Improving Bundle Routing in a Space DTN by Approximating the Transmission Time of the Reliable LTP
Network, 2023 Because the operation of space networks is carefully planned, it is possible to predict future contact opportunities from link budget analysis using the anticipated positions of the nodes over time.
Ricardo Lent
doaj +1 more source
On deferred I-statistical rough convergence of difference sequences in neutrosophic normed spaces [PDF]
Neutrosophic Sets and SystemsIn this study, using the concepts of deferred density and the notion of the ideal I, we extend the idea of rough convergence by introducing the notion of deferred I–statistical rough convergence via difference operators in the framework of neutrosophic ...
Mukhtar Ahmad +2 more
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Experimental Evaluation and Analysis of Federated Learning in Edge Computing Environments
IEEE Access, 2023 Federated learning (FL) is a machine learning system that allows a network of devices to train a model without centralized data. This characteristic makes FL an ideal choice for machine learning using user data while maintaining privacy.
Pham Khanh Quan +2 more
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Validation of the Jarzynski relation for a system with strong thermal coupling: an isothermal ideal gas model [PDF]
, 2006 We revisit the paradigm of an ideal gas under isothermal conditions. A moving piston performs work on an ideal gas in a container that is strongly coupled to a heat reservoir. The thermal coupling is modeled by stochastic scattering at the boundaries. In
A. Baule +5 more
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Strong and uniform convergence in the teleportation simulation of bosonic Gaussian channels [PDF]
, 2018 In the literature on the continuous-variable bosonic teleportation protocol due to [Braunstein and Kimble, Phys. Rev. Lett., 80(4):869, 1998], it is often loosely stated that this protocol converges to a perfect teleportation of an input state in the ...
Wilde, Mark M.
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Petuum: A New Platform for Distributed Machine Learning on Big Data [PDF]
, 2015 What is a systematic way to efficiently apply a wide spectrum of advanced ML programs to industrial scale problems, using Big Models (up to 100s of billions of parameters) on Big Data (up to terabytes or petabytes)?
Dai, Wei +9 more
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Alexandria Engineering Journal, 2023 This paper addresses the pressing concern of traffic safety by focusing on the optimization of vehicle cruise control systems. While traditional control techniques have been widely employed, their design procedures can be time-consuming and suboptimal ...
Davut Izci +3 more
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Orlicz–Pettis Theorem through Summability Methods
Mathematics, 2019 This paper unifies several versions of the Orlicz−Pettis theorem that incorporate summability methods. We show that a series is unconditionally convergent if and only if the series is weakly subseries convergent with respect to a regular linear ...
Fernando León-Saavedra +2 more
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General empirical Bayes wavelet methods and exactly adaptive minimax estimation
, 2005 In many statistical problems, stochastic signals can be represented as a sequence of noisy wavelet coefficients. In this paper, we develop general empirical Bayes methods for the estimation of true signal.
Zhang, Cun-Hui
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Quantum gas-liquid condensation in an attractive Bose gas [PDF]
, 2005 Gas-liquid condensation (GLC) in an attractive Bose gas is studied on the basis of statistical mechanics. Using some results in combinatorial mathematics, the following are derived: (1) With decreasing temperature, the Bose-statistical coherence grows in
Koh, Shun-ichiro
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