Traffic theory and the Internet

We argue that traffic theory, an essential component in the design of traditional telecommunications networks, should be increasingly applied in the development of the multiservice Internet. We discuss the statistical characteristics of Internet traffic at different time scales. Modeling is facilitated on identifying the notion of flow and distinguishing the categories of streaming and elastic traffic. We review mathematical modeling approaches useful for predicting the relationship between demand, capacity and performance for both streaming and elastic flows. Derived results indicate the limitations of service differentiation as a means for guaranteeing QoS and highlight the importance of traditional traffic engineering approaches in ensuring that the network has sufficient capacity to handle offered demand     

Spectral mixture analysis of simulated thermal infraredspectrometry data: An initial temperature estimate bounded TESSMA searchapproach

At sensor thermal infrared (TIR) radiation varies depending on the temperature and emissivity of surface materials and the modifying impact of atmospheric absorption and emission. TIR imaging spectrometry often involves extracting temperature, emissivity, and/or surface composition, which are useful in diverse studies ranging from climatology to land use analyses. A two-stage application of temperature emissivity separation (TES) using spectral mixture analysis (SMA) or TESSMA, was employed to characterize isothermal mixtures on a subpixel basis. This two-stage approach first uses the relationship between a virtual cold endmember fraction and surface temperature to extract initial image temperature estimates. Second, an isothermal SMA application searches the region within the maximum temperature error range of the initial estimate, selecting the best subpixel spectral mixture fit. Work presented includes characterizations of synthetically generated temperature and constituent mixture gradient test images, and a discussion of errors associated with selecting temperature search ranges 25% and 75% smaller than the initial temperature calculation error range. Results using this two-stage approach indicate improved overall temperature estimates, constituent estimates, and constituent fraction estimates using simulated TIR data     

Inferring the eigenvalues of covariance matrices from limited,noisy data

The eigenvalue spectrum of covariance matrices is of central importance to a number of data analysis techniques. Usually, the sample covariance matrix is constructed from a limited number of noisy samples. We describe a method of inferring the true eigenvalue spectrum from the sample spectrum. Results of Silverstein (1986), which characterize the eigenvalue spectrum of the noise covariance matrix, and inequalities between the eigenvalues of Hermitian matrices are used to infer probability densities for the eigenvalues of the noise-free covariance matrix, using Bayesian inference. Posterior densities for each eigenvalue are obtained, which yield error estimates. The evidence framework gives estimates of the noise variance and permits model order selection by estimating the rank of the covariance matrix. The method is illustrated with numerical examples     

Gender differences in structured risk assessment: Comparing the accuracy of five instruments.

Structured risk assessment should guide clinical risk management, but it is uncertain which instrument has the highest predictive accuracy among men and women. In the present study, the authors compared the Psychopathy Checklist—Revised (PCL–R; R. D. Hare, 1991, 2003); the Historical, Clinical, Risk Management–20 (HCR-20; C. D. Webster, K. S. Douglas, D. Eaves, & S. D. Hart, 1997); the Risk Matrix 2000–Violence (RM2000[V]; D. Thornton et al., 2003); the Violence Risk Appraisal Guide (VRAG; V. L. Quinsey, G. T. Harris, M. E. Rice, & C. A. Cormier, 1998); the Offenders Group Reconviction Scale (OGRS; J. B. Copas & P. Marshall, 1998; R. Taylor, 1999); and the total previous convictions among prisoners, prospectively assessed prerelease. The authors compared predischarge measures with subsequent offending and instruments ranked using multivariate regression. Most instruments demonstrated significant but moderate predictive ability. The OGRS ranked highest for violence among men, and the PCL–R and HCR-20 H subscale ranked highest for violence among women. The OGRS and total previous acquisitive convictions demonstrated greatest accuracy in predicting acquisitive offending among men and women. Actuarial instruments requiring no training to administer performed as well as personality assessment and structured risk assessment and were superior among men for violence. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Narrating personality change.

The present research investigated the longitudinal relations between personality traits and narratives. Specifically, the authors examined how individual differences in 170 college students' narratives of personality change (a) were predicted by personality traits at the beginning of college, (b) related to actual changes and perceived changes in personality traits during college, and (c) related to changes in emotional health during college. Individual differences in narratives of personality trait change told in the 4th year of college fell into 2 dimensions: affective processing, characterized by positive emotions, and exploratory processing, characterized by meaning making and causal processing. Conscientious, open, and extraverted freshmen told exploratory stories of change as seniors. Emotionally healthy freshmen told stories of change that were high in positive affect. Both positive affective and exploratory stories corresponded to change in emotional stability and conscientiousness during college above and beyond the effects of perceived changes in these traits. In addition, both positive affective and exploratory narratives corresponded to increases in emotional health during college independent of the effects of changes in personality traits. These findings improve our understanding of how individuals conceptualize their changing identity over time. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Structural aspects of chemisorption at Cu(110) revealed at the atomic level

We illustrate the impact that scanning tunnelling microscopy (STM) has made on our understanding of chemisorption and catalysis at metal surfaces at the atomic level by considering four examples where information from surface sensitive techniques was also available. The advantages of STM and the limitations of some of the other experimental methods are discussed. (1) Through a combination of STM and X-ray photoelectron spectroscopy (XPS) we have established that a number of distinct oxygen chemisorbed states can exist at a Cu(110) surface. These are metastable and temperature dependent. Furthermore, the presence of chemisorbed sulphur is shown to promote a specific oxygen state – isolated oxygen strings – which are likely to be more chemically reactive than the oxygen overlayer present at Cu(110). In this sense the sulphur is a structural promoter. (2) The oxidation of ammonia under ammonia-rich conditions results in the growth of imide (NH) strings at a Cu(110) surface and this has been followed quantitatively by STM. The reactive surface oxygen state participates in an oxydehydrogenation reaction generating NH-radical species which undergo surface diffusion and result in string growth. (3) Nitric oxide dissociates at Cu(110) to generate a two-phase system of chemisorbed nitrogen and oxygen adatoms. The oxygen is present in a well ordered (2 × 1) structure and the nitrogen in a (3 × 2) structure. The limitations of an earlier LEED study are discussed. (4) Structural aspects of chemisorbed sulphur generated by the dissociative chemisorption of hydrogen sulphide and methyl mercaptan are discussed. In the latter case carbon–sulphur bond cleavage results in the formation of a sulphide overlayer at 450 K with complete removal of carbon as desorbed hydrocarbons. Various sulphur structures have been delineated over a wide temperature range. This revised version was published online in August 2006 with corrections to the Cover Date.     

Photoconductivity in p-i-n Quantum Well Optical Modulators

Abstract

We have studied the temperature dependence of the current due to photoexcited carriers in p-i-n single quantum-well optical modulators, in order to ascertain the dominant transport mechanisms involved. A model describing the photocurrent is presented which includes the temperature and field dependence of the thermal emission, the tunnelling, the mobility and the recombination rate. A comparison between the experimental results and the model is also presented, outlining the probable transport processes.