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  • Rural Digital Europe
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/

    Report on dissemination activities at workshops organised outside the project.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Patel, Pankesh; Pathak, Animesh; Teixeira, Thiago; Issarny, Valérie;

    ISBN: 978-1-4503-1072-7; International audience; The Internet of Things (IoT) integrates the physical world with the existing Internet, and is rapidly gaining popularity, thanks to the increased adoption of smart phones and sensing devices. One of the important challenges in this domain is to enable domain experts to easily specify applications for the IoT. As a first step towards developing a suitable programming abstraction, in this paper we present a domain model for applications in the Internet of Things, based on a survey of recently proposed IoT applications from the real world that represent a wide class of behaviors found in IoT use cases.

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    https://hal.inria.fr/hal-00711...
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    https://doi.org/10.1145/209319...
    Conference object . 2011 . Peer-reviewed
    Data sources: Crossref
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Bettge, Anika; Roscher, Ribana; Wenzel, Susanne;

    This paper addresses the land cover classification task for remote sensing images by deep self-taught learning. Our self-taught learning approach learns suitable feature representations of the input data using sparse representation and undercomplete dictionary learning. We propose a deep learning framework which extracts representations in multiple layers and use the output of the deepest layer as input to a classification algorithm. We evaluate our approach using a multispectral Landsat 5 TM image of a study area in the North of Novo Progresso (South America) and the Zurich Summer Data Set provided by the University of Zurich. Experiments indicate that features learned by a deep self-taught learning framework can be used for classification and improve the results compared to classification results using the original feature representation. Comment: This is a corrected version of the final paper published in the proceedings

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ arXiv.org e-Print Ar...arrow_drop_down
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    https://doi.org/10.48550/arxiv...
    Article . 2017
    License: arXiv Non-Exclusive Distribution
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ arXiv.org e-Print Ar...arrow_drop_down
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      https://doi.org/10.48550/arxiv...
      Article . 2017
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Aiello, Orazio; Crovetti, Paolo; Alioto, Massimo;

    In this paper, two circuit topologies of pW-power Hz-range wake-up oscillators for sensor node applications are presented. The proposed circuits are based on standard cells utilizing the Dynamic Leakage Suppression logic style [4]–[5]. The proposed oscillators exhibit low supply voltage sensitivity over a wide supply voltage range, from nominal voltage down to the deep sub-threshold region (i.e., 0.3 V). This enables direct powering from energy harvesters or batteries through their whole discharge cycle, suppressing the need for voltage regulation. Post-layout time-domain simulations of the proposed oscillators in 180nm show a power consumption of 1.4–1.7pW, a supply-sensitivity of 55–40%/V over the 0.3V–1.8V supply voltage range, and a compact area down to 1,500µm2. The very low power consumption makes the proposed circuits very well suited for energy-harvested systems-on-chip for Internet of Things applications.

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    https://doi.org/10.1109/iscas....
    Conference object . 2019 . Peer-reviewed
    License: IEEE Copyright
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    https://doi.org/10.1109/ISCAS....
    Other literature type . Conference object . 2019
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Publications Open Re...arrow_drop_down
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      https://doi.org/10.1109/iscas....
      Conference object . 2019 . Peer-reviewed
      License: IEEE Copyright
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      https://doi.org/10.1109/ISCAS....
      Other literature type . Conference object . 2019
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  • Authors: Christine Poncet; Cécile Bresch; Hicham Fatnassi; Ludovic Mailleret; +6 Authors

    International audience; Protected cultivation or Controlled Environment Agriculture (CEA) system has increased tenfold in the last 25 years thanks to tremendous scientific and technical breakthroughs, mainly directed to increasing crop yields and adapting to tough ambient conditions. Currently, greenhouse areas are still spreading and the CEA system is one of the keystones for the agriculture forecasting scenario. However, the environmental acceptability of this very intensive agro-ecosystem is now being questioned. Energy inputs are source of the main economic and environmental weakness, especially for high-tech greenhouses, where IPM is well-established. Pesticides, common in low-cost greenhouses systems, are a major barrier-to IPM. To design and manage more robust CEA systems, both technological and ecological approaches have been chosen. This allowed for increased consideration of IPM issues among global greenhouse engineering innovation and better use of greenhouse system capacities to enhance dedicated IPM high-tech tools and management practices. On the other hand, ecological concepts were used to determine and characterize complex biotic interactions that lead to question the tenant of biological control as soon as IPM is implemented in greenhouses with sub-optimum physical pest control means. More specifically, microclimate at the boundary layer level has been investigated both from a physical and biological point of view in order to determine the best climate preferences of the main pests and beneficials. By the same token, the efficiency of diverse biocontrol plants to provide accurate shelter to natural enemies has been assessed

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Henry C. Bittig; Arne Körtzinger;

    Abstract. Oxygen optode measurements on floats and gliders suffer from a slow time response and sensors that are or eventually run out of calibration. Based on two dual-O2 Argo floats, we show how to post-correct for the effect of the optode’s time response and give an update on optode in-situ drift stability and in-air calibration. Both floats are equipped with an unpumped Aanderaa 4330 optode and a pumped Sea-Bird SBE63 optode. Response times for the pumped SBE63 were derived after Bittig et al. (2014). Also their methods were used to correct the time response bias. Using both optodes on each float, the time response regime of the unpumped Aanderaa optode was characterized more accurately than previously possible. Response times for the pumped SBE63 are in the range of 25–40 s, while they are between 60–95 s for the unpumped 4330 optode. Our parameterization can be employed to post-correct the slow optode time response on floats and gliders. After correction, both sensors agree to within 2–3 μmol kg−1 (median difference) in the strongest gradients (120 μmol kg−1 change over 8 minutes or 20 dbar) and better elsewhere. However, time response correction is only possible if measurement times are known, i.e., provided by the platform as well as transmitted and stored with the data. The O2 in-air measurements show a significant in-situ optode drift of −0.4 % yr−1 and −0.2 % yr−1, respectively. Optode in-air measurements are systematically biased high during mid-day surfacings compared to dusk, dawn, and nighttime. While preference can be given to nighttime surfacings to avoid this in-air calibration bias, we suggest a parameterization of the daytime effect as function of the sun’s elevation to be able to use all data and to better constrain the result. Taking all effects into account, calibration factors have an uncertainty of 0.1 %. In addition, in-air calibration factors vary by 0.1–0.2 % when using different reanalysis models as reference. The overall accuracy that can be achieved following the proposed correction routines is <1 μmol kg−1.

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    https://doi.org/10.5194/os-201...
    Preprint . 2016 . Peer-reviewed
    License: CC BY
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    https://www.ocean-sci.net/13/1...
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      https://doi.org/10.5194/os-201...
      Preprint . 2016 . Peer-reviewed
      License: CC BY
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      https://www.ocean-sci.net/13/1...
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Gutiérrez, Salvador; Diago, María P.; Fernández-Novales, Juan; Tardaguila, Javier;

    The high impact of irrigation in crop quality and yield in grapevine makes the development of plant water status monitoring systems an essential issue in the context of sustainable viticulture. This study presents an on-the-go approach for the estimation of vineyard water status using thermal imaging and machine learning. The experiments were conducted during seven different weeks from July to September in season 2016. A thermal camera was embedded on an all-terrain vehicle moving at 5 km/h to take on-the-go thermal images of the vineyard canopy at 1.2 m of distance and 1.0 m from the ground. The two sides of the canopy were measured for the development of side-specific and global models. Stem water potential was acquired and used as reference method. Additionally, reference temperatures T and T were determined for the calculation of two thermal indices: the crop water stress index (CWSI) and the Jones index (I). Prediction models were built with and without considering the reference temperatures as input of the training algorithms. When using the reference temperatures, the best models casted determination coefficients R of 0.61 and 0.58 for cross validation and prediction (RMSE values of 0.190 MPa and 0.204 MPa), respectively. Nevertheless, when the reference temperatures were not considered in the training of the models, their performance statistics responded in the same way, returning R values up to 0.62 and 0.65 for cross validation and prediction (RMSE values of 0.190 MPa and 0.184 MPa), respectively. The outcomes provided by the machine learning algorithms support the use of thermal imaging for fast, reliable estimation of a vineyard water status, even suppressing the necessity of supervised acquisition of reference temperatures. The new developed on-the-go method can be very useful in the grape and wine industry for assessing and mapping vineyard water status. This work is part of the RESOLVE project, for which the authors acknowledge the financial support provided by transnational funding bodies, being partners of the FP7 ERA-net project, CORE Organic Plus, and the cofund from the European Commission. Salvador Gutierrrez would like to acknowledge the research founding FPI grant 299/2016 by Universidad de La Rioja, Gobierno de La Rioja. Dr. Maria P. Diago is funded by the Spanish Ministry of Economy, Industry and Competitiveness (MINECO) with a Ramon y Cajal grant RYC-2015-18429. Peer reviewed

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    Europe PubMed Central
    Article . 2018
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    Article . 2018
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    Article . 2018
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    PLoS ONE
    Article . 2018 . Peer-reviewed
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      PLoS ONE
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Camille Abadie; Fabienne Maignan; Marine Remaud; Kukka-Maaria Kohonen; +8 Authors

    Gross primary production (GPP) by boreal forests is highly sensitive to environmental changes. However, GPP simulated by land surface models (LSMs) remains highly uncertain due to the lack of direct photosynthesis observations at large scales. Carbonyl sulfide (COS) has emerged as a promising proxy to improve the representation of GPP in LSMs. Because COS is absorbed by vegetation following the same diffusion pathway as CO2 during photosynthesis and not emitted back to the atmosphere, incorporating a mechanistic representation of vegetation COS uptake in LSMs allows using COS observations to refine GPP representation. Here, we perform ecosystem COS flux and GPP data assimilations to constrain the COS- and GPP-related parameters in the ORCHIDEE LSM for boreal evergreen needleleaf forests (BorENF). Assimilating ecosystem COS fluxes at Hyytiälä forest increases the simulated net ecosystem COS uptake by 14%. This increase largely results from changes in the internal conductance to COS, highlighting the need to improve the representation of COS internal diffusion and consumption. Moreover, joint assimilation of ecosystem COS flux and GPP at Hyytiälä improves the simulated latent heat flux, contrary to the GPP-only data assimilation, which fails to do so. Finally, we scaled this assimilation framework up to the boreal region and find that the joint assimilation of COS at Hyytiälä and GPP fluxes at 10 BorENF sites increases the modeled vegetation COS uptake up to 18%, but not GPP. Therefore, this study encourages the use of COS flux observations to inform GPP and latent heat flux representations in LSMs. Journal of Geophysical Research: Biogeosciences, 128 (7) ISSN:2169-8961 ISSN:0148-0227 ISSN:2169-8953

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    Journal of Geophysical Research Biogeosciences
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    Authors: Leila El-Bassi; Ahmed Amine Azzaz; Salah Jellali; Hanene Akrout; +3 Authors

    International audience; The olive oil industry is an important economic sector in Mediterranean countries. However, oil production is unfortunately accompanied by the generation of huge amounts of olive mill solid wastes (OMSW) and olive mill wastewater (OMWW). In the present study, a strategy is proposed for converting these olive mill wastes into biochar through pyrolysis, for their later use as an organic amendment in agriculture. Specifically, two biochars were prepared from the pyrolysis of OMSW at 500°C, either alone or impregnated with OMWW (OMSW-B and I-OMSW-B). The characterization of the OMSW and I-OMSW samples and their derived biochars showed that the fixed carbon and ash contents in the feedstocks increased by 38% and 11% respectively for OMSW-B, and by 37% and 12% respectively for I-OMSW-B. Interestingly, the impregnation process significantly increased Na, P, K, Ca and Fe contents in the produced biochars. The effect of OMSW-B and I-OMSW-B amendments at different application dose (1%, 2.5% and 5% wt/wt) on the enzymatic activity of an agricultural soil was performed at laboratory scale with a pot test. The experimental results showed that phosphatase and urease activity increased with biochar application rate; amendment with I-OMSW-B at 1%, 2.5% and 5% enhanced the phosphatase activity by 63%, 142% and 285% and urease activity by 50%, 116% and 149%, respectively. On the other hand, dehydrogenase and protease activities were higher for the application rate of 2.5% biochar. Biochar amendment promoted tomatoes seedling growth after 10 weeks, which was highest in the application rates of 2.5% and 5% for both OMSW-B and I-OSMW-B. Thus, the produced biochars had great potential to be used as biofertilizers in agriculture.

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    The Science of The Total Environment
    Article . 2021 . Peer-reviewed
    License: Elsevier TDM
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    Hal-Diderot
    Article . 2020
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  • Authors: Kounades-Bastian, Dionyssos;

    In this thesis we address the problem of multichannel audio source separa- tion (MASS) for underdetermined convolutive mixtures through probabilistic modeling. We focus on three aspects of the problem and make three contri- butions. Firstly, inspired from the empirically well validated representation of an audio signal, that is know as local Gaussian signal model (LGM) with non-negative matrix factorization (NMF), we propose a Bayesian extension to this, that overcomes some of the limitations of the NMF. We incorporate this representation in a MASS framework and compare it with the state of the art in MASS, yielding promising results. Secondly, we study how to separate mix- tures of moving sources and/or of moving microphones. Movements make the acoustic path between sources and microphones become time-varying. Ad- dressing time-varying audio mixtures appears is not so popular in the MASS literature. Thus, we begin from a state of the art LGM-with-NMF method designed for separating time-invariant audio mixtures and propose an exten- sion that uses a Kalman smoother to track the acoustic path across time. The proposed method is benchmarked against a block-wise adaptation of that state of the art (ran on time segments), and delivers competitive results on both simulated and real-world mixtures. Lastly, we investigate the link between MASS and the task of audio diarisation. Audio diarisation is the detection of the time intervals where each speaker/source is active or silent. Most state of the art MASS methods consider the sources to emit continuously; A hypothe- sis that can result in spurious signal estimates for a source, in intervals where that source was silent. Our aim is that diarisation can aid MASS by indicat- ing the emitting sources at each time frame. To that extent we design a joint framework for simultaneous diarisation and MASS, that incorporates a hidden Markov model (HMM) to track the temporal activity of the sources, within a state of the art LGM-with-NMF MASS framework. We compare the proposed method with the state of the art in MASS and audio diarisation tasks. We ob- tain performances comparable, with the state of the art, in terms of separation while winning in terms of diarisation.; Dans cette thèse nous abordons le problème de la séparation de sources audio dans des mélanges convolutifs multicanaux et sous-déterminés, en utilisant une modélisation probabiliste. Nous nous concentrons sur trois aspects, et nous apportons trois contributions. D’abord, nous nous inspirons du modèle Gaussien local par factorisation en matrices non-négatives (LGM-with-NMF), qui est un modèle empiriquement validé pour représenter un signal audio. Nous proposons une extension Bayésienne de ce modèle, qui permet de sur- passer certaines limitations du modèle NMF. Nous incorporons cette représentation dans un cadre de separation audio multicanaux, et le comparons avec l’état de l’art sur des tâches de séparation. Nous obtenons des résultats prometteurs. Deuxièment, nous étudions comment séparer des mélanges audio de sources et/ou des capteurs en mouvement. Ces déplacements rendent le chemin acoustique entre les sources et les microphones variant en cours du temps. L’adressage des mélanges convolutifs variant au cours du temps est peu exploré dans la littérature. Ainsi, nous partons d’une méthode de l’état de l’art développée pour la séparation de mélanges invariant (sources et microphones statiques) et utilisant LGM-with-NMF. Nous proposons à ceci une extension qui utilise un filtre de Kalman pour suivre le chemin acoustique au cours du temps. La technique proposée est comparée à une adaptation block-par-block d’une technique de l’état de l’art appliquée sur des intervalles de temps, et a donné des résultats exceptionels sur les mélanges simulés et les mélanges du monde réel. Enfin, nous investiguons les similitudes entre la séparation et la journalisation audio. La journalisation est le problème de détection des intervalles auxquels chaque locuteur/source est émettant. La plupart des méthodes de séparation supposent toutes les sources émettent continuellement. Cette hypothèe peut donner lieu à de fausses estimations durant les intervalles au cours desquels cette source n’a pas émis. Notre objectif est que la journalisation puisse aider à résoudre la séparation, en indiquant les sources qui émettent à chaque intervalle de temps. Dans cette mesure, nous concevons une cadre commun pour traiter simultanément la journalisation et la séparation du mélange audio. Ce cadre incorpore un modèle de Markov caché pour suivre les activités des sources au sein d’une technique de séparation LGM-with-NMF. Nous comparons l’algorithme proposé à l’état de l’art sur des tâches de séparation et de journalisation. Nous obtenons des performances comparables avec l’état de l’art pour la séparation, et supériures pour la journalisation.

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    Report on dissemination activities at workshops organised outside the project.

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    Authors: Patel, Pankesh; Pathak, Animesh; Teixeira, Thiago; Issarny, Valérie;

    ISBN: 978-1-4503-1072-7; International audience; The Internet of Things (IoT) integrates the physical world with the existing Internet, and is rapidly gaining popularity, thanks to the increased adoption of smart phones and sensing devices. One of the important challenges in this domain is to enable domain experts to easily specify applications for the IoT. As a first step towards developing a suitable programming abstraction, in this paper we present a domain model for applications in the Internet of Things, based on a survey of recently proposed IoT applications from the real world that represent a wide class of behaviors found in IoT use cases.

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    https://doi.org/10.1145/209319...
    Conference object . 2011 . Peer-reviewed
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    Authors: Bettge, Anika; Roscher, Ribana; Wenzel, Susanne;

    This paper addresses the land cover classification task for remote sensing images by deep self-taught learning. Our self-taught learning approach learns suitable feature representations of the input data using sparse representation and undercomplete dictionary learning. We propose a deep learning framework which extracts representations in multiple layers and use the output of the deepest layer as input to a classification algorithm. We evaluate our approach using a multispectral Landsat 5 TM image of a study area in the North of Novo Progresso (South America) and the Zurich Summer Data Set provided by the University of Zurich. Experiments indicate that features learned by a deep self-taught learning framework can be used for classification and improve the results compared to classification results using the original feature representation. Comment: This is a corrected version of the final paper published in the proceedings

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    https://doi.org/10.48550/arxiv...
    Article . 2017
    License: arXiv Non-Exclusive Distribution
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    Authors: Aiello, Orazio; Crovetti, Paolo; Alioto, Massimo;

    In this paper, two circuit topologies of pW-power Hz-range wake-up oscillators for sensor node applications are presented. The proposed circuits are based on standard cells utilizing the Dynamic Leakage Suppression logic style [4]–[5]. The proposed oscillators exhibit low supply voltage sensitivity over a wide supply voltage range, from nominal voltage down to the deep sub-threshold region (i.e., 0.3 V). This enables direct powering from energy harvesters or batteries through their whole discharge cycle, suppressing the need for voltage regulation. Post-layout time-domain simulations of the proposed oscillators in 180nm show a power consumption of 1.4–1.7pW, a supply-sensitivity of 55–40%/V over the 0.3V–1.8V supply voltage range, and a compact area down to 1,500µm2. The very low power consumption makes the proposed circuits very well suited for energy-harvested systems-on-chip for Internet of Things applications.

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    https://doi.org/10.1109/iscas....
    Conference object . 2019 . Peer-reviewed
    License: IEEE Copyright
    Data sources: Sygma; Crossref
    https://doi.org/10.1109/ISCAS....
    Other literature type . Conference object . 2019