Results 101 to 110 of about 13,061 (285)
Metric Differential Privacy on the Special Orthogonal Group SO(3)
Journal of Cybersecurity and PrivacyDifferential privacy (DP) is an important framework to provide strong theoretical guarantees on the privacy and utility of released data. Since its introduction in 2006, DP has been applied to various data types and domains.
Anna Katharina Hildebrandt +2 more
doaj +1 more source
Laplace pressure based disjoining pressure isotherm in non symmetric conditions
, 2017 International audienceUnderstanding the stability and dynamics of two phase systems, such as foams and emulsions, in porous media is still a challenge for physicists and calls for a better understanding of the intermolecular interactions between ...
Valignat, Marie-Pierre +5 more
core +1 more source
, 2009 Published in 1831, this work forms part of a collection of introductory volumes suggested by Henry, Lord Brougham and Vaux, the Lord Chancellor, for the Society of the Diffusion of Useful Knowledge.
Pierre Simon Laplace
core +1 more source
Nanodiamonds as Bioactive Platforms to Modulate Microbial, Mammalian, and Vertebrate Systems
Advanced NanoBiomed Research, EarlyView.Nanodiamonds (NDs) are biocompatible and antibacterial nanomaterials that support mammalian cell growth while inhibiting bacterial pathogens. NDs showed strong antibacterial activity, with Escherichia coli being more sensitive than Staphylococcus aureus. At 10 mg/mL, both bacteria exhibited ~8% viability.
Aaqil Rifai +6 more
wiley +1 more source
Privacy-Preserving Classification on Deep Learning with Exponential Mechanism
International Journal of Computational Intelligence SystemsHow to protect the privacy of training data in deep learning has been the subject of increasing amounts of related research in recent years. Private Aggregation of Teacher Ensembles (PATE) uses transfer learning and differential privacy methods to ...
Quan Ju +3 more
doaj +1 more source
Unifying Laplace Mechanism with Instance Optimality in Differential Privacy
CoRRWe adapt the canonical Laplace mechanism, widely used in differentially private data analysis, to achieve near instance optimality with respect to the hardness of the underlying dataset. In particular, we construct a piecewise Laplace distribution whereby we defy traditional assumptions and show that Laplace noise can in fact be drawn proportional to ...
openaire +2 more sources
Journal of Applied MathematicsThe KdV-Burgers equation is one of the most important partial differential equations, established by Korteweg and de Vries to describe the behavior of nonlinear waves and many physical phenomena. In this paper, we reformulate this problem in the sense of
Aliaa Burqan +4 more
doaj +1 more source
Asia-Pacific Journal of Chemical Engineering, EarlyView.ABSTRACT The global trend toward sustainable and intensified bioprocesses is driving innovation in the design and scalable synthesis of liposomal nanocarriers, a cornerstone of modern drug delivery. For decades, these nanosystems have relied exclusively on polyethylene glycol (PEG) for their sustained circulation in vivo, but they are currently ...
Chandra Has
wiley +1 more source
Differential Privacy Preservation for Continuous Release of Real-Time Location Data
EntropyContinuous real-time location data is very important in the big data era, but the privacy issues involved is also a considerable topic. It is not only necessary to protect the location privacy at each release moment, but also have to consider the impact ...
Lihui Mao, Zhengquan Xu
doaj +1 more source
Bayesianism, Conditional Probability and Laplace Law of Succession in Quantum Mechanics
Foundations of PhysicsWe present a comparative study between classical probability and quantum probability from the Bayesian viewpoint, where probability is construed as our rational degree of belief on whether a given statement is true. From this viewpoint, including conditional probability, three issues are discussed: i) Given a measure of the rational degree of belief ...
openaire +3 more sources