Should Firms Look to an Insider or an Outsider When Hiring a New CEO? Evidence from China
In: Journal of Asia Pacific business, Band 17, Heft 2, S. 103-129
ISSN: 1528-6940
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In: Journal of Asia Pacific business, Band 17, Heft 2, S. 103-129
ISSN: 1528-6940
In: Reihe Phönixfeder 32
In: Waste management: international journal of integrated waste management, science and technology, Band 174, S. 88-95
ISSN: 1879-2456
In: Progress in nuclear energy: the international review journal covering all aspects of nuclear energy, Band 117, S. 103086
ISSN: 0149-1970
In: Waste management: international journal of integrated waste management, science and technology, Band 133, S. 1-9
ISSN: 1879-2456
In: Defence Technology, Band 16, Heft 1, S. 257-262
ISSN: 2214-9147
With the rapid development of communication technology in recent years, Wireless Sensor Network (WSN) has become a promising research project. WSN is widely applied in a number of fields such as military, environmental monitoring, space exploration and so on. The non-line-of-sight (NLOS) localization is one of the most essential techniques for WSN. However, the NLOS propagation of WSN is largely influenced by many factors. Hence, a triple filters mixed Kalman Filter (KF) and Unscented Kalman Filter (UKF) voting algorithm based on Fuzzy-C-Means (FCM) and residual analysis (TF-FCM) has been proposed to cope with this problem. Firstly, an NLOS identification algorithm based on residual analysis is used to identify NLOS errors. Then, an NLOS correction algorithm based on voting and NLOS errors classification algorithm based on FCM are used to process the NLOS measurements. Hard NLOS measurements and soft NLOS measurements are classified by FCM classification. Secondly, KF and UKF are applied to filter two categories of NLOS measurements. Thirdly, maximum likelihood localization (ML) is employed to estimate the position of mobile nodes. The simulation result confirms that the accuracy and robustness of TF-FCM are better than IMM, UKF and KF. Finally, an experiment is conducted to test and verify our algorithm which obtains higher localization accuracy.
BASE
In: Environmental science and pollution research: ESPR, Band 28, Heft 34, S. 46130-46146
ISSN: 1614-7499
In: Materials and design, Band 95, S. 446-454
ISSN: 1873-4197
In: Advances in applied ceramics: structural, functional and bioceramics, Band 119, Heft 4, S. 195-203
ISSN: 1743-6761
In: Environmental science and pollution research: ESPR, Band 24, Heft 35, S. 26881-26892
ISSN: 1614-7499
In: Environmental science and pollution research: ESPR, Band 25, Heft 3, S. 2293-2302
ISSN: 1614-7499
In: HELIYON-D-22-21284
SSRN
International audience ; The Orbiting Carbon Observatory-2 has been on orbit since 2014, and its global coverage holds the potential to reveal new information about the carbon cycle through the use of top-down atmospheric inversion methods combined with column average CO 2 retrievals. We employ a large ensemble of atmospheric inversions utilizing different transport models, data assimilation techniques, and prior flux distributions in order to quantify the satellite-informed fluxes from OCO-2 Version 7r land observations and their uncertainties at continental scales. Additionally, we use in situ measurements to provide a baseline against which to compare the satellite-constrained results. We find that within the ensemble spread, in situ observations, and satellite retrievals constrain a similar global total carbon sink of 3.7 ± 0.5 PgC yr −1 , and 1.5±0.6 PgC yr −1 for global land, for the 2015-2016 annual mean. This agreement breaks down in smaller regions, and we discuss the differences between the experiments. Of particular interest is the difference between the different assimilation constraints in the tropics, with the largest differences occurring in tropical Africa, which could be an indication of the global perturbation from the 2015-2016 El Niño. Evaluation of posterior concentrations using TCCON and aircraft observations gives some limited insight into the quality of the different assimilation constraints, but the lack of such data in the tropics inhibits our ability to make strong conclusions there. Copyright statement. The works published in this journal are distributed under the Creative Commons Attribution 4.0 License. This license does not affect the Crown copyright work, which is re-usable under the Open Government Licence (OGL). The Creative Commons Attribution 4.0 License and the OGL are interoperable and do not conflict with, reduce or limit each other. Published by Copernicus Publications on behalf of the European Geosciences Union. 9798 S. Crowell et al.: The 2015-2016 carbon cycle as seen ...
BASE
International audience ; The Orbiting Carbon Observatory-2 has been on orbit since 2014, and its global coverage holds the potential to reveal new information about the carbon cycle through the use of top-down atmospheric inversion methods combined with column average CO 2 retrievals. We employ a large ensemble of atmospheric inversions utilizing different transport models, data assimilation techniques, and prior flux distributions in order to quantify the satellite-informed fluxes from OCO-2 Version 7r land observations and their uncertainties at continental scales. Additionally, we use in situ measurements to provide a baseline against which to compare the satellite-constrained results. We find that within the ensemble spread, in situ observations, and satellite retrievals constrain a similar global total carbon sink of 3.7 ± 0.5 PgC yr −1 , and 1.5±0.6 PgC yr −1 for global land, for the 2015-2016 annual mean. This agreement breaks down in smaller regions, and we discuss the differences between the experiments. Of particular interest is the difference between the different assimilation constraints in the tropics, with the largest differences occurring in tropical Africa, which could be an indication of the global perturbation from the 2015-2016 El Niño. Evaluation of posterior concentrations using TCCON and aircraft observations gives some limited insight into the quality of the different assimilation constraints, but the lack of such data in the tropics inhibits our ability to make strong conclusions there. Copyright statement. The works published in this journal are distributed under the Creative Commons Attribution 4.0 License. This license does not affect the Crown copyright work, which is re-usable under the Open Government Licence (OGL). The Creative Commons Attribution 4.0 License and the OGL are interoperable and do not conflict with, reduce or limit each other. Published by Copernicus Publications on behalf of the European Geosciences Union. 9798 S. Crowell et al.: The 2015-2016 carbon cycle as seen ...
BASE