The Experts below are selected from a list of 101577 Experts worldwide ranked by ideXlab platform
W. Maneschg - One of the best experts on this subject based on the ideXlab platform.
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Large-size sub-keV sensitive germanium detectors for the CONUS experiment
The European Physical Journal C, 2021Co-Authors: H. Bonet, A. Bonhomme, C. Buck, K. Fülber, J. Hakenmüller, G. Heusser, T. Hugle, J. B. Legras, M. Lindner, W. ManeschgAbstract:Intense fluxes of reactor antineutrinos offer a unique possibility to probe the fully coherent character of elastic neutrino scattering off atomic nuclei. In this regard, detectors face the challenge to register tiny recoil energies of a few keV at the maximum. The Conus experiment was installed in 17.1 m distance from the reactor core of the nuclear power plant in Brokdorf, Germany, and was designed to detect this neutrino Interaction Channel by using four 1 kg-sized point contact germanium detectors with sub-keV energy thresholds. This report describes the unique specifications addressed to the design, the research and development, and the final production of these detectors. It demonstrates their excellent electronic performance obtained during commissioning under laboratory conditions as well as during the first 2 years of operation at the reactor site which started on April 1, 2018. It highlights the long-term stability of different detector parameters and the achieved background levels of the germanium detectors inside the Conus shield setup.
L. Sajn - One of the best experts on this subject based on the ideXlab platform.
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augmented coaching ecosystem for non obtrusive adaptive personalized elderly care on the basis of cloud fog dew computing paradigm
arXiv: Computers and Society, 2017Co-Authors: Yu. Gordienko, U. Lushchyk, A. Rojbi, Oleg Alienin, Sergii Stirenko, Karolj Skala, Z Soyat, J Lopez R Benito, Artetxe E Gonzalez, L. SajnAbstract:The concept of the augmented coaching ecosystem for non-obtrusive adaptive personalized elderly care is proposed on the basis of the integration of new and available ICT approaches. They include the multimodal user interface (MMUI), augmented reality (AR), machine learning (ML), Internet of Things (IoT), and machine-to-machine (M2M) Interactions. The ecosystem is based on the Cloud-Fog-Dew computing paradigm services, providing a full symbiosis by integrating the whole range from low-level sensors up to high-level services using integration efficiency inherent in synergistic use of applied technologies. Inside of this ecosystem, all of them are encapsulated in the following network layers: Dew, Fog, and Cloud computing layer. Instead of the "spaghetti connections", "mosaic of buttons", "puzzles of output data", etc., the proposed ecosystem provides the strict division in the following dataflow Channels: consumer Interaction Channel, machine Interaction Channel, and caregiver Interaction Channel. This concept allows to decrease the physical, cognitive, and mental load on elderly care stakeholders by decreasing the secondary human-to-human (H2H), human-to-machine (H2M), and machine-to-human (M2H) Interactions in favor of M2M Interactions and distributed Dew Computing services environment. It allows to apply this non-obtrusive augmented reality ecosystem for effective personalized elderly care to preserve their physical, cognitive, mental and social well-being.
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Augmented Coaching Ecosystem for Non-obtrusive Adaptive Personalized Elderly Care on the basis of Cloud-Fog-Dew computing paradigm
2017 40th International Convention on Information and Communication Technology Electronics and Microelectronics MIPRO 2017 - Proceedings, 2017Co-Authors: Yu. Gordienko, E. Artetxe Gonzalez, U. Lushchyk, J. R. López Benito, Zorislav Sojat, A. Rojbi, Oleg Alienin, Sergii Stirenko, Karolj Skala, L. SajnAbstract:The concept of the augmented coaching ecosystem for non-obtrusive adaptive personalized elderly care is proposed on the basis of the integration of new and available ICT approaches. They include multimodal user interface (MMUI), augmented reality (AR), machine learning (ML), Internet of Things (IoT), and machine-to-machine (M2M) Interactions. The ecosystem is based on the Cloud-Fog-Dew computing paradigm services, providing a full symbiosis by integrating the whole range from low level sensors up to high level services using integration efficiency inherent in synergistic use of applied technologies. Inside of this ecosystem, all of them are encapsulated in the following network layers: Dew, Fog, and Cloud computing layer. Instead of the “spaghetti connections”, “mosaic of buttons”, “puzzles of output data”, etc., the proposed ecosystem provides the strict division in the following dataflow Channels: consumer Interaction Channel, machine Interaction Channel, and caregiver Interaction Channel. This concept allows to decrease the physical, cognitive, and mental load on elderly care stakeholders by decreasing the secondary human-to-human (H2H), human-to-machine (H2M), and machine-to-human (M2H) Interactions in favor of M2M Interactions and distributed Dew Computing services environment. It allows to apply this non-obtrusive augmented reality ecosystem for effective personalized elderly care to preserve their physical, cognitive, mental and social well-being.
H. Bonet - One of the best experts on this subject based on the ideXlab platform.
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Large-size sub-keV sensitive germanium detectors for the CONUS experiment
The European Physical Journal C, 2021Co-Authors: H. Bonet, A. Bonhomme, C. Buck, K. Fülber, J. Hakenmüller, G. Heusser, T. Hugle, J. B. Legras, M. Lindner, W. ManeschgAbstract:Intense fluxes of reactor antineutrinos offer a unique possibility to probe the fully coherent character of elastic neutrino scattering off atomic nuclei. In this regard, detectors face the challenge to register tiny recoil energies of a few keV at the maximum. The Conus experiment was installed in 17.1 m distance from the reactor core of the nuclear power plant in Brokdorf, Germany, and was designed to detect this neutrino Interaction Channel by using four 1 kg-sized point contact germanium detectors with sub-keV energy thresholds. This report describes the unique specifications addressed to the design, the research and development, and the final production of these detectors. It demonstrates their excellent electronic performance obtained during commissioning under laboratory conditions as well as during the first 2 years of operation at the reactor site which started on April 1, 2018. It highlights the long-term stability of different detector parameters and the achieved background levels of the germanium detectors inside the Conus shield setup.
Yu. Gordienko - One of the best experts on this subject based on the ideXlab platform.
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augmented coaching ecosystem for non obtrusive adaptive personalized elderly care on the basis of cloud fog dew computing paradigm
arXiv: Computers and Society, 2017Co-Authors: Yu. Gordienko, U. Lushchyk, A. Rojbi, Oleg Alienin, Sergii Stirenko, Karolj Skala, Z Soyat, J Lopez R Benito, Artetxe E Gonzalez, L. SajnAbstract:The concept of the augmented coaching ecosystem for non-obtrusive adaptive personalized elderly care is proposed on the basis of the integration of new and available ICT approaches. They include the multimodal user interface (MMUI), augmented reality (AR), machine learning (ML), Internet of Things (IoT), and machine-to-machine (M2M) Interactions. The ecosystem is based on the Cloud-Fog-Dew computing paradigm services, providing a full symbiosis by integrating the whole range from low-level sensors up to high-level services using integration efficiency inherent in synergistic use of applied technologies. Inside of this ecosystem, all of them are encapsulated in the following network layers: Dew, Fog, and Cloud computing layer. Instead of the "spaghetti connections", "mosaic of buttons", "puzzles of output data", etc., the proposed ecosystem provides the strict division in the following dataflow Channels: consumer Interaction Channel, machine Interaction Channel, and caregiver Interaction Channel. This concept allows to decrease the physical, cognitive, and mental load on elderly care stakeholders by decreasing the secondary human-to-human (H2H), human-to-machine (H2M), and machine-to-human (M2H) Interactions in favor of M2M Interactions and distributed Dew Computing services environment. It allows to apply this non-obtrusive augmented reality ecosystem for effective personalized elderly care to preserve their physical, cognitive, mental and social well-being.
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Augmented Coaching Ecosystem for Non-obtrusive Adaptive Personalized Elderly Care on the basis of Cloud-Fog-Dew computing paradigm
2017 40th International Convention on Information and Communication Technology Electronics and Microelectronics MIPRO 2017 - Proceedings, 2017Co-Authors: Yu. Gordienko, E. Artetxe Gonzalez, U. Lushchyk, J. R. López Benito, Zorislav Sojat, A. Rojbi, Oleg Alienin, Sergii Stirenko, Karolj Skala, L. SajnAbstract:The concept of the augmented coaching ecosystem for non-obtrusive adaptive personalized elderly care is proposed on the basis of the integration of new and available ICT approaches. They include multimodal user interface (MMUI), augmented reality (AR), machine learning (ML), Internet of Things (IoT), and machine-to-machine (M2M) Interactions. The ecosystem is based on the Cloud-Fog-Dew computing paradigm services, providing a full symbiosis by integrating the whole range from low level sensors up to high level services using integration efficiency inherent in synergistic use of applied technologies. Inside of this ecosystem, all of them are encapsulated in the following network layers: Dew, Fog, and Cloud computing layer. Instead of the “spaghetti connections”, “mosaic of buttons”, “puzzles of output data”, etc., the proposed ecosystem provides the strict division in the following dataflow Channels: consumer Interaction Channel, machine Interaction Channel, and caregiver Interaction Channel. This concept allows to decrease the physical, cognitive, and mental load on elderly care stakeholders by decreasing the secondary human-to-human (H2H), human-to-machine (H2M), and machine-to-human (M2H) Interactions in favor of M2M Interactions and distributed Dew Computing services environment. It allows to apply this non-obtrusive augmented reality ecosystem for effective personalized elderly care to preserve their physical, cognitive, mental and social well-being.
J. B. Legras - One of the best experts on this subject based on the ideXlab platform.
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Large-size sub-keV sensitive germanium detectors for the CONUS experiment
The European Physical Journal C, 2021Co-Authors: H. Bonet, A. Bonhomme, C. Buck, K. Fülber, J. Hakenmüller, G. Heusser, T. Hugle, J. B. Legras, M. Lindner, W. ManeschgAbstract:Intense fluxes of reactor antineutrinos offer a unique possibility to probe the fully coherent character of elastic neutrino scattering off atomic nuclei. In this regard, detectors face the challenge to register tiny recoil energies of a few keV at the maximum. The Conus experiment was installed in 17.1 m distance from the reactor core of the nuclear power plant in Brokdorf, Germany, and was designed to detect this neutrino Interaction Channel by using four 1 kg-sized point contact germanium detectors with sub-keV energy thresholds. This report describes the unique specifications addressed to the design, the research and development, and the final production of these detectors. It demonstrates their excellent electronic performance obtained during commissioning under laboratory conditions as well as during the first 2 years of operation at the reactor site which started on April 1, 2018. It highlights the long-term stability of different detector parameters and the achieved background levels of the germanium detectors inside the Conus shield setup.