Kantorovich Distance Based Fault Detection Scheme for Non-Linear Processes [PDF]
IEEE Access, 2022 Fault detection is necessary for safe operation in modern process plants. The kernel principal component analysis (KPCA) technique has been widely utilized for monitoring non-linear processes because it enhances dimension reduction and fault detection in
K. Ramakrishna Kini +2 more
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Improved Process Monitoring Strategy Using Kantorovich Distance-Independent Component Analysis: An Application to Tennessee Eastman Process [PDF]
IEEE Access, 2020 Vowing to the increasing complexity in industrial processes, the need for safety is of highest priority and this has led to development of efficient fault detection (FD) methods.
K. Ramakrishna Kini, Muddu Madakyaru
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Global Resource Disparities Between Pulmonary Hypertension Centers: Results From the International Survey by the PVRI IDDI Access to Care Workstream. [PDF]
Pulm CircABSTRACT There is a limited understanding of how pulmonary hypertension (PH) patients are managed worldwide. The Pulmonary Vascular Research Institute (PVRI) Innovative Drug Discovery Initiative (IDDI) global survey attempted to obtain insights into access to PH care in diverse international regions to pave future action plans.
Prisco SZ +9 more
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Entropy-Regularized Optimal Transport on Multivariate Normal and q-normal Distributions. [PDF]
Entropy (Basel), 2021 The distance and divergence of the probability measures play a central role in statistics, machine learning, and many other related fields. The Wasserstein distance has received much attention in recent years because of its distinctions from other ...
Tong Q, Kobayashi K.
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Wasserstein Distance-Based Deep Leakage from Gradients. [PDF]
Entropy (Basel), 2023 Federated learning protects the privacy information in the data set by sharing the average gradient. However, “Deep Leakage from Gradient” (DLG) algorithm as a gradient-based feature reconstruction attack can recover privacy training data using gradients
Wang Z, Peng C, He X, Tan W.
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Characteristic Logics for Behavioural Hemimetrics via Fuzzy Lax Extensions [PDF]
Logical Methods in Computer Science, 2022 In systems involving quantitative data, such as probabilistic, fuzzy, or metric systems, behavioural distances provide a more fine-grained comparison of states than two-valued notions of behavioural equivalence or behaviour inclusion.
Paul Wild, Lutz Schröder
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Mathematics, 2020 We introduce a generalized stationary renewal distribution (also called the equilibrium transform) for arbitrary distributions with finite nonzero first moment and study its properties.
Irina Shevtsova, Mikhail Tselishchev
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Variational approach to eikonal function computation [PDF]
Компьютерная оптика, 2018 The problem of calculating the eikonal function from the condition of focusing into a prescribed region is formulated as a variational problem and as a Monge-Kantorovich mass transportation problem.
Leonid Doskolovich +3 more
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A two-stage stochastic optimization based-on monte carlo simulation for maximizing the profitability of a smart microgrid [PDF]
Journal of Hyperstructures, 2018 In this paper, a two-stage stochastic model for optimizing the profit of a smart microgrid is proposed in which the uncertainty of loads, electricity market price and renewable generation are modeled using developing stochastic scenarios with Monte Carlo
Mohammad Javad Salehpour +1 more
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Logical Characterization of Bisimulation Metrics [PDF]
Electronic Proceedings in Theoretical Computer Science, 2016 Bisimulation metrics provide a robust and accurate approach to study the behavior of nondeterministic probabilistic processes. In this paper, we propose a logical characterization of bisimulation metrics based on a simple probabilistic variant of the ...
Valentina Castiglioni +2 more
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