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1. A Small-scale Implementation of Industry 4.0

   Aqlan, Faisal; Alabsi, Mohammed; Baxter, Ethan; Sreekanth, Ramakrishnan (January 2020, Proceedings of the 2020 IISE Annual Conference)

   null (Ed.)

   This paper discusses the implementation of Industry 4.0 in an educational setting. Simulation, virtual reality, analytics, robotics and automation, and 3D printing are integrated to develop a small-scale production line for producing and inspecting 3D printed parts. The system consists of a robot and controller, programmable logic controller, 3D printer, machine vision system, conveyor belt, 3-phase motor and motor controller, webcam, PC and monitor, Raspberry Pi computer, pneumatic system, beam sensor, simulation software, and VR equipment. The system components are connected via ethernet cables running to a basic ethernet switch. An ethernet router is also connected to the switch to resolve IP connection attempts by the connected components. A mini CNC machine is used to drill holes on small metal parts that are assembled with 3D printed parts and plastic bricks to make a car toy. A robot is pre-programmed to perform the assembly of the car toy and a Cognex® camera is used to inspect the parts. Deep learning models are used to predict the remaining useful life of the drilling bits. 

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2. Smart Webcam Cover: Exploring the Design of an Intelligent Webcam Cover to Improve Usability and Trust

   https://doi.org/10.1145/3494983  

   Do, Youngwook; Park, Jung Wook; Wu, Yuxi; Basu, Avinandan; Zhang, Dingtian; Abowd, Gregory D.; Das, Sauvik (December 2021, Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies)

   Laptop webcams can be covertly activated by malware and law enforcement agencies. Consequently, 59% percent of Americans manually cover their webcams to avoid being surveilled. However, manual covers are prone to human error---through a survey with 200 users, we found that 61.5% occasionally forget to re-attach their cover after using their webcam. To address this problem, we developed Smart Webcam Cover (SWC): a thin film that covers the webcam (PDLC-overlay) by default until a user manually uncovers the webcam, and automatically covers the webcam when not in use. Through a two-phased design iteration process, we evaluated SWC with 20 webcam cover users through a remote study with a video prototype of SWC, compared to manual operation, and discussed factors that influence users' trust in the effectiveness of SWC and their perceptions of its utility. 

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3. Light-weight electrophysiology hardware and software platform for cloud-based neural recording experiments

   https://doi.org/10.1088/1741-2552/ac310a  

   Voitiuk, Kateryna; Geng, Jinghui; Keefe, Matthew G.; Parks, David F.; Sanso, Sebastian E.; Hawthorne, Nico; Freeman, Daniel B.; Currie, Rob; Mostajo-Radji, Mohammed A.; Pollen, Alex A.; et al (November 2021, Journal of Neural Engineering)

   Abstract Objective.Neural activity represents a functional readout of neurons that is increasingly important to monitor in a wide range of experiments. Extracellular recordings have emerged as a powerful technique for measuring neural activity because these methods do not lead to the destruction or degradation of the cells being measured. Current approaches to electrophysiology have a low throughput of experiments due to manual supervision and expensive equipment. This bottleneck limits broader inferences that can be achieved with numerous long-term recorded samples.Approach.We developed Piphys, an inexpensive open source neurophysiological recording platform that consists of both hardware and software. It is easily accessed and controlled via a standard web interface through Internet of Things (IoT) protocols.Main results.We used a Raspberry Pi as the primary processing device along with an Intan bioamplifier. We designed a hardware expansion circuit board and software to enable voltage sampling and user interaction. This standalone system was validated with primary human neurons, showing reliability in collecting neural activity in near real-time.Significance.The hardware modules and cloud software allow for remote control of neural recording experiments as well as horizontal scalability, enabling long-term observations of development, organization, and neural activity at scale. 

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4. Hands-on parallel & distributed computing with Raspberry Pi devices and clusters

   https://doi.org/10.1016/j.jpdc.2024.104996  

   Shoop, Elizabeth; Matthews, Suzanne J; Brown, Richard; Adams, Joel C (February 2025, Journal of Parallel and Distributed Computing)

   Parallel and distributed computing (PDC) concepts are now required topics for accredited undergraduate computer science programs. However, introducing PDC into the CS curriculum is challenging for several reasons, including an instructors’ lack of PDC knowledge and difficulties in accessing PDC hardware. This paper addresses both of these challenges by presenting free, interactive, web-based PDC teaching modules using inexpensive Raspberry Pi single board computers (SBCs). Our materials include a free disk image that makes it possible for instructors to build Raspberry Pi clusters in minutes and use our software in a variety of curricular contexts. Our multi-year assessment of these materials on students and faculty members indicates that: (i) our materials increased students’ confidence regarding important PDC concepts and motivated them to study PDC further; and (ii) our materials increased faculty members’ confidence and preparedness in teaching key PDC concepts at their own institutions. 

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5. Design and initial performance of the HARDWARE.astronomy Housekeeping (H.aHk) box

   https://doi.org/10.1117/12.2630261  

   Shaw, Stephen; Vettleson-Trutza, Larry; Ferkinhoff, Carl; Stammer, Adam; Antwi, Nathan; Kovacevich, Aubrey; Franta, Alex; Stacey, Gordon J.; Nikola, Thomas; Rooney, Christopher; et al (August 2022, Proc. SPIE 12190, Millimeter, Submillimeter, and Far-Infrared Detectors and Instrumentation for Astronomy XI)

   Zmuidzinas, Jonas; Gao, Jian-Rong (Ed.)

   An often unglamorous, yet critical, part of most millimeter/submillimeter astronomical instruments is cryogenic temperature monitoring and control. Depending on the operating wavelength of the instrument and detector technology, this could be stable temperatures in the Kelvin range for millimeter heterodyne systems to 100 mK temperatures at sub-micro-Kelvin stability as for many submillimeter bolometer systems. Here we describe a project of the HARDWARE.astronomy initiative to build a low-cost open-source temperature monitoring and control system. The HARDWARE.astronomy Housekeeping Box, or H.aHk Box (pronounced “hack box”) is developed primarily by undergraduates and employs existing open-source devices (e.g Arduino, Raspberry Pi) to reduce costs while also limiting the complexity of the development. The H.aHk Box features a chassis with a control computer and ten expansion slots that can be filled with a variety of expansion cards. These cards include initially an AC 4-wire temperature monitor and PID control cards. Future work will develop 2-wire temperature monitors, stepper motor controller, and high-power supply. The base-system will also be able to interface with other house-keeping systems over USB, serial port and ethernet. The first deployment of the H.aHk Box will be for the ZEUS-2 submillimeter grating spectrometer. All designs, firmware, software and parts list will be published online allowing for other projects to adopt the system and create custom expansion cards as needed. Here we describe the design (including mechanical, electrical, firmware, and software components) and initial performance of the H.aHk Box system with initial AC/DC 4-wire and PID cards. 

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