Multi Agent System for Machine Learning Under Uncertainty in Cyber Physical Manufacturing System

Recent advancement in predictive machine learning has led to its application in various use cases in manufacturing. Most research focused on maximising predictive accuracy without addressing the uncertainty associated with it. While accuracy is important, focusing primarily on it poses an overfitting danger, exposing manufacturers to risk, ultimately hindering the adoption of these techniques. In this paper, we determine the sources of uncertainty in machine learning and establish the success criteria of a machine learning system to function well under uncertainty in a cyber-physical manufacturing system (CPMS) scenario. Then, we propose a multi-agent system architecture which leverages probabilistic machine learning as a means of achieving such criteria. We propose possible scenarios for which our architecture is useful and discuss future work. Experimentally, we implement Bayesian Neural Networks for multi-tasks classification on a public dataset for the real-time condition monitoring of a hydraulic system and demonstrate the usefulness of the system by evaluating the probability of a prediction being accurate given its uncertainty. We deploy these models using our proposed agent-based framework and integrate web visualisation to demonstrate its real-time feasibility

Convective storms in closed cyclones in Jupiter's South Temperate Belt: (I) observations

On May 31, 2020 a short-lived convective storm appeared in one of the small cyclones of Jupiter's South Temperate Belt (STB) at planetographic latitude 30.8S. The outbreak was captured by amateur astronomer Clyde Foster in methane-band images, became widely known as Clyde's Spot, and was imaged at very high resolution by the Junocam instrument on board the Juno mission 2.5 days later. Junocam images showed a white two-lobed cyclonic system with high clouds observed in the methane-band at 890 nm. The storm evolved over a few days to become a dark feature that showed turbulence for months, presented oscillations in its drift rate, and slowly expanded, first into a Folded Filamentary Region (FFR), and later into a turbulent segment of the STB over a timescale of one year. On August 7, 2021, a new storm strikingly similar to Clyde's Spot erupted in a cyclone of the STB. The new storm exhibited first a similar transformation into a turbulent dark feature, and later transformed into a dark cyclone fully formed by January 2022. We compare the evolution into a FFR of Clyde's Spot with the formation of a FFR observed by Voyager 2 in 1979 in the South South Temperate Belt (SSTB) after a convective outburst in a cyclone that also developed a two-lobed shape. We also discuss the contemporaneous evolution of an additional cyclone of the STB, which was similar to the one were Clyde's Spot developed. This cyclone did not exhibit visible internal convective activity, and transformed from pale white in 2019, with low contrast with the environment, to dark red in 2020, and thus, was very similar to the outcome of the second storm. This cyclone became bright again in 2021 after interacting with Oval BA. We present observations of these phenomena obtained by amateur astronomers, ground-based telescopes, Hubble Space Telescope and Junocam. This study reveals that short-lived small storms that are active for only a few days can produce complex longterm changes that extend over much larger areas than those initially covered by the storms. In a second paper [In tilde urrigarro et al., 2022] we use the EPIC numerical model to simulate these storms and study moist convection in closed cyclones.We are very thankful to the large community of amateur observers operating small telescopes that submit their Jupiter observations to databases such as PVOL and ALPO-Japan. We are also grateful to two anonymous reviewers for their comments that improved the clarity of this paper. This work has been supported by Grant PID2019-109467GB-I00 funded by MCIN/AEI/10.13039/501100011033/and by Grupos Gobierno Vasco IT1366-19. PI acknowledges a PhD scholarship from Gobierno Vasco. GSO and TM were supported by NASA with funds distributed to the Jet Propulsion Laboratory, California Institute of Technology under contract 80NM0018D0004. C. J. Hansen was sup-ported by funds from NASA, USA to the Juno mission via the Planetary Science Institute. IOE was supported by a contract funded by Europlanet 2024 RI to navigate Junocam images, now available as maps in PVOL at http://pvol2.ehu.eus. Europlanet 2024 RI has received funding from the European Unions Horizon 2020 research and innovation programme under grant agreement No 871149. G.S. Orton, S. R. Brueshaber, T. W. Momary, K. H. Baines and E. K. Dahl were visiting Astronomers at the Infrared Telescope Facility, which is operated by the University of Hawaii under contract 80HQTR19D0030 with the National Aeronautics and Space Administration. In addition, support from NASA Juno Participating Scientist award 80NSSC19K1265 was provided to M.H. Wong. This work has used data acquired from the NASA/ESA Hubble Space Telescope (HST) , which is operated by the Association of 807 Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These HST observations are associated with several HST observing programs: GO/DD 14661 (PI: M.H. Wong) , GO/DD 15665 (PI: I. de Pater) , GO/DD 15159 (PI: M. H. Wong) , GO/DD 15502 (PI: A. Simon) , GO/DD 14661 (PI: M. H. Wong) , GO/DD 16074 (PI: M.H. Wong) , GO/DD 16053 (PI: I. de Pater) , GO/DD 15929 (PI: A. Simon) , GO/DD 16269 (PI: A. Simon) . PlanetCam observations were collected at the Centro Astronomico Hispanico en Andalucia (CAHA) , operated jointly by the Instituto de Astrofisica de Andalucia (CSIC) and the Andalusian Universities (Junta de Andalucia) . This work was enabled by the location of the IRTF and Gemini North telescopes within the Mauakea Science Reserve, adjacent to the summit of Maunakea. We are grateful for the privilege of observing Kaawela (Jupiter) from a place that is unique in both its astronomical quality and its cultural signifi-cance. This research has made use of the USGS Integrated Software for Imagers and Spectrometers (ISIS) . Voyager 2 images were accessed through The PDS Ring-Moon Systems Nodes OPUS search service

Mathematical modelling to support traceable dynamic calibration of pressure sensors

This paper focuses on the mathematical modelling required to support the development of new primary standard systems for traceable calibration of dynamic pressure sensors. We address two fundamentally different approaches to realizing primary standards, specifically the shock tube method and the drop-weight method. Focusing on the shock tube method, the paper presents first results of system identification and discusses future experimental work that is required to improve the mathematical and statistical models. We use simulations to identify differences between the shock tube and drop-weight methods, to investigate sources of uncertainty in the system identification process and to assist experimentalists in designing the required measuring systems. We demonstrate the identification method on experimental results and draw conclusions

Landscape structure influences the use of social information in an insectivorous bat

In anthropogenic landscapes, aerial insectivores are often confronted with variable habitat complexity, which may influence the distribution of prey. Yet, high mobility may allow aerial insectivores to adjust their foraging strategy to different prey distributions. We investigated whether aerial-hunting common noctules Nyctalus noctula adjust their foraging strategy to landscapes with different habitat complexity and assumingly different prey distribution. We hypothesized that the movement behaviour of hunting common noctules and changes of movement behaviour in reaction towards conspecifics would depend on whether they hunt in a structurally poor cropland dominated landscape or a structurally rich forest dominated landscape. We tracked flight paths of common noctules in northeastern Germany using GPS loggers equipped with an ultrasonic microphone that recorded foraging events and presence of conspecifics. Above cropland, common noctules hunted mainly during bouts of highly tortuous and area restricted movements (ARM). Bats switched from straight flight to ARM after encountering conspecifics. In the forested landscape, common noctules hunted both during ARM and during straight flights. The onset of ARM did not correlate with the presence of conspecifics. Common noctules showed a lower feeding rate and encountered more conspecifics above the forested than above the cropland dominated landscape. We conjecture that prey distribution above cropland was patchy and unpredictable, thus making eavesdropping on hunting conspecifics crucial for bats during search for prey patches. In contrast, small scale structural diversity of the forested landscape possibly led to a more homogeneous prey distribution at the landscape scale, thus enabling bats to find sufficient food independent of conspecific presence. This suggests that predators depending on ephemeral prey can increase their foraging success in structurally poor landscapes by using social information provided by conspecifics. Hence, a minimum population density might be obligatory to enable successful foraging in simplified landscapes