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Featured submissions

August 2022

July 2022

  • FY2022 statistics:

    • 99,422 items in UA Campus Repository (as of June 30, 2022)

    • 2,506,430 downloads (entire repository) from July 1, 2021 - June 30, 2022

    • The 12,500th article collected under the UA Open Access Policy was added to the UA Faculty Publications collection in April 2022

    • 315,827 downloads of open research articles from this collection from July 1, 2021 - June 30, 2022

June 2022

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  • Science Operations Planning and Implementation for the OSIRIS-REx Mission, Part 1: Process

    Polit, Anjani T.; Balram-Knutson, Sara S.; Audi, Edward; Becker, Tammy; Boynton, William V.; Dean, David; Drozd, Kristofer; Enos, Heather L.; Fitzgibbon, Michael; Galinsky, Ingrid; et al. (IEEE, 2022-03-05)
    The Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer (OSIRIS-REx) spacecraft arrived at the near-Earth asteroid (101955) Bennu in December 2018 and executed a science observation campaign to comprehensively characterize the asteroid. Proximity operations at Bennu included orbital phases and flyby phases with various viewing geometries and altitudes. The complexity of the mission plan, integrated instrument operations, and the challenges of spacecraft navigation in the microgravity environment required an intricate planning and implementation process that included participation and coordination among all mission elements. The Science Planning Team (SPT) and the Implementation Team (IpT) at the University of Arizona planned and implemented all science and most optical navigation observations. Prior to the formal planning process, science requirements were mapped to mission phases and observation geometry constraints. During development of the mission phases, the navigation team produced a spacecraft trajectory, and the SPT developed the pointing and attitude profile to meet the specified constraints. In the strategic planning process, which began three months prior to execution, the SPT conducted sensitivity analysis of the observation designs against a set of perturbed trajectories delivered by the navigation team to ensure that they were robust to navigational uncertainties. Planning of the specific observations to occur within each phase was divided into units of weeks, and the plans for each week were developed and implemented on a rolling eight-week tactical planning and implementation cycle, ending with execution and data downlink. This cycle included a standardized schedule of activities and gateways to ensure that every observation plan underwent a full suite of analysis, verification, and approval in the allocated timeframe. Checklists guided the SPT and IpT through the build and verification process to confirm plan safety and fidelity. The SPT led the first four weeks of the tactical process, with participation from the IpT and other stakeholders. During the first two weeks, the SPT gathered information from stakeholders, conducted preliminary planning to confirm the science observations were feasible and obeyed spacecraft constraints, and determined how to integrate instrument commanding with the spacecraft pointing profile. The SPT started the final observation design and planning six weeks prior to execution. Once complete, plan walkthroughs were conducted with stakeholders, which culminated in a go/no-go decision to proceed with implementation at the four-week point. In the last four weeks of the tactical planning and implementation process, the IpT led the final processing of science plans with participation from stakeholders. The IpT compiled the plans, performed comprehensive safety checks against established spacecraft and instrument flight rules, and generated flight products and artifacts. After IpT delivered the flight products, the spacecraft team integrated them with the spacecraft sequencing, performed ground testing, and produced an integrated report. IpT reviewed the report, verifying instrument health and safety and confirming nominal plan execution in the ground simulation. The final flight products were uplinked to the spacecraft a few days prior to the execution week. During execution, the IpT and other stakeholders monitored instrument performance and viewed science and navigation data. Resulting science data products were used for operational decisions and science investigations.
  • International Telemetering Conference Proceedings, Volume 56 (2021)

    International Foundation for Telemetering, 2021-10
  • Pseudo-Electrical Alternans: Beyond Pericardial Effusion

    Jaina, Akhil; Kaurb, Parneet; Gasparyanc, Lilit; Jindald, Rishabh; Kelaiyae, Arjun; Popatf, Apurva; Miranig, Zankhan; Buragamadagua, Bhanusowmya; Jain, Siddharth; Mercy Catholic Medical Center, PA, USA; et al. (International Foundation for Telemetering, 2021-10)
    Electrical alternans on ECG is reported in substantial pericardial effusion. Pseudo Electrical alternans (pseudoEA) is the alternation in the QRS amplitude in the absence of pericardial effusion. We reviewed 16 such cases of pseudoEA (26-72 years, 68.75% males, 31.25% females). Besides physiological causes, cardiac diagnosis included arrhythmia (31.25%), coronary artery disease (18.75%), congestive heart failure (12.5%) in our review. The most common non-cardiac diagnosis was bronchial asthma. PseudoEA in both chest and limb leads was seen in 42.8%, chest leads alone in 35.7%, and limb leads alone in 21.4%. Telemetry surveillance is useful in identifying pseudoEA and confirms it by its reversal after treating the main pathology or removing the causing agent. There should be a high index of suspicion amongst physicians when electrical alternans is present on telemetry to identify and treat the alternative conditions in the absence of pericardial effusion.
  • Edge Machine Learning for Face Detection

    Cooper, Geffen; Manjunath, B.S.; Isukapalli, Yogananda; University of California, Santa Barbara (International Foundation for Telemetering, 2021-10)
    This paper describes an implementation of edge machine learning for vision-based classification and detection tasks. In edge machine learning, machine and deep learning algorithms are executed locally on embedded devices rather than on more powerful computers or the cloud. The main task explored is face detection using a low-power microcontroller. This device utilizes a convolutional neural network (CNN) accelerator that optimizes convolution and pooling operations for fast power-efficient inference. Development for this system requires building and training a hardwarelimited CNN rather than fine-tuning a pre-trained state-of-the-art model. The development process is discussed along with the constraints of this embedded device.
  • An Experiment on Energy Harvesting for Aircraft Instrumentation

    Rice, Michael; Giullian, Amy; Brigham Young University (International Foundation for Telemetering, 2021-10)
    Sensor installation for flight test instrumentation is a difficult process because the sensors must be wired to a central power unit. A small power source for transducers would make the installation process more efficient. This paper investigates the power output of a piezoelectric energy harvester. An experiment was conducted using a piezoelectric diaphragm connected to a full-wave bridge rectifier. The circuit is analyzed and experimental results are presented. The results are analyzed to determine if the output power is sufficient to supply a small transducer.

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