Racing Multi-Objective Selection Probabilities

In the context of Noisy Multi-Objective Optimization, dealing with uncertainties requires the decision maker to define some preferences about how to handle them, through some statistics (e.g., mean, median) to be used to evaluate the qualities of the solutions, and define the corresponding Pareto set. Approximating these statistics requires repeated samplings of the population, drastically increasing the overall computational cost. To tackle this issue, this paper proposes to directly estimate the probability of each individual to be selected, using some Hoeffding races to dynamically assign the estimation budget during the selection step. The proposed racing approach is validated against static budget approaches with NSGA-II on noisy versions of the ZDT benchmark functions

Bagging ensemble selection for regression

Bagging ensemble selection (BES) is a relatively new ensemble learning strategy. The strategy can be seen as an ensemble of the ensemble selection from libraries of models (ES) strategy. Previous experimental results on binary classification problems have shown that using random trees as base classifiers, BES-OOB (the most successful variant of BES) is competitive with (and in many cases, superior to) other ensemble learning strategies, for instance, the original ES algorithm, stacking with linear regression, random forests or boosting. Motivated by the promising results in classification, this paper examines the predictive performance of the BES-OOB strategy for regression problems. Our results show that the BES-OOB strategy outperforms Stochastic Gradient Boosting and Bagging when using regression trees as the base learners. Our results also suggest that the advantage of using a diverse model library becomes clear when the model library size is relatively large. We also present encouraging results indicating that the non negative least squares algorithm is a viable approach for pruning an ensemble of ensembles

Can an influence graph driven by outage data determine transmission line upgrades that mitigate cascading blackouts?

We transform historically observed line outages in a power transmission network into an influence graph that statistically describes how cascades propagate in the power grid. The influence graph can predict the critical lines that are historically most involved in cascading propagation. After upgrading these critical lines, simulating the influence graph suggests that these upgrades could mitigate large blackouts by reducing the probability of large cascades

Robust fault detection for networked systems with communication delay and data missing

n this paper, the robust fault detection problem is investigated for a class of discrete-time networked systems with unknown input and multiple state delays. A novel measurement model is utilized to represent both the random measurement delays and the stochastic data missing phenomenon, which typically result from the limited capacity of the communication networks. The network status is assumed to vary in a Markovian fashion and its transition probability matrix is uncertain but resides in a known convex set of a polytopic type. The main purpose of this paper is to design a robust fault detection filter such that, for all unknown inputs, possible parameter uncertainties and incomplete measurements, the error between the residual signal and the fault signal is made as small as possible. By casting the addressed robust fault detection problem into an auxiliary robust H∞ filtering problem of a certain Markovian jumping system, a sufficient condition for the existence of the desired robust fault detection filter is established in terms of linear matrix inequalities. A numerical example is provided to illustrate the effectiveness and applicability of the proposed technique

Thermodynamic and transport properties of underdoped cuprates from ARPES data

he relationship between photoemission spectra of high-$T_{\textrm{c}}$ cuprates and their thermodynamic and transport properties are discussed. The doping dependence of the expected quasi-particle density at the Fermi level ($E_\mathrm{F}$) are compared with the electronic specific heat coefficient $\gamma$ and that of the spectral weight at $E_\mathrm{F}$ with the in-plane and out-of-plane superfluid density. We have estimated the electrical resistivity of underdoped cuprates from the momentum distribution curve (MDC) at $E_\mathrm{F}$ in the nodal direction. The temperature dependence of the MDC width is also consistent with that of the electrical resistivity.Comment: 14 pages, 4 figures, proceeding of International Symposium on Synchrotron Radiatin Research for Spin and Electronic States in d and f Electron Systems(SRSES2003

Distribution of spectral weight in a system with disordered stripes

The ``band-structure'' of a disordered stripe array is computed and compared, at a qualitative level, to angle resolved photoemission experiments on the cuprate high temperature superconductors. The low-energy states are found to be strongly localized transverse to the stripe direction, so the electron dynamics is strictly one-dimensional (along the stripe). Despite this, aspects of the two dimensional band-structure Fermi surface are still vividly apparent.Comment: 10 pages, 11 figure

Proton strangeness form factors in (4,1) clustering configurations

We reexamine a recent result within a nonrelativistic constituent quark model (NRCQM) which maintains that the uuds\bar s component in the proton has its uuds subsystem in P state, with its \bar s in S state (configuration I). When the result are corrected, contrary to the previous result, we find that all the empirical signs of the form factors data can be described by the lowest-lying uuds\bar s configuration with \bar s in P state that has its uuds subsystem in $S$ state (configuration II). Further, it is also found that the removal of the center-of-mass (CM) motion of the clusters will enhance the contributions of the transition current considerably. We also show that a reasonable description of the existing form factors data can be obtained with a very small probability P_{s\bar s}=0.025% for the uuds\bar s component. We further see that the agreement of our prediction with the data for G_A^s at low-q^2 region can be markedly improved by a small admixture of configuration I. It is also found that by not removing CM motion, P_{s\bar s} would be overestimated by about a factor of four in the case when transition dominates over direct currents. Then, we also study the consequence of a recent estimate reached from analyzing the existing data on quark distributions that P_{s\bar s} lies between 2.4-2.9% which would lead to a large size for the five-quark (5q) system, as well as a small bump in both G^s_E+\eta G^s_M and G^s_E in the region of q^2 =< 0.1 GeV^2.Comment: Prepared for The Fifth Asia-Pacific Conference on Few-Body Problems in Physics 2011 in Seoul, South Korea, 22-26 August 201

Single- and multi-walled carbon nanotubes viewed as elastic tubes with Young's moduli dependent on layer number

The complete energy expression of a deformed single-walled carbon nanotube (SWNT) is derived in the continuum limit from the local density approximation model proposed by Lenosky {\it et al.} \lbrack Nature (London) {\bf 355}, 333 (1992)\rbrack and shows to be content with the classic shell theory by which the Young's modulus, the Poisson ratio and the effective wall thickness of SWNTs are obtained as $Y=4.70$TPa, $\nu=0.34$, $h=0.75{\rm \AA}$, respectively. The elasticity of a multi-walled carbon nanotube (MWNT) is investigated as the combination of the above SWNTs of layer distance $d=3.4 {\rm \AA}$ and the Young's modulus of the MWNT is found to be an apparent function of the number of layers, $N$, varying from 4.70TPa to 1.04TPa for N=1 to $\infty$.Comment: 4 pages, 1 figur

Photosynthetic characteristics of summer maize under different planting patterns and the responses to nitrogen application of previous crop

Maize (Zea mays L.) is one of the most important grain crops in the North China Plain. Management practices affect the photosynthetic characteristics and the production of summer maize. This two-year (2014-2015) study examined the effects of different planting patterns and the application of nitrogen to previous winter wheat (Triticum aestivum L.) on the photosynthetic characteristics, yield and radiation use efficiency (RUE) of summer maize. Field experiments used a two-factor split-plot design with three replicates at Taian, Shandong Province, China (36°09′ N, 117°09′ E). The experiments involved two planting patterns (ridge planting, RP; and uniform row planting, UR) and two nitrogen application levels of previous winter wheat (N1, 112.50 kg ha-1; N2, 225.00 kg ha-1). The results indicated that the application of nitrogen on previous crop and ridge planting of the following crop had significant effects on the photosynthetic characteristics and yields of summer maize. Compared with UR, this study found that RP increased the chlorophyll content index (CCI), leaf area index (LAI), net photosynthetic rate (Pn), dry matter (DM), yield and grain RUE by 4.1%, 6.3%, 5.2%, 6.4%, 8.9% and 9.4%, respectively. The CCI, LAI, Pn, yield, and grain RUE of N2 were 9.7%, 3.3%, 3.7%, 10.0% and 10.1% higher than those of N1, respectively. RP combined with the application of nitrogen on previous crop of winter wheat could increase the CCI, LAI, Pn, DM, ultimately increasing the grain yield and RUE of the following summer’s maize. It was concluded that previous crop nitrogen application and RP pattern treatment resulted in optimal cropping conditions for the North China plain

Solar Magnetic Carpet I: Simulation of Synthetic Magnetograms

This paper describes a new 2D model for the photospheric evolution of the magnetic carpet. It is the first in a series of papers working towards constructing a realistic 3D non-potential model for the interaction of small-scale solar magnetic fields. In the model, the basic evolution of the magnetic elements is governed by a supergranular flow profile. In addition, magnetic elements may evolve through the processes of emergence, cancellation, coalescence and fragmentation. Model parameters for the emergence of bipoles are based upon the results of observational studies. Using this model, several simulations are considered, where the range of flux with which bipoles may emerge is varied. In all cases the model quickly reaches a steady state where the rates of emergence and cancellation balance. Analysis of the resulting magnetic field shows that we reproduce observed quantities such as the flux distribution, mean field, cancellation rates, photospheric recycle time and a magnetic network. As expected, the simulation matches observations more closely when a larger, and consequently more realistic, range of emerging flux values is allowed (4e16 - 1e19 Mx). The model best reproduces the current observed properties of the magnetic carpet when we take the minimum absolute flux for emerging bipoles to be 4e16 Mx. In future, this 2D model will be used as an evolving photospheric boundary condition for 3D non-potential modeling.Comment: 33 pages, 16 figures, 5 gif movies included: movies may be viewed at http://www-solar.mcs.st-and.ac.uk/~karen/movies_paper1