Multi-robot allocation of assistance from a shared uncertain operator

Shared autonomy systems allow robots to either operate autonomously or request assistance from a human operator. In such settings, the human operator may exhibit sub-optimal behaviours, influenced by latent variables such as attention level or task proficiency. In this paper, we consider shared autonomy systems composed of multiple robots and one human. In this setting, we aim to synthesise a controller that selects, at each decision step, the actions to be taken by each robot and which (if any) robot the human operator should assist. To efficiently allocate the human operator to a robot at any given time, we propose a controller that reasons about the uncertainty over the latent variables impacting the human operator’s performance. To ensure scalability, we use an online bidding system, where each robot plans while considering its belief over the human’s performance, and bids according to the direct benefit of human assistance and how much information will be gained by the system about the human. We experiment on two domains, where we outperform approaches for allocation of human assistance that do not consider the human’s latent variables, and show that the performance of the overall system increases when robots consider the information gained by requesting human assistance when bidding

Integration and evaluation of a near-infrared camera utilizing a HgCdTe NICMOS3 array for the Mt. Palomar 200-inch Observatory

In this paper we describe the main subsystems that constitute the Mt. Palomar Prime Focus InfraRed Camera (PFIRCAM), together with some of the characterization data obtained for the focal plane array. This camera is currently a facility instrument at the 200-inch Mt. Palomar Observatory. It helps to satisfy the observational needs of astronomers in the spectral range of 1 micrometers to 2.5 micrometers by utilizing a HgCdTe NICMOS3 array. The camera has a plate scale of 0.54 arcsec/pixel for an overall FOV of 138 X 138 arcsec

Development and test of an IR camera for astronomical observation at the Palomar 200-inch observatory using the NICMOS II array

A NICMOS II array, a NIR (0.80 - 2.6 micron) imaging system, was integrated into the California Institute of Technology Palomar Observatory camera. The Palomar camera system which consists of six discrete subsystems including a focal plane, an electrical interface, data acquisition electronics, a dewar, dewar optics, and the software is described. The performance and calibration data for each subsystem are presented. Emphasis is placed on test data on the focal plane performance

Integration and evaluation of a near-infrared camera utilizing a HgCdTe NICMOS3 array for the Mt. Palomar 200-inch Observatory

In this paper we describe the main subsystems that constitute the Mt. Palomar Prime Focus InfraRed Camera (PFIRCAM), together with some of the characterization data obtained for the focal plane array. This camera is currently a facility instrument at the 200-inch Mt. Palomar Observatory. It helps to satisfy the observational needs of astronomers in the spectral range of 1 micrometers to 2.5 micrometers by utilizing a HgCdTe NICMOS3 array. The camera has a plate scale of 0.54 arcsec/pixel for an overall FOV of 138 X 138 arcsec

Development and test of an IR camera for astronomical observation at the Palomar 200-inch observatory using the NICMOS II array

A NICMOS II array, a NIR (0.80 - 2.6 micron) imaging system, was integrated into the California Institute of Technology Palomar Observatory camera. The Palomar camera system which consists of six discrete subsystems including a focal plane, an electrical interface, data acquisition electronics, a dewar, dewar optics, and the software is described. The performance and calibration data for each subsystem are presented. Emphasis is placed on test data on the focal plane performance

Genomic Islands of Speciation in Anopheles gambiae

The African malaria mosquito, Anopheles gambiae sensu stricto (A. gambiae), provides a unique opportunity to study the evolution of reproductive isolation because it is divided into two sympatric, partially isolated subtaxa known as M form and S form. With the annotated genome of this species now available, high-throughput techniques can be applied to locate and characterize the genomic regions contributing to reproductive isolation. In order to quantify patterns of differentiation within A. gambiae, we hybridized population samples of genomic DNA from each form to Affymetrix GeneChip microarrays. We found that three regions, together encompassing less than 2.8 Mb, are the only locations where the M and S forms are significantly differentiated. Two of these regions are adjacent to centromeres, on Chromosomes 2L and X, and contain 50 and 12 predicted genes, respectively. Sequenced loci in these regions contain fixed differences between forms and no shared polymorphisms, while no fixed differences were found at nearby control loci. The third region, on Chromosome 2R, contains only five predicted genes; fixed differences in this region were also verified by direct sequencing. These “speciation islands” remain differentiated despite considerable gene flow, and are therefore expected to contain the genes responsible for reproductive isolation. Much effort has recently been applied to locating the genes and genetic changes responsible for reproductive isolation between species. Though much can be inferred about speciation by studying taxa that have diverged for millions of years, studying differentiation between taxa that are in the early stages of isolation will lead to a clearer view of the number and size of regions involved in the genetics of speciation. Despite appreciable levels of gene flow between the M and S forms of A. gambiae, we were able to isolate three small regions of differentiation where genes responsible for ecological and behavioral isolation are likely to be located. We expect reproductive isolation to be due to changes at a small number of loci, as these regions together contain only 67 predicted genes. Concentrating future mapping experiments on these regions should reveal the genes responsible for reproductive isolation between forms

Comprehensive analysis of correlation coefficients estimated from pooling heterogeneous microarray data

Background The synthesis of information across microarray studies has been performed by combining statistical results of individual studies (as in a mosaic), or by combining data from multiple studies into a large pool to be analyzed as a single data set (as in a melting pot of data). Specific issues relating to data heterogeneity across microarray studies, such as differences within and between labs or differences among experimental conditions, could lead to equivocal results in a melting pot approach. Results We applied statistical theory to determine the specific effect of different means and heteroskedasticity across 19 groups of microarray data on the sign and magnitude of gene-to-gene Pearson correlation coefficients obtained from the pool of 19 groups. We quantified the biases of the pooled coefficients and compared them to the biases of correlations estimated by an effect-size model. Mean differences across the 19 groups were the main factor determining the magnitude and sign of the pooled coefficients, which showed largest values of bias as they approached ±1. Only heteroskedasticity across the pool of 19 groups resulted in less efficient estimations of correlations than did a classical meta-analysis approach of combining correlation coefficients. These results were corroborated by simulation studies involving either mean differences or heteroskedasticity across a pool of N \u3e 2 groups. Conclusions The combination of statistical results is best suited for synthesizing the correlation between expression profiles of a gene pair across several microarray studies

SWIRE: The SIRTF Wide‐Area Infrared Extragalactic Survey

The SIRTF Wide-Area Infrared Extragalactic Survey (SWIRE), the largest SIRTF Legacy program, is a wide-area imaging survey to trace the evolution of dusty, star-forming galaxies, evolved stellar populations, and active galactic nuclei (AGNs) as a function of environment, from redshifts to the current z ∼ 3 epoch. SWIRE will survey seven high-latitude fields, totaling 60–65 deg2 in all seven SIRTF bands: Infrared Array Camera (IRAC) 3.6, 4.5, 5.6, and 8 mm and Multiband Imaging Photometer for SIRTF (MIPS) 24, 70, and 160 mm. Extensive modeling suggests that the Legacy Extragalactic Catalog may contain in excess of 2 million IR-selected galaxies, dominated by (1) ∼150,000 luminous infrared galaxies (LIRGs; LFIR 1 1011 L,) detected by MIPS (and significantly more detected by IRAC), ∼7000 of these with ; (2) 1 million IRAC- z 1 2 detected early-type galaxies (∼ with and ∼10,000 with ); and (3) ∼20,000 classical AGNs 5 2 # 10 z 1 1 z 1 2 detected with MIPS, plus significantly more dust-obscured quasi-stellar objects/AGNs among the LIRGs. SWIRE will provide an unprecedented view of the evolution of galaxies, structure, and AGNs. The key scientific goals of SWIRE are (1) to determine the evolution of actively star forming and passively evolving galaxies in order to understand the history of galaxy formation in the context of cosmic structure formation; (2) to determine the evolution of the spatial distribution and clustering of evolved galaxies, starbursts, and AGNs in the key redshift range over which much of cosmic evolution has occurred; and (3) to 0.5 ! z ! 3 determine the evolutionary relationship between “normal galaxies” and AGNs and the contribution of AGN accretion energy versus stellar nucleosynthesis to the cosmic backgrounds. The large area of SWIRE is important to establish statistically significant population samples over enough volume cells that we can resolve the star formation history as a function of epoch and environment, i.e., in the context of structure formation. The large volume is also optimized for finding rare objects. The SWIRE fields are likely to become the next generation of large “cosmic windows” into the extragalactic sky. They have been uniquely selected to minimize Galactic cirrus emission over large scales. The Galaxy Evolution Explorer will observe them as part of its deep 100 deg2 survey, as will Herschel. SWIRE includes ∼9 deg2 of the unique large-area XMM Large Scale Structure hard X-ray imaging survey and is partly covered by the UKIDSS deep J and K survey. An extensive optical/near-IR imaging program is underway from the ground. The SWIRE data are nonproprietary; catalogs and images will be released twice yearly, beginning about 11 months after SIRTF launch. Details of the data products and release schedule are presented

Differential cross section measurements for the production of a W boson in association with jets in proton–proton collisions at √s = 7 TeV

Measurements are reported of differential cross sections for the production of a W boson, which decays into a muon and a neutrino, in association with jets, as a function of several variables, including the transverse momenta (pT) and pseudorapidities of the four leading jets, the scalar sum of jet transverse momenta (HT), and the difference in azimuthal angle between the directions of each jet and the muon. The data sample of pp collisions at a centre-of-mass energy of 7 TeV was collected with the CMS detector at the LHC and corresponds to an integrated luminosity of 5.0 fb[superscript −1]. The measured cross sections are compared to predictions from Monte Carlo generators, MadGraph + pythia and sherpa, and to next-to-leading-order calculations from BlackHat + sherpa. The differential cross sections are found to be in agreement with the predictions, apart from the pT distributions of the leading jets at high pT values, the distributions of the HT at high-HT and low jet multiplicity, and the distribution of the difference in azimuthal angle between the leading jet and the muon at low values.United States. Dept. of EnergyNational Science Foundation (U.S.)Alfred P. Sloan Foundatio

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis