Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Human Error”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

A Bayesian approach to tracking patients having changing pharmacokinetic parameters

This paper considers the updating of Bayesian posterior densities for pharmacokinetic models associated with patients having changing parameter values. For estimation purposes it is proposed to use the Interacting Multiple Model (IMM) estimation algorithm, which is currently a popular algorithm in the aerospace community for tracking maneuvering targets. The IMM algorithm is described, and compared to the multiple model (MM) and Maximum A-Posteriori (MAP) Bayesian estimation methods, which are presently used for posterior updating when pharmacokinetic parameters do not change. Both the MM and MAP Bayesian estimation methods are used in their sequential forms, to facilitate tracking of changing parameters. Results indicate that the IMM algorithm is well suited for tracking time-varying pharmacokinetic parameters in acutely ill and unstable patients, incurring only about half of the integrated error compared to the sequential MM and MAP methods on the same example.

Bayes Theorem↗
NASA NTRSDate not supplied

Enhancing Air Traffic Control Planning with Automatic Speech Recognition

The decisions made during the Federal Aviation Administration Air Traffic Control System Command Center's planning teleconferences hold significant sway over the National Airspace System. Held every two hours, these teleconferences convene air traffic managers and stakeholders from across the nation to discuss airspace conditions, weather, and constraints, leading to the formulation and adjustment of traffic management initiatives. Given the critical nature of these decisions, the need for accurate and efficient record-keeping is paramount. In recent years, the application of automatic speech recognition has gained popularity across diverse industries, including aviation. While traditional applications focus on transcribing air traffic control communication, this paper explores a unique application of automatic speech recognition by converting the audio from planning teleconferences into text transcriptions. This innovative approach addresses key challenges in the field, presenting potential benefits for quality assurance, real-time participation, and downstream natural language processing tasks. A notable breakthrough in the machine learning community, namely the transformer neural network architecture, forms the backbone of the proposed solution in this paper. The transformer architecture's role in this research represents a paradigm shift in the efficiency of automatic speech recognition models. By reducing the amount of in-domain training data required, this architecture allows for the fine-tuning of such models like Whisper, originally pretrained on vast English speech datasets. The adaptability of the transformer architecture proves invaluable in capturing the nuances of aviation terminology and specific language used in planning teleconferences. Leveraging the Whisper model as a baseline, our research details the fine-tuning and validation using a dataset comprising 20 hours of meticulously transcribed planning teleconferences. Notably, the baseline pretrained Whisper model exhibited a word error rate of 18.77%. Through the fine-tuning process, the model achieved a substantial improvement, demonstrating an impressive performance with a reduced word error rate of 6.82%. This substantial decrease in WER not only highlights the effectiveness of the transformer architecture but also emphasizes the practical advancements achieved through the application of automatic speech recognition in this specific domain. The utilization of automatic speech recognition in planning teleconferences in this work introduces several novelties. Firstly, the creation of text transcriptions offers a valuable tool for quality assurance and facilitates the efficient review of teleconferences. This is an important aspect of the proposed solution, given the time-sensitive and high-stakes nature of decisions made during these meetings. Furthermore, text-searchable transcriptions provide a streamlined approach for locating and validating critical information, potentially saving hours of manual effort in searching through audio recordings. Moreover, our research identifies a key use case for external facilities and stakeholders. In situations where attendance at the planning teleconference is not feasible, having access to text transcriptions in real-time or shortly after the teleconference ends, proves to be a time-saving and informative resource. This feature enhances collaboration and ensures that stakeholders can stay abreast of important discussions and decisions even in their absence. Despite the efficiency gains facilitated by the transformer architecture in automatic speech recognition technology, it is essential to acknowledge the human factors in data creation. Subject matter experts play a crucial role in accurately transcribing planning teleconferences due to the specificity and complexity of the information discussed. The research dataset, consisting of 20 hours of transcribed planning teleconferences, forms the foundation for fine-tuning and validating the Whisper model. The achieved word error rate of 6.82% demonstrates promising advancements, particularly in recognizing essential aviation terminology within the teleconferences. In conclusion, this paper presents a comprehensive exploration of the application of automatic speech recognition in Air Traffic Control System Command Center planning teleconferences, leveraging the transformer architecture for enhanced efficiency. The novel contributions lie in the improved accessibility of decision-making records, real-time participation opportunities for external stakeholders, and the potential for downstream natural language processing advancements. As the aviation industry continues to evolve, the integration of automatic speech recognition technologies holds the promise of revolutionizing decision-making processes and contributing to the overall safety and efficiency of air traffic management.

ATM↗
NASA NTRS1978

Some modern control techniques for human operator modeling and identification

Some recent results in quantitative modeling of the human operator are reviewed as well as a method for processing his input-output data. Modern control techniques are applied to the pilot operating in a dynamic compensatory tracking task. Trained pilots are known to behave in an optimal manner under fully stressed conditions. This has led to the development of an optimal control model of the human operator which takes his limitations into account. A rationale for determining the appropriate cost functions is determined. Experimental results indicate that the model can closely predict pilot performance in one- or two-axis tracking tasks. The model predicts pilot remnant (noise), error scores, and frequency response in both single-axis and multi-axis tracking tasks.

Shirley, R. S.↗
NASA NTRS1984

Mean and Random Errors of Visual Roll Rate Perception from Central and Peripheral Visual Displays

A large number of roll rate stimuli, covering rates from zero to plus or minus 25 deg/sec, were presented to subjects in random order at 2 sec intervals. Subjects were to make estimates of magnitude of perceived roll rate stimuli presented on either a central display, on displays in the peripheral ield of vision, or on all displays simultaneously. Response was by way of a digital keyboard device, stimulus exposition times were varied. The present experiment differs from earlier perception tasks by the same authors in that mean rate perception error (and standard deviation) was obtained as a function of rate stimulus magnitude, whereas the earlier experiments only yielded mean absolute error magnitude. Moreover, in the present experiment, all stimulus rates had an equal probability of occurrence, whereas the earlier tests featured a Gaussian stimulus probability density function. Results yield a ood illustration of the nonlinear functions relating rate presented to rate perceived by human observers or operators.

Vandervaart, J. C.↗
NASA NTRS2007

Space Radiation Organ Doses for Astronauts on Past and Future Missions

We review methods and data used for determining astronaut organ dose equivalents on past space missions including Apollo, Skylab, Space Shuttle, NASA-Mir, and International Space Station (ISS). Expectations for future lunar missions are also described. Physical measurements of space radiation include the absorbed dose, dose equivalent, and linear energy transfer (LET) spectra, or a related quantity, the lineal energy (y) spectra that is measured by a tissue equivalent proportional counter (TEPC). These data are used in conjunction with space radiation transport models to project organ specific doses used in cancer and other risk projection models. Biodosimetry data from Mir, STS, and ISS missions provide an alternative estimate of organ dose equivalents based on chromosome aberrations. The physical environments inside spacecraft are currently well understood with errors in organ dose projections estimated as less than plus or minus 15%, however understanding the biological risks from space radiation remains a difficult problem because of the many radiation types including protons, heavy ions, and secondary neutrons for which there are no human data to estimate risks. The accuracy of projections of organ dose equivalents described here must be supplemented with research on the health risks of space exposure to properly assess crew safety for exploration missions.

Cucinotta, Francis A.↗
NASA NTRS2024

Effective structural impact detection and localization using convolutional neural network and Bayesian information fusion with limited sensors

Due to their unpredictable nature, many impact events (e.g., overheight vehicles striking on bridges) go unnoticed or get reported many hours later. However, they can induce structural failures or hidden damage that accelerates the structure’s long-term degradation. Therefore, prompt impact detection and localization strategies are essential for early warning of impact events and rapid maintenance of structures. Most existing impact detection strategies are developed for aircraft composite panels utilizing high-rate synchronized measurement from densely deployed sensors. Limited efforts have been made for infrastructure or human habitats which generally require large-scale but low-rate measurement. In particular, due to harsh environments (e.g., deep space habitats under meteoroids), structural impact localization must be robust to limited sensors (e.g., sensor damage during impacts) and multi-source errors (e.g., measurement errors). In this study, an effective impact detection and localization strategy is proposed using a limited number of vibration measurements, especially in harsh environments (e.g. in deep space). Convolutional neural networks are trained for each sensor node and are fused using Bayesian theory to improve the accuracy of impact localization. Special considerations are paid to evaluate the effect of both measurement error and modeling error in the analysis. The proposed strategy is illustrated using 1D structure, and further validated in 3D geodesic dome structure numerically. The results demonstrate that it can detect and localize impact events accurately and robustly on structures.

Yuguang Fu↗
NASA NTRS2020

Building a standardized Observing System Simulation Experiment (OSSE) framework for Mars

We advocate that the Decadal Survey recommends the NASA Science Mission Directorate to develop a rigorous Observing System Simulation Experiment (OSSE) framework for Mars, to optimize future atmospheric observations. Atmospheric conditions on Mars are a potential hazard source for landing missions. Errors in the estimates of atmospheric density profiles, inadequate knowledge of wind vertical structure and dust concentration as a function of height are likely causes of uncertainty at the landing site on the order of kilometers. An operational real-time weather forecasting capability for Mars would reduce such uncertainties, carrying enormous benefits to future robotic missions, and would be an invaluable prerequisite for human missions.A real-time forecasting capability relies upon three fundamental components: a critical mass of observing systems, a data assimilation system (DAS), and a global forecast model. The DAS allows the model to ingest the data effectively, optimizing the observational information content,and transforming them into a gridded representation of the atmosphere at a given time, called an ‘analysis’. The analysis is the best estimate of the atmospheric state for that time, and also represents a set of ‘initial conditions’ from which a global model can be initialized, to predict a future state of the atmosphere. The connection between analysis and forecast represents the foundation of modern weather forecasting. However, from the point of view of a forecast system,not all observations are equally impactful, partially because of the problem of “observational error correlation”, one important research topic in data assimilation development. For the Earth, partly due to the spontaneous and deregulated development of observations and forecast capabilities worldwide for more than half a century,the use of observations in contemporary operational forecast systems is suboptimal, with many potentially useful data being underutilized. On the contrary, Mars atmospheric scientists are in the unique situation of designing the next-generation observing systems by learning from the experience gathered on the Earth, so as to assure that the future instruments are specifically optimized to give the maximum benefit to a future weather forecast capability.An immensely powerful tool that has been firmly established by atmospheric scientists on the Earth is represented by a properly designed OSSE framework. A realistic OSSE framework cannot only quantify the benefit of future data types, be them surface based or space borne, but can also help design and optimize an entire observational network. Furthermore, OSSEs can provide deep insights into an atmosphere’s behavior, by addressing conceptual problems of its intrinsic predictability and delineating the regions or features of the atmosphere which are more sensitive to additional data and would benefit from a denser sampling. The difficulties posed by OSSEs are fundamentally different for Earth and Mars. For Earth, the enormous data volume imposes a tremendous constraint on any innovation in the observing systems: it is very hard for a single sensor to impact the skill. For Mars, the problem is the opposite: almost any additional instrument will exert some impact. However, OSSEs can help to evaluate the cost/benefit for every sensor and suggest optimal data configuration and density.The purpose of this white paper is to provide an introduction to a rigorously designed OSSE framework, explain the underlying problems and challenges, and engage the Mars community to collaborate with Earth Atmospheric scientists in order to develop a joint-OSSE framework for Mars with the largest consensual basis possible. An OSSE infrastructure would increase the understanding of the Martian atmosphere, would help NASA to optimize instrument specifications and orbit choice, providing the maximium benefit for a given expenditure of resources, and could even help establishing a roadmap for a future real-time weather forecasting capability.

Oreste Reale↗
NASA NTRS1989

An error-resistant linguistic protocol for air traffic control

The research results described here are intended to enhance the effectiveness of the DATALINK interface that is scheduled by the Federal Aviation Administration (FAA) to be deployed during the 1990's to improve the safety of various aspects of aviation. While voice has a natural appeal as the preferred means of communication both among humans themselves and between humans and machines as the form of communication that people find most convenient, the complexity and flexibility of natural language are problematic, because of the confusions and misunderstandings that can arise as a result of ambiguity, unclear reference, intonation peculiarities, implicit inference, and presupposition. The DATALINK interface will avoid many of these problems by replacing voice with vision and speech with written instructions. This report describes results achieved to date on an on-going research effort to refine the protocol of the DATALINK system so as to avoid many of the linguistic problems that still remain in the visual mode. In particular, a working prototype DATALINK simulator system has been developed consisting of an unambiguous, context-free grammar and parser, based on the current air-traffic-control language and incorporated into a visual display involving simulated touch-screen buttons and three levels of menu screens. The system is written in the C programming language and runs on the Macintosh II computer. After reviewing work already done on the project, new tasks for further development are described.

Cushing, Steven↗
DOE OSTI2021

Initialized Earth system prediction from subseasonal to decadal timescales

Initialized Earth system predictions are made by starting a numerical prediction model in a state as consistent as possible to observations, and running it forward in time for up to ten years. Skillful predictions at time slices from subseasonal to seasonal (S2S), seasonal to interannual (S2I) and seasonal to decadal (S2D) offer information useful for various stakeholders, from agriculture to water resource management, and human and infrastructure safety. In this Review, we examine the processes influencing predictability, and discuss estimates of skill across S2S, S2I and S2D timescales. There are encouraging signs that skillful predictions can be made: at S2S timescales, there has been some skill in predicting the Madden-Julian Oscillation and North Atlantic Oscillation; at S2I in predicting the El Niño-Southern Oscillation; and at S2D, in predicting variability in North Atlantic sea surface temperatures. However, challenges remain, and future work must prioritise reducing model error, more effectively communicating forecasts to users, and increasing process and mechanistic understanding that could increase predictive skill and, in turn, confidence. As numerical models progress towards Earth system models, initialized predictions are expanding to include prediction of sea-ice, air pollution, terrestrial and ocean biochemistry which can bring clear benefit to society and various stakeholders.

climate prediction↗
NASA NTRS2016

Cislunar Near Rectilinear Halo Orbit for Human Space Exploration

In order to conduct sustained human exploration beyond Low Earth Orbit (LEO), spacecraft systems are designed to operate in a series of missions of increasing complexity. Regardless of the destination, Moon, Mars, asteroids or beyond, there is a substantial set of common objectives that must be met. Many orbit characterization studies have endeavored to evaluate the potential locations in cislunar space that are favorable for meeting common human exploration objectives in a stepwise approach. Multiple studies, by both NASA and other international space agencies, have indicated that Earth-­‐moon libration point orbits are attractive candidates for staging operations in the proving ground and beyond. In particular, the Near Rectilinear Orbit (NRO) has been demonstrated to meet multi-­‐mission and multi-­‐destination architectural constraints. However, a human mission to a selected NRO presents a variety of new challenges for mission planning. While a growing number of robotic missions have completed successful operations to various specific libration point orbits, human missions have never been conducted to orbits of this class. Human missions have unique challenges that differ significantly from robotic missions, including a lower tolerance for mission risk and additional operational constraints that are associated only with human spacecraft. In addition, neither robotic nor human missions have been operated in the NRO regime specifically, and NROs exhibit dynamical characteristics that can differ significantly as compared to other halo orbits. Finally, multi-­‐body orbits, such as libration point orbits, are identified to exist in a simplified orbit model known as the Circular Restricted Three Body Problem (CRTBP) and must then be re-­‐solved in the full ephemeris model. As a result, the behavior of multi-­‐body orbits cannot be effectively characterized within the classical two-­‐body orbit dynamics framework more familiar to the human spaceflight community. In fact, a given NRO is not identified by a set of Keplerian orbit parameters, and a valid epoch specific state vector must be first obtained from a multi-body dynamical model. In this paper, the significant performance and operational challenges of conducting human missions to the NRO are evaluated. First, a systematic process for generating full ephemeris based ballistic NROs of various families is outlined to demonstrate the relative ease in which a multi-­‐revolution orbit can be found for any epoch and for various orbit geometries. In the Earth-­‐Moon system, NROs, which are halo orbits with close passage over a lunar pole, can exist with respect to libration point 1 (L1) or libration point 2 (L2) and are either from a North or South family orbit class with respect to the ecliptic. Second, the ability to maintain the orbit over the lifetime of a habitat mission by applying a reliable station-keeping strategy is investigated. The NRO, while similar to the quasi-­‐halo orbits that the Artemis mission flew, requires an updated station keeping strategy. This is due to several dynamical differences such as the increased relative stability of the NRO compared to other halo orbits and the close passage over the lunar surface as shown in Figure 1. Multiple station-keeping strategies are being investigated to ensure a human spacecraft remains on a predictable path. As the NRO is not described in simple two-­‐body parameters, analysis must determine the best strategy for targeting a reference NRO as well as how closely a future state should be constrained. In addition, costs will be minimized by determining maneuver directionality based on an identified pattern in the optimal station-keeping solutions or an analytically derived relationship. The candidate station-keeping algorithm must be stable and robust to environmental and vehicle uncertainties as well to navigation estimation and flight control execution errors. To that end, navigation accuracies, the impact on the station-keeping execution errors as well as other vehicle uncertainties need to be assessed. Starting with Orion, current navigation accuracies are evaluated and then navigation requirements are derived assuming a desired station-keeping propellant budget. Third, the performance requirements to and from the NRO are evaluated. Important parameters for developing expected propellant costs include epoch of operation, size and type of NRO, Earth departure and return constraints, as well as abort or early-­‐return capability. Finally, rendezvous and proximity operations are vital aspects of multi-­‐mission human exploration endeavors. The ability to conduct rendezvous and the associated propellant costs are assessed as well as the impacts of various profile assumptions including the location within the NRO the rendezvous is performed. The results of these studies will influence plans for international cooperation on both nearer term proving ground missions and beyond.

Whitley, Ryan↗
DOE OSTI2021

A synthetic RNA-mediated evolution system in yeast

Laboratory evolution is a powerful approach to search for genetic adaptations to new or improved phenotypes, yet either relies on labour-intensive human-guided iterative rounds of mutagenesis and selection, or prolonged adaptation regimes based on naturally evolving cell populations. Here we present CRISPR- and RNA-assisted in vivo directed evolution (CRAIDE) of genomic loci using evolving chimeric donor gRNAs continuously delivered from an error-prone T7 RNA polymerase, and directly introduced as RNA repair donors into genomic targets under either Cas9 or dCas9 guidance. We validate CRAIDE by evolving novel functional variants of an auxotrophic marker gene, and by conferring resistance to a toxic amino acid analogue in baker's yeast Saccharomyces cerevisiae with a mutation rate >3,000-fold higher compared to spontaneous native rate, thus enabling the first demonstrations of in vivo delivery and information transfer from long evolving RNA donor templates into genomic context without the use of in vitro supplied and pre-programmed repair donors.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1966

Short Period Fluctuations in Intelligence Final Report

The problem of isolating fluctuations in intellectual function is one that has long intrigued both psychologists and non-psychologists, We are all aware of our own short-period physiological, mood and motivational changes and many believe that their intelligence must undergo similar change. 1965 for a recent review) does not provide support for this kind of argu- ment. It indicates that measures of intelligence - -at least those intended for use with people other than infants --are usually highly stable over both short and rather extended periods of time: the changes which are indicated have almost always been regarded as errors of measurement. Thus in scientific developments (as opposed, perhaps, to common- sense discussions) ;intelligence usually has been regarded as a highly stable attribute of man. But existing scientific evidence (see Tyler, A notable exception to the scientific theory arguing (albeit im- plicitly) that human intellect does not fluctuate over short period of time is that of Moran (1961) and his co-workers (Moran, Kimble & Mefferd, 1960; 1964; Moran & Mefferd, 1959). The work of these in- vestigators has been directed at designing alternate -form tests to measure some of what are now regarded as the major, replicated-by- research dimensions of human intelligence, viz., what are known as the primary mental abilities (French, 1951: French, Ekstrom & Price, 1963; Guilford, 1966; Guilford & Merrifield, 1960). The Repetitive Psychological Measures (RPM) resulting from this work are intended to assess "change in performance with time" (Moran & Mefferd, 1959: p. 269). little has been done to determine whether or not the performances actually assessed do, in fact, change in a reliable manner. Indeed, evidence somewhat contrary to an hypothesis of short-period change is provided by the high (relative to test length) test-retest correlations ob- tained over a period of 3 hours with the RPM tests (Moran & Mefferd, 1959; Table 2). Hence, while a basic hypothesis underlying this work certainly does imply that abilities change over short periods, evidence for this hypothesis either has not been developed or, where it has (as in test-retest correlations), does not provide convincing support for the hypothesis

Intelligence↗
NASA NTRS1980

The relative importance of noise level and number of events on human reactions to noise: Community survey findings and study methods

The data from seven surveys of community response to environmental noise are reanalyzed to assess the relative influence of peak noise levels and the numbers of noise events on human response. The surveys do not agree on the value of the tradeoff between the effects of noise level and numbers of events. The value of the tradeoff cannot be confidently specified in any survey because the tradeoff estimate may have a large standard error of estimate and because the tradeoff estimate may be seriously biased by unknown noise measurement errors. Some evidence suggests a decrease in annoyance with very high numbers of noise events but this evidence is not strong enough to lead to the rejection of the conventionally accepted assumption that annoyance is related to a log transformation of the number of noise events.

Fields, J. M.↗
NASA NTRS1983

Comparison of simulator fidelity model predictions with in-simulator evaluation data

A full factorial in simulator experiment of a single axis, multiloop, compensatory pitch tracking task is described. The experiment was conducted to provide data to validate extensions to an analytic, closed loop model of a real time digital simulation facility. The results of the experiment encompassing various simulation fidelity factors, such as visual delay, digital integration algorithms, computer iteration rates, control loading bandwidths and proprioceptive cues, and g-seat kinesthetic cues, are compared with predictions obtained from the analytic model incorporating an optimal control model of the human pilot. The in-simulator results demonstrate more sensitivity to the g-seat and to the control loader conditions than were predicted by the model. However, the model predictions are generally upheld, although the predicted magnitudes of the states and of the error terms are sometimes off considerably. Of particular concern is the large sensitivity difference for one control loader condition, as well as the model/in-simulator mismatch in the magnitude of the plant states when the other states match.

Parrish, R. V.↗
NASA NTRS2013

Precise Truss Assembly using Commodity Parts and Low Precision Welding

We describe an Intelligent Precision Jigging Robot (IPJR), which allows high precision assembly of commodity parts with low-precision bonding. We present preliminary experiments in 2D that are motivated by the problem of assembling a space telescope optical bench on orbit using inexpensive, stock hardware and low-precision welding. An IPJR is a robot that acts as the precise "jigging", holding parts of a local assembly site in place while an external low precision assembly agent cuts and welds members. The prototype presented in this paper allows an assembly agent (in this case, a human using only low precision tools), to assemble a 2D truss made of wooden dowels to a precision on the order of millimeters over a span on the order of meters. We report the challenges of designing the IPJR hardware and software, analyze the error in assembly, document the test results over several experiments including a large-scale ring structure, and describe future work to implement the IPJR in 3D and with micron precision.

Komendera, Erik↗
NASA NTRSDate not supplied

Elevated CO2 Could Undermine an Exploration Crew's Ability to Independently Respond to Unanticipated, Time- and Safety-Critical Anomalies

Safety and mission critical anomalies are inevitable on NASA exploration missions. Delays and interruptions in communication with Earth-experts drives the requirement that crew resolve some time- and safety-critical anomalies on their own. The HRP, HFBP, Human-System Integration Architecture (HSIA) risk refers to the possibility that, during communication blackouts and thus the absence of vast ground expertise, a small crew may not be able to independently respond to unanticipated, time-critical malfunctions or to detect safety critical procedure errors.

carbon dioxide↗
DOE OSTI2022

Author Correction: Expanded encyclopaedias of DNA elements in the human and mouse genomes

In the version of this article initially published, two members of the ENCODE Project Consortium were missing from the author list. Rizi Ai (Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, USA) and Shantao Li (Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA) are now included in the author list. These errors have been corrected in the online version of the article.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Live cell imaging of cellular dynamics in poplar wood using computational cannula microscopy

This study presents significant advancements in computational cannula microscopy for live imaging of cellular dynamics in poplar wood tissues. Leveraging machine-learning models such as pix2pix for image reconstruction, we achieved high-resolution imaging with a field of view of 55µm using a 50µm-core diameter probe. Our method allows for real-time image reconstruction at 0.29 s per frame with a mean absolute error of 0.07. We successfully captured cellular-level dynamics in vivo , demonstrating morphological changes at resolutions as small as 3µm. We implemented two types of probabilistic neural network models to quantify confidence levels in the reconstructed images. This approach facilitates context-aware, human-in-the-loop analysis, which is crucial for in vivo imaging where ground-truth data is unavailable. Using this approach we demonstrated deep in vivo computational imaging of living plant tissue with high confidence (disagreement score ⪅0.2). This work addresses the challenges of imaging live plant tissues, offering a practical and minimally invasive tool for plant biologists.

Ingold, Alexander (ORCID:0009000752380016)↗