App With Multiple Stakeholders To Reduce Meltdowns In Autistic Children, Louanne E. Boyd, Espen Garner, Ian Kim, Gianna Valencia

Engineering Faculty Articles and Research

Many autistic children can have difficulty communicating, understanding others, and interacting with new and unfamiliar environments. At times they may suffer from a meltdown. The major contributing factor to meltdowns is sensory overwhelm. Technological solutions have shown promise in improving the quality of life for autistic children-however little exists to manage meltdowns. In this work with stakeholders, we design and deploy a low cost, mobile VR application to provide relief during sensory discomfort. Through the analysis of surveys from 88 stakeholders from a variety of groups (i.e., autistic adults, children with autism, parents of autistic individuals, and medical practitioners), we …


Online Laboratory Course Using Low Tech Supplies To Introduce Digital Logic Design Concepts, Dhanya Nair Jun 2021

Online Laboratory Course Using Low Tech Supplies To Introduce Digital Logic Design Concepts, Dhanya Nair

Engineering Faculty Articles and Research

This paper describes a Digital Logic Design Laboratory Course developed to engage students with hardware systems within an online setting. This is a junior level core course for students from Computer Science (CS), Computer Engineering (CE) and Electrical Engineering (EE). Hence, the laboratories are designed to provide the hands-on experience of breadboarding, testing and debugging essential to CE and EE while accommodating CS students with no prior hardware experience. Commercially available low-cost electronic trainers (portable workstations) are loaned to the students in addition to basic electronic components. To ensure a strong foundation in debugging, prior to utilizing these workstations, students …


On-Device Deep Learning Inference For System-On-Chip (Soc) Architectures, Tom Springer, Elia Eiroa-Lledo, Elizabeth Stevens, Erik Linstead Mar 2021

On-Device Deep Learning Inference For System-On-Chip (Soc) Architectures, Tom Springer, Elia Eiroa-Lledo, Elizabeth Stevens, Erik Linstead

Engineering Faculty Articles and Research

As machine learning becomes ubiquitous, the need to deploy models on real-time, embedded systems will become increasingly critical. This is especially true for deep learning solutions, whose large models pose interesting challenges for target architectures at the “edge” that are resource-constrained. The realization of machine learning, and deep learning, is being driven by the availability of specialized hardware, such as system-on-chip solutions, which provide some alleviation of constraints. Equally important, however, are the operating systems that run on this hardware, and specifically the ability to leverage commercial real-time operating systems which, unlike general purpose operating systems such as Linux, can …


Supporting Self-Regulation Of Children With Adhd Using Wearables: Tensions And Design Challenges, Franceli L. Cibrian, Kimberley D. Lakes, Arya Tavakoulnia, Kayla Guzman, Sabrina Schuck, Gillian R. Hayes Apr 2020

Supporting Self-Regulation Of Children With Adhd Using Wearables: Tensions And Design Challenges, Franceli L. Cibrian, Kimberley D. Lakes, Arya Tavakoulnia, Kayla Guzman, Sabrina Schuck, Gillian R. Hayes

Engineering Faculty Articles and Research

The design of wearable applications supporting children with Attention Deficit Hyperactivity Disorders (ADHD) requires a deep understanding not only of what is possible from a clinical standpoint but also how the children might understand and orient towards wearable technologies, such as a smartwatch. Through a series of participatory design workshops with children with ADHD and their caregivers, we identified tensions and challenges in designing wearable applications supporting the self-regulation of children with ADHD. In this paper, we describe the specific challenges of smartwatches for this population, the balance between self-regulation and co-regulation, and tensions when receiving notifications on a smartwatch …


Low-Energy Acceleration Of Binarized Convolutional Neural Networks Using A Spin Hall Effect Based Logic-In-Memory Architecture, Ashkan Samiee, Payal Borulkar, Ronald F. Demara, Peiyi Zhao, Yu Bai May 2019

Low-Energy Acceleration Of Binarized Convolutional Neural Networks Using A Spin Hall Effect Based Logic-In-Memory Architecture, Ashkan Samiee, Payal Borulkar, Ronald F. Demara, Peiyi Zhao, Yu Bai

Engineering Faculty Articles and Research

Deep Learning (DL) offers the advantages of high accuracy performance at tasks such as image recognition, learning of complex intelligent behaviors, and large-scale information retrieval problems such as intelligent web search. To attain the benefits of DL, the high computational and energy-consumption demands imposed by the underlying processing, interconnect, and memory devices on which software-based DL executes can benefit substantially from innovative hardware implementations. Logic-in-Memory (LIM) architectures offer potential approaches to attaining such throughput goals within area and energy constraints starting with the lowest layers of the hardware stack. In this paper, we develop a Spintronic Logic-in-Memory (S-LIM) XNOR neural …