Point distribution. by Jiang Li (272926)

Mean ± SD values of unipedal stance parameters evaluated at the different time points of the postural training session. by Cristina Dolciotti (16317330)

RTs (in ms, bars) and ACC (in%, line) across time points, with 95% confidence interval. by Marcel F. Hinss (14675457)

The Samn-Perelli Scale is a 7-point Likert scale used to assess fatigue [42, 45]. by Marcel F. Hinss (14675457)

This decision-making and root cause analysis demonstration employs decision mining with machine learning and Petri Net, for example, in the manuscript, featuring annotated decision... by Mohammad Bakhtiari (11838264)

The 5-point summary of CPM dataset. by Gaurav Sandeep Dave (21519884)

The Karolinska Sleepiness Scale (KSS) is a 9-point Likert scale, ranging from “extremely 1 = alert” to “9 = extremely sleepy–fighting sleep” [44]. by Marcel F. Hinss (14675457)

Comparison of environmental perception time results at different learning rates. by Wenhui Wang (34265)

AI KRegression by CHIN-CHENG CHU (20718575)

The shortened version of the Edinburgh Handedness Inventory encompasses 4 items (e.g. writing) scored on a 5-point scale ranging from:” Always right; usually right; both equally; u... by Marcel F. Hinss (14675457)

<b>Ensemble learning model identifies </b><b>adaptation classification and turning points</b><b> of river microbial communities in response to heatwaves</b> by Qian Qu (14198684)

Comparison of Mean Absolute Error (MAE) in Millimeters as a Function of Kernel Size. by Liu Liu (512237)

Deep reinforcement learning agents trained using a curriculum solve navigation tasks with delayed rewards. by William L. Tong (22238845)

Deep learning-based locomotive syndrome prediction method. by Junichi Kushioka (12236447)

A novel RNN architecture to improve the precision of ship trajectory predictions by Martha Dais Ferreira (18704596)

“…To solve these challenges, Recurrent Neural Network (RNN) models have been applied to STP to allow scalability for large data sets and to capture larger regions or anomalous vessels behavior. This research proposes a new RNN architecture that decreases the prediction error up to 50% for cargo vessels when compared to the OU model. …”

Regression analyses of the number of all ultrasonic calls identified by the experienced researcher (A.P.; “Human”) and by the DeepSqueak machine learning tool. by Piotr Popik (292215)

Participants demographics at baseline. by Dawn M. Sears (4807302)

Subjects:

Flowchart of responses- Baseline Survey from 2018- to all employed and affiliated physicians and APPs. by Dawn M. Sears (4807302)

Subjects:

Burnout, Leadership aspiration and organizational retention at follow up vs. baseline. by Dawn M. Sears (4807302)

Subjects:

Flowchart of responses- Follow up survey from 2020 connected to Employee Engagement system wide survey and went to all “Senior leaders” instead of only physicians and clinicians.... by Dawn M. Sears (4807302)

Subjects: