This study introduces AutoCLC, an AI-powered system designed to assess and provide feedback on Closed-Loop Communication (CLC) in professional learning environments. CLC, where a sender’s Call-Out statement is acknowledged by the receiver’s Check-Back statement, is a critical safety protocol in high-reliability domains, including emergency medicine resuscitation teams. Existing methods for evaluating CLC lack quantifiable metrics and depend heavily on human observation. AutoCLC addresses these limitations by leveraging natural language processing and large language models to analyze audio recordings from Advanced Cardiovascular Life Support (ACLS) simulation training. The system identifies CLC instances, measures their frequency and rate per minute, and categorizes communications as effective, incomplete, or missed. Technical evaluations demonstrate that AutoCLC achieves 78.9% precision for identifying Call-Outs and 74.3% for Check-Backs, with a performance gap of only 5% compared to human annotations. A user study involving 11 cardiac arrest instructors across three training sites supported the need for automated CLC assessment. Instructors found AutoCLC reports valuable for quantifying CLC frequency and quality, as well as for providing actionable, example-based feedback. Participants rated AutoCLC highly, with a System Usability Scale score of 76.4%, reflecting above-average usability. This work represents a significant step toward developing scalable, data-driven feedback systems that enhance individual skills and team performance in high-reliability settings.

Estimators motivated by the minimum mean square error estimation criterion are presented for the estimation of the optical signal intensity in free space optical communication systems impaired by atmospheric-induced scintillation. Joint parameter estimators for the estimation of signal intensities across a photodetector array are investigated. Three scenarios are considered. First, it is assumed that the received signal is detected by using a p-i-n photodiode array and that the receiver operates under a shot-noise-limited condition. In the second scenario, the received signal is detected by using an avalanche photodiode (APD) array and the receiver operates under a shot-noise-limited condition. In the third scenario, the received signal is detected by using an APD array, but the receiver is impaired by thermal noise as well as shot noise. The mean primary electron count received by the APD is assumed to be large enough to justify the Gaussian approximation. The optical channel is modeled using a lognormal distribution with correlated random signal intensities across the array. With the aid of simulation, it is shown that the proposed estimators outperform maximum likelihood estimators for small scintillation indices while providing a performance similar to the maximuma posterioriestimator.

Estimators motivated by the minimum mean-square estimation (MMSE) criterion are presented for the estimation of the optical signal intensity in free-space optical (FSO) communication systems impaired by atmospheric-induced scintillation. Joint parameter estimators for the estimation of signal intensities across a photodetector array are investigated. Three scenarios are considered. First, it is assumed that the received signal is detected using a p-i-n photodiode array and that the receiver operates under a shot-noise-limited condition. In the second scenario, the received signal is detected using an APD array and the receiver operates under a shot-noise-limited condition. In the third scenario, the received signal is detected using an APD array, but the receiver is impaired by thermal noise as well as shot noise. The mean primary electron count received by the APD is assumed to be large enough to justify the Gaussian approximation. The optical channel is modeled using a log-normal distribution with correlated random signal intensities across the array. With the aid of simulation, it is shown that the proposed estimators outperform the maximum-likelihood estimators for small scintillation indices while providing a performance similar to the maximum a posteriori estimator.

The channel estimation problem is addressed for freespace optical communications impaired by optical turbulence. Estimators which are motivated by the minimum mean square error (MMSE) estimation criterion are proposed for the estimation of optical signal intensity in p-i-n and APD-based freespace optical (FSO) communication systems. A shot noise limited condition is assumed. The received signal intensity is modelled using a log-normal (LN) probability density function (pdf) for low (<0.75) scintillation indices and a negative exponential pdf for scintillation indices in the vicinity of 1. When considering APD-based receivers, only the low scintillation scenario is considered. With the aid of simulation, it is shown that the proposed estimators outperform maximum likelihood (ML) estimators for small scintillation indices.