Stanford University

About: Stanford University is a education organization based out in Stanford, California, United States. It is known for research contribution in the topics: Population & Transplantation. The organization has 125751 authors who have published 320347 publications receiving 21892059 citations. The organization is also known as: Leland Stanford Junior University & University of Stanford.

Quantification of sleepiness: a new approach.

Abstract: The Stanford Sleepiness Scale (SSS) is a self-rating scale which is used to quantify progressive steps in sleepiness. The present study investigated whether the SSS cross-validates with performance on mental tasks and whether the SSS demonstrates changes in sleepiness with sleep loss. Five college student Ss were given a brief test of memory and the Wilkinson Addition Test in 2 test sessions and The Wilkinson Vigilance Test in 2 other sessions spaced throughout a 16-hr day for 6 days. Ss made SSS ratings every 15 min during their waking activities. On night 4, Ss underwent all night sleep deprivation. On all other nights, Ss were allowed only 8 hrs in bed. Mean SSS ratings correlated r= .68 with performance on the Wilkinson Tests. Discrete SSS ratings correlated r= .47 with performance on the memory test. Moreover, mean baseline SSS ratings were found to be significantly lower than corresponding ratings of the deprivation period.

30 years of adaptive neural networks: perceptron, Madaline, and backpropagation

Abstract: Fundamental developments in feedforward artificial neural networks from the past thirty years are reviewed. The history, origination, operating characteristics, and basic theory of several supervised neural-network training algorithms (including the perceptron rule, the least-mean-square algorithm, three Madaline rules, and the backpropagation technique) are described. The concept underlying these iterative adaptation algorithms is the minimal disturbance principle, which suggests that during training it is advisable to inject new information into a network in a manner that disturbs stored information to the smallest extent possible. The two principal kinds of online rules that have developed for altering the weights of a network are examined for both single-threshold elements and multielement networks. They are error-correction rules, which alter the weights of a network to correct error in the output response to the present input pattern, and gradient rules, which alter the weights of a network during each pattern presentation by gradient descent with the objective of reducing mean-square error (averaged over all training patterns). >

Strong radiative heating due to the mixing state of black carbon in atmospheric aerosols

Abstract: Aerosols affect the Earth's temperature and climate by altering the radiative properties of the atmosphere. A large positive component of this radiative forcing from aerosols is due to black carbon--soot--that is released from the burning of fossil fuel and biomass, and, to a lesser extent, natural fires, but the exact forcing is affected by how black carbon is mixed with other aerosol constituents. From studies of aerosol radiative forcing, it is known that black carbon can exist in one of several possible mixing states; distinct from other aerosol particles (externally mixed) or incorporated within them (internally mixed), or a black-carbon core could be surrounded by a well mixed shell. But so far it has been assumed that aerosols exist predominantly as an external mixture. Here I simulate the evolution of the chemical composition of aerosols, finding that the mixing state and direct forcing of the black-carbon component approach those of an internal mixture, largely due to coagulation and growth of aerosol particles. This finding implies a higher positive forcing from black carbon than previously thought, suggesting that the warming effect from black carbon may nearly balance the net cooling effect of other anthropogenic aerosol constituents. The magnitude of the direct radiative forcing from black carbon itself exceeds that due to CH4, suggesting that black carbon may be the second most important component of global warming after CO2 in terms of direct forcing.

Metal–Oxide RRAM

Abstract: In this paper, recent progress of binary metal-oxide resistive switching random access memory (RRAM) is reviewed. The physical mechanism, material properties, and electrical characteristics of a variety of binary metal-oxide RRAM are discussed, with a focus on the use of RRAM for nonvolatile memory application. A review of recent development of large-scale RRAM arrays is given. Issues such as uniformity, endurance, retention, multibit operation, and scaling trends are discussed.