1,723,751 research outputs found
Some Computational Aspects of Gaussian CARMA Modelling
Get PDFRepresentation of continuous-time ARMA, CARMA, models is reviewed. Computational aspects of simulating and calculating the likelihood-function of CARMA are summarized. Some numerical properties are illustrated by simulations. Some real data applications are shown.CARMA, maximum-likelihood, spectrum, Kalman filter, computation
MieeYang/CARMA-1Dexoplanet: CARMA-1Dexoplanet
No full text<p>Baseline experiment for running 1-D CARMA; A template for exoplanet cloud microphysics simulations.</p>
MieeYang/CARMA-1D: CARMA-1Dexoplanet
No full textA baseline experiment for 1-D CARMA cloud microphysics model, especially to study exoplanets with different parameters
Carma Stewart
No full textCarma Stewart is the daughter of Erma and Percy Stewart. Photo can be found on page 413 of the Jensen Utah Book
1D CARMA template for Exoplanets
No full text<p>This repository is for running the baseline case of 1D cloud microphysical experiment with CARMA. It also works as a template for running experiments for exoplanets with different planetary parameters. </p>
<p>The folder "source" is a standard version of CARMA files, which is well documented in https://wiki.ucar.edu/display/CARMA/CARMA+Home. The folder "test" includes files to edit in order to tune planetary parameters. Details are described in the README file.</p>
<p>This is a Fortran package working requiring an ifort & intel-mpi envrionment.</p>
p-CARMA: Politely Scaling LoRaWAN
No full textLong Range Wide Area Network (LoRaWAN) covers the needs of energy-constrained IoT-devices for operational longevity and extended communication range in a best-effort fashion. However, Lo- RaWAN’s minimalist design cannot handle the traffic from dense deployments with more than a few hundred devices connected to a single gateway, since each LoRa-device transmits data-packets without any information regarding the availability of the medium. In this paper, we try to improve the scalability of LoRaWAN by manifolds, serving thousands of devices per gateway. We present a novel protocol called p persistent-Channel Activity Recognition Multiple Access (p-CARMA) that exploits LoRaWAN’s Channel Activity Detection (CAD) as a crude mechanism to assess if the channel is free. Due to CAD’s imperfections (it only scans for preambles, not for any channel activity) p-CARMA operates probabilistically with each device deciding on a p value based upon local estimation. At the beginning of operation, this estimate is derived from pure local information, that is without involvement of the gateway, and devices automatically adapt to changes in the environment. Then, the adaptation of p-value is assisted by critical information on the cumulative device-delays, multicasted by the gateway at regular, large timespans. To evaluate the performance of p-CARMA, we implemented it in ns-3 based upon a detailed characterization of LoRaWAN’s CAD mechanism involving an extensive set of real-world experiments. We compared p-CARMA to vanilla LoRaWAN as well as a variant using the theoretically optimal p = 1=N (N being the total number of devices). The simulation results show that p-CARMA achieves from three-fold, up to a twenty-fold higher Packet Reception Ratio than LoRaWAN while handling thousands of devices. Further, its adaptivity outperforms the fixed p-value by a factor of 5.25 when scaling up. Moreover, p-CARMA does so while consuming 37.31%-58.17% less energy on average per device compared to vanilla LoRaWAN.Embedded SystemsElectrical Engineering, Mathematics and Computer Scienc
fvitt/CAM: CARMA sectional aerosol microphysical model in CESM2
No full textCARMA sectional aerosol microphysical model in CESM
Community Aerosol and Radiation Model for Atmospheres (CARMA) standalone 4.11 code
No full textCARMA is a general-purpose sectional microphysics code that has been used to study a wide variety of aerosols in planetary atmospheres. It originated from a one-dimensional stratospheric aerosol code developed by Turco et al. (1979) and Toon et al. (1979) that included both gas-phase sulfur chemistry and aerosol microphysics. The model was improved and extended to three dimensions as described by Toon et al. (1988). CARMA has been applied to almost every cloud and aerosol on Earth, as well as those on Venus, Mars, Titan, and exoplanets. This is the standalone CARMA version 4.11. To get the latest code, please download from https://github.com/ESCOMP/CARMA_base. </p
CARMA-F
No full textCARMA-F (CARibbean MAngroves-Fossil) is a dataset that gathers the published fossil pollen records of mangrove taxa from the Caribbean region. The latest update includes nearly 90 localities ranging from the Late Cretaceous to the Pliocene. This dataset has been compiled to facilitate the study of the origin, evolution and diversification of Caribbean mangroves, along with the main environmental drivers involved. The data contained in CARMA-F have been used in a collection of papers by the author organized chronologically that discuss the Eocene origin, the Eocene/Oligocene evolutionary turnover and the Neogene diversification of these iconic tropical/subtropical coastal ecosystems, as occurrent in the Neotropical Caribbean region. CARMA-F is provided as a spreadsheet and is open to modifications to adapt it to the particular interests of each researcher. A detailed description of the dataset in available as a preprint (https://doi.org/10.20944/preprints202310.2106.v1) and will be published soon in the journal Plants. The dataset remains open to further updates, as new data are published/retrieved.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV
CARMA-F
No full textCARMA-F (CARibbean MAngroves-Fossil) is a dataset that gathers the published fossil pollen records of mangrove taxa from the Caribbean region. The latest update includes nearly 90 localities ranging from the Late Cretaceous to the Pliocene. This dataset has been compiled to facilitate the study of the origin, evolution and diversification of Caribbean mangroves, along with the main environmental drivers involved. The data contained in CARMA-F have been used in a collection of papers by the author organized chronologically that discuss the Eocene origin, the Eocene/Oligocene evolutionary turnover and the Neogene diversification of these iconic tropical/subtropical coastal ecosystems, as occurrent in the Neotropical Caribbean region. CARMA-F is provided as a spreadsheet and is open to modifications to adapt it to the particular interests of each researcher. A detailed description of the dataset in available as a preprint (https://doi.org/10.20944/preprints202310.2106.v1) and will be published soon in the journal Plants. The dataset remains open to further updates, as new data are published/retrieved.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV
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