Results 41 to 50 of about 70,225 (278)

Probing Dark Energy Dynamics from Current and Future Cosmological Observations [PDF]

open access: yes, 2010
We report the constraints on the dark energy equation-of-state w(z) using the latest 'Constitution' SNe sample combined with the WMAP5 and SDSS data. Based on the localized principal component analysis and the model selection criteria, we find that the ...
A. Shafieloo   +4 more
core   +3 more sources

Conductance‐Dependent Photoresponse in a Dynamic SrTiO3 Memristor for Biorealistic Computing

open access: yesAdvanced Functional Materials, EarlyView.
A nanoscale SrTiO3 memristor is shown to exhibit dynamic synaptic behavior through the interaction of local electrical and global optical signals. Its photoresponse depends quantitatively on the conductance state, which evolves and decays over tunable timescales, enabling ultralow‐power, biorealistic learning mechanisms for advanced in‐memory and ...
Christoph Weilenmann   +8 more
wiley   +1 more source

Dynamic Neural Fields with Intrinsic Plasticity

open access: yesFrontiers in Computational Neuroscience, 2017
Dynamic neural fields (DNFs) are dynamical systems models that approximate the activity of large, homogeneous, and recurrently connected neural networks based on a mean field approach.
Claudius Strub   +4 more
doaj   +1 more source

Associated production of a Z boson and a b-jet in ATLAS [PDF]

open access: yes, 2007
The current uncertainty on the parametrization of the partonic content of the proton (PDF's) affects the potential for the discovery of new physics at LHC.
Diglio, S.   +3 more
core   +1 more source

Applications of Parametric Searching in Geometric Optimization

open access: yesJournal of Algorithms, 1994
Summary: We present several applications in computational geometry of Megiddo's parametric searching technique. These applications include: (1) finding the minimum Hausdorff distance in the Euclidean metric between two polygonal regions under translation; (2) computing the biggest line segment that can be placed inside a simple polygon; (3) computing ...
Agarwal, Pankaj K.   +2 more
openaire   +2 more sources

Conductive Hydrogels for Exogenous Sensing and Cell Fate Control

open access: yesAdvanced Materials, EarlyView.
We engineer electrically conductive hydrogels by combining sulfated glycosaminoglycans with semiconducting polymers. These hydrogels bind bioactive proteins, including growth factors, whose release or retention can be modulated by low‐voltage stimulation. The hydrogels are also integrated as 3D channels in organic electrochemical transistors as part of
Teuku Fawzul Akbar   +15 more
wiley   +1 more source

Minimax Parametric Optimization Problems and Multidimensional Parametric Searching

open access: yesInterdisciplinary Information Sciences, 2001
Summary: The parametric minimax problem, which finds the parameter value minimizing the weight of a solution of a combinatorial maximization problem, is a fundamental problem in sensitivity analysis. Moreover, several problems in computational geometry can be formulated as parametric minimax problems.
openaire   +3 more sources

Information Transmission Strategies for Self‐Organized Robotic Aggregation

open access: yesAdvanced Robotics Research, EarlyView.
In this review, we discuss how information transmission influences the neighbor‐based self‐organized aggregation of swarm robots. We focus specifically on local interactions regarding information transfer and categorize previous studies based on the functions of the information exchanged.
Shu Leng   +5 more
wiley   +1 more source

Reconstructing a String-Inspired Non-minimally Coupled Quintom Model

open access: yes, 2008
Motivated by the recent work of Zhang and Chen \cite{bin}, we generalize their work to the non-minimally coupled case. We consider a quintom model of dark energy with a single scalar field $T$ given by a Lagrangian which inspired by tachyonic Lagrangian ...
A. R. AMANI   +11 more
core   +2 more sources

Non-parametric policy search with limited information loss [PDF]

open access: yes, 2017
Learning complex control policies from non-linear and redundant sensory input is an important challenge for reinforcement learning algorithms. Non-parametric methods that approximate values functions or transition models can address this problem, by adapting to the complexity of the data set. Yet, many current non-parametric approaches rely on unstable
Herke van Hoof   +2 more
openaire   +5 more sources

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