Cooperative Game Theory within Multi-Agent Systems for Systems Scheduling

Research concerning organization and coordination within multi-agent systems continues to draw from a variety of architectures and methodologies. The work presented in this paper combines techniques from game theory and multi-agent systems to produce self-organizing, polymorphic, lightweight, embedded agents for systems scheduling within a large-scale real-time systems environment. Results show how this approach is used to experimentally produce optimum real-time scheduling through the emergent behavior of thousands of agents. These results are obtained using a SWARM simulation of systems scheduling within a High Energy Physics experiment consisting of 2500 digital signal processors.Comment: Fourth International Conference on Hybrid Intelligent Systems (HIS), Kitakyushu, Japan, December, 200

Superfluidity of a perfect quantum crystal

In recent years, experimental data were published which point to the possibility of the existence of superfluidity in solid helium. To investigate this phenomenon theoretically we employ a hierarchy of equations for reduced density matrices which describes a quantum system that is in thermodynamic equilibrium below the Bose-Einstein condensation point, the hierarchy being obtained earlier by the author. It is shown that the hierarchy admits solutions relevant to a perfect crystal (immobile) in which there is a frictionless flow of atoms, which testifies to the possibility of superfluidity in ideal solids. The solutions are studied with the help of the bifurcation method and some their peculiarities are found out. Various physical aspects of the problem, among them experimental ones, are discussed as well.Comment: 24 pages with 2 figures, version accepted for publication in Eur.Phys.J.

Prototype of Fault Adaptive Embedded Software for Large-Scale Real-Time Systems

This paper describes a comprehensive prototype of large-scale fault adaptive embedded software developed for the proposed Fermilab BTeV high energy physics experiment. Lightweight self-optimizing agents embedded within Level 1 of the prototype are responsible for proactive and reactive monitoring and mitigation based on specified layers of competence. The agents are self-protecting, detecting cascading failures using a distributed approach. Adaptive, reconfigurable, and mobile objects for reliablility are designed to be self-configuring to adapt automatically to dynamically changing environments. These objects provide a self-healing layer with the ability to discover, diagnose, and react to discontinuities in real-time processing. A generic modeling environment was developed to facilitate design and implementation of hardware resource specifications, application data flow, and failure mitigation strategies. Level 1 of the planned BTeV trigger system alone will consist of 2500 DSPs, so the number of components and intractable fault scenarios involved make it impossible to design an `expert system' that applies traditional centralized mitigative strategies based on rules capturing every possible system state. Instead, a distributed reactive approach is implemented using the tools and methodologies developed by the Real-Time Embedded Systems group.Comment: 2nd Workshop on Engineering of Autonomic Systems (EASe), in the 12th Annual IEEE International Conference and Workshop on the Engineering of Computer Based Systems (ECBS), Washington, DC, April, 200

Prototype of Fault Adaptive Embedded Software for Large-Scale Real-Time Systems

This paper describes a comprehensive prototype of large-scale fault adaptive embedded software developed for the proposed Fermilab BTeV high energy physics experiment. Lightweight self-optimizing agents embedded within Level 1 of the prototype are responsible for proactive and reactive monitoring and mitigation based on specified layers of competence. The agents are self-protecting, detecting cascading failures using a distributed approach. Adaptive, reconfigurable, and mobile objects for reliability are designed to be self-configuring to adapt automatically to dynamically changing environments. These objects provide a self-healing layer with the ability to discover, diagnose, and react to discontinuities in real-time processing. A generic modeling environment was developed to facilitate design and implementation of hardware resource specifications, application data flow, and failure mitigation strategies. Level 1 of the planned BTeV trigger system alone will consist of 2500 DSPs, so the number of components and intractable fault scenarios involved make it impossible to design an “expert system” that applies traditional centralized mitigative strategies based on rules capturing every possible system state. Instead, a distributed reactive approach is implemented using the tools and methodologies developed by the RealTime Embedded Systems group

Cooperative Game Theory within Multi-Agent Systems for Systems

Research concerning organization and coordination within multi-agent systems continues to draw from a variety of architectures and methodologies. The work presented in this paper combines techniques from game theory and multi-agent systems to produce self-organizing, polymorphic, lightweight, embedded agents for systems scheduling within a large-scale real-time systems environment. Results show how this approach is used to experimentally produce optimum real-time scheduling through the emergent behavior of thousands of agents. These results are obtained using a SWARM simulation of systems scheduling within a High Energy Physics experiment consisting of 2500 digital signal processors

Farmers’ assessment of the use value of agrobiodiversity in complex cocoa agroforestry systems in central Cameroon

Agroforestry systems in humid tropical areas are complex multispecies cropping systems whose value for farmers is often hard to assess. We present the findings of a participatory assessment that we applied to cocoa agroforestry systems. This assessment, adapted from the pebble distribution method, was used to quantify the value given by farmers to each species of their cocoa agroforestry system according to the attributed uses. A tree inventory in 50 cocoa agroforests was carried out in central Cameroon. Overall, 122 non-cocoa tree species were inventoried. The mean species richness was 23 species per plot and the mean Shannon index was 2.42, for a mean density of 180 non-cocoa trees ha−1 and 1,511 cocoa trees ha−1. Cocoa farmers defined seven different uses for tree species, including Theobroma cacao. 81 % of the species (including cocoa trees) had one to seven uses whereas the highest use value was given to T. cacao, with a mean score of 23.6 %. Then, in descending order, the 10 non-cocoa species with the highest use values were Dacryodes edulis, Persea americana, Elaeis guineensis, Citrus sinensis, Mangifera indica, Milicia excelsa, Cola nitida, Citrus sp., Ricinodendron heudelotii, and Terminalia superba. The frequency of non-cocoa species was significantly and positively correlated with their use value (R2 = 0.914). Our results showed that technical innovations designed to improve cocoa agroforestry systems should take into account farmers’ knowledge to propose them systems so as to be able to more effectively address their expectations

Combining point correlation maps with self-organising maps to compare observed and simulated atmospheric teleconnection patterns

We use a new method based on point correlation maps and self-organising maps (SOMs) to identify teleconnection patterns in 60 yr of National Centres for Environmental Prediction/National Centre for Atmospheric Research (NCEP/NCAR) sea level pressure (SLP) re-analysis data. The most prevalent patterns are the El Nino Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO) and the Southern Annular Mode (SAM). Asymmetries are found between base points in opposite centres of action of the NAO and the Pacific North America pattern (PNA). The SOM-based method is a powerful tool that allows us to efficiently assess how realistically teleconnections are reproduced in any climate model. The degree of agreement between modelled and re-analysis-based teleconnections (or between different models) can be summarised in a single plot. Here, we illustrate this by assessing the skill of the medium complexity climate model FORTE (Fast Ocean Rapid Troposphere Experiment). FORTE reproduces some realistic teleconnections, such as the Arctic Oscillation (AO), the NAO, the PNA, the SAM, the African Monsoon and ENSO, along with several other teleconnections, which resemble to varying degrees the corresponding NCEP patterns. However, FORTE tends to underestimate the strength of the correlation patterns and the patterns tend to be slightly too zonal. The accuracy of frequency of occurrence is variable between patterns. The Indian Ocean is a region where FORTE performs poorly, as it does not reproduce the teleconnection patterns linked to the Indian Monsoon. In contrast, the North and equatorial Pacific and North Atlantic are reasonably well reproduced

Satellite remote sensing and the Marine Biodiversity Observation Network: current science and future steps

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Kavanaugh, M. T., Bell, T., Catlett, D. C., Cimino, M. A., Doney, S. C., Klajbor, W., Messie, M., Montes, E., Muller-Karger, F. E., Otis, D., Santora, J. A., Schroeder, I. D., Trinanes, J., & Siegel, D. A. Satellite remote sensing and the Marine Biodiversity Observation Network: current science and future steps. Oceanography, 34(2), (2021): 62–79, https://doi.org/10.5670/oceanog.2021.215.Coastal ecosystems are rapidly changing due to human-caused global warming, rising sea level, changing circulation patterns, sea ice loss, and acidification that in turn alter the productivity and composition of marine biological communities. In addition, regional pressures associated with growing human populations and economies result in changes in infrastructure, land use, and other development; greater extraction of fisheries and other natural resources; alteration of benthic seascapes; increased pollution; and eutrophication. Understanding biodiversity is fundamental to assessing and managing human activities that sustain ecosystem health and services and mitigate humankind’s indiscretions. Remote-sensing observations provide rapid and synoptic data for assessing biophysical interactions at multiple spatial and temporal scales and thus are useful for monitoring biodiversity in critical coastal zones. However, many challenges remain because of complex bio-optical signals, poor signal retrieval, and suboptimal algorithms. Here, we highlight four approaches in remote sensing that complement the Marine Biodiversity Observation Network (MBON). MBON observations help quantify plankton community composition, foundation species, and unique species habitat relationships, as well as inform species distribution models. In concert with in situ observations across multiple platforms, these efforts contribute to monitoring biodiversity changes in complex coastal regions by providing oceanographic context, contributing to algorithm and indicator development, and creating linkages between long-term ecological studies, the next generations of satellite sensors, and marine ecosystem management.The authors would like to acknowledge the support of the Marine Biodiversity Observation Network (MBON), through National Aeronautics and Space Administration (NASA) awards NNX14AP62A, 80NSSC20K0017MK, NNX14AR62AFMK, 80NSSC20M0001, and 80NSSC20M008; and National Oceanic and Atmospheric Administration (NOAA) Integrated Ocean Observing System grant NA19NOS0120199. In addition, the work was supported by the Group on Earth Observations NASA awards 80NSSC18K0318 to EM and 80NSSC18K0412 to MK. FMK acknowledges the US National Science Foundation (NSF) grant 2500-1710-00 to the OceanObs Research Coordination Network, and the Gulf of Mexico Coastal Ocean Observing System NOAA Cooperative Agreement NA16NOS0120018. MM and JS were also supported by the NASA Life in Moving Oceans award 80NSSC17K0574. DS, TB, and DC acknowledge Plumes and Blumes NASA award 80NSSC18K0735, the Bureau of Ocean and Energy Management Ecosystem Studies program award MC15AC00006, NASA PACE Science Team award 80NSSC20M0226, and NSF Santa Barbara Coastal Long Term Ecological Research site award OCE-1831937

Boundary influences on HAB phytoplankton ecology in a stratification-enhanced upwelling shadow

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