ROSAT HRI catalogue of X-ray sources in the LMC region

All 543 pointed observations of the ROSAT High Resolution Imager (HRI) with exposure times higher than 50 sec in a field of 10 deg x 10 deg covering the Large Magellanic Cloud (LMC) were analyzed. A catalogue was produced containing 397 X-ray sources with their properties measured by the HRI. The list was cross-correlated with the ROSAT Position Sensitive Propotional Counter (PSPC) source catalogue presented by Haberl & Pietsch (1999), the SIMBAD data base, and the TYCHO catalogue. 138 HRI sources are contained in the PSPC catalogue. The spatial resolution of the HRI was higher than that of the PSPC and the source position could be determined with errors mostly smaller than 15 arcsec which are dominated by systematic attitude errors. 94 HRI sources were identified with known objects based on their positional coincidence and X-ray properties. The catalogue contains 39 foreground stars, 24 supernova remnants (SNRs), five supersoft sources (SSSs), nine X-ray binaries (XBs), and nine AGN well known from literature. Another eight sources were identified with known candidates for these source classes. Additional 21 HRI sources are suggested in the present work as candidates for SNR, X-ray binary in the LMC, or background AGN because of their extent, hardness ratios, X-ray to optical flux ratio, or flux variability.Comment: 22 pages, 8 figures, 4 table

Comparing human robot interaction scenarios using live and video based methods: towards a novel methodological approach

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.---- Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. DOI : 10.1109/AMC.2006.1631754This paper presents results of a pilot study that investigated whether people’s perceptions from live and video HRI trials were comparable. Subjects participated in a live HRI trial and videotaped HRI trials in which the scenario for both trials was identical, and involved a robot fetching an object using different approach directions. Results of the trials indicated moderate to high levels of agreement for subjects’ preferences, and opinions for both the live and video based HRI trials. This methodology is in its infancy and should not be seen as a replacement for live trials. However, our results indicate that for certain HRI scenarios videotaped trials do have potential as a technique for prototyping, testing, developing HRI scenarios, and testing methodologies for use in definitive live trials

Adaptive evolution is substantially impeded by Hill–Robertson interference in Drosophila

Hill–Robertson interference (HRi) is expected to reduce the efficiency of natural selection when two or more linked selected sites do not segregate freely, but no attempt has been done so far to quantify the overall impact of HRi on the rate of adaptive evolution for any given genome. In this work, we estimate how much HRi impedes the rate of adaptive evolution in the coding genome of Drosophila melanogaster. We compiled a data set of 6,141 autosomal protein-coding genes from Drosophila, from which polymorphism levels in D. melanogaster and divergence out to D. yakuba were estimated. The rate of adaptive evolution was calculated using a derivative of the McDonald–Kreitman test that controls for slightly deleterious mutations. We find that the rate of adaptive amino acid substitution at a given position of the genome is positively correlated to both the rate of recombination and the mutation rate, and negatively correlated to the gene density of the region. These correlations are robust to controlling for each other, for synonymous codon bias and for gene functions related to immune response and testes. We show that HRi diminishes the rate of adaptive evolution by approximately 27%. Interestingly, genes with low mutation rates embedded in gene poor regions lose approximately 17% of their adaptive substitutions whereas genes with high mutation rates embedded in gene rich regions lose approximately 60%. We conclude that HRi hampers the rate of adaptive evolution in Drosophila and that the variation in recombination, mutation, and gene density along the genome affects the HRi effect

ROSAT-HRI detection of the Class I protostar YLW16A in the rho Ophiuchi dark cloud

I analyze unpublished or partially published archival ROSAT data of the rho Ophiuchi dark cloud. This set of seven overlapping ROSAT HRI pointings, composed of eight ~one-hour exposures, detects mainly the X-ray brightest T Tauri stars of this star-forming region. Only two HRI sources are new X-ray sources, and their optical counterparts are proposed as new Weak T Tauri star candidates. Meanwhile the ROSAT HRI caught during just one exposure a weak X-ray source (maximum likelihood=10; SNR=4.1\sigma for Gaussian statistics) among a group of three embedded young stellar objects including two Class I protostars. Previous ROSAT PSPC, ASCA GIS observations, and as I argue here one Einstein IPC observation, have already detected an X-ray source in this area, but this higher angular resolution data show clearly that X-rays are emitted by the Class I protostar YLW16A. This is the second Class I protostar detected by the ROSAT HRI in this dark cloud. The determination of the intrinsic X-ray luminosity of this event, L_X[0.1-2.4 keV]=(9.4-450)*1E30 erg/s, critically depends on the source absorption estimate. Improvements will be obtained only by the direct determination of this parameter from fitting of Chandra and XMM-Newton spectra.Comment: 4 pages, 2 figures, 2 tables. Accepted for publication in A&

Facial expressions emotional recognition with NAO robot

Human-robot interaction research is diverse and covers a wide range of topics. All aspects of human factors and robotics are within the purview of HRI research so far as they provide insight into how to improve our understanding in developing effective tools, protocols, and systems to enhance HRI. For example, a significant research effort is being devoted to designing human-robot interface that makes it easier for the people to interact with robots. HRI is an extremely active research field where new and important work is being published at a fast pace. It is crucial for humanoid robots to understand the emotions of people for efficient human robot interaction. Initially, the robot detects human face by Viola- Jones technique. Later, facial distance measurements are accumulated by geometric based facial distance measurement method. Then facial action coding system is used to detect movements of measured facial points. Finally, measured facial movements are evaluated to get instant emotional properties of human face in this research; it has been specifically applied to NAO humanoid robot

Post-test questionnaire - HRI 1

This questionnaire has been used within the experiments described in a forthcoming publication in order to assess participants' conscious assessment of the quality of the interaction they have experienced with the robot. The questionnaire is based on two established questionnaires assessing participants' perception of `presence': the Temple Presence Inventory (TPI), and the Networked Minds Social Presence Inventory (NMI

Alternative model-building for the study of socially interactive robots

In this discussion paper, we consider the potential merits of applying an alternative approach to model building (Empirical Modelling, also known as EM) in studying social aspects of human-robot interaction (HRI). The first section of the paper considers issues in modelling for HRI. The second introduces EM principles, outlining their potential application to modelling for HRI and its implications. The final section examines the prospects for applying EM to HRI from a practical perspective with reference to a simple case study and to existing models

Multimodal Signal Processing and Learning Aspects of Human-Robot Interaction for an Assistive Bathing Robot

We explore new aspects of assistive living on smart human-robot interaction (HRI) that involve automatic recognition and online validation of speech and gestures in a natural interface, providing social features for HRI. We introduce a whole framework and resources of a real-life scenario for elderly subjects supported by an assistive bathing robot, addressing health and hygiene care issues. We contribute a new dataset and a suite of tools used for data acquisition and a state-of-the-art pipeline for multimodal learning within the framework of the I-Support bathing robot, with emphasis on audio and RGB-D visual streams. We consider privacy issues by evaluating the depth visual stream along with the RGB, using Kinect sensors. The audio-gestural recognition task on this new dataset yields up to 84.5%, while the online validation of the I-Support system on elderly users accomplishes up to 84% when the two modalities are fused together. The results are promising enough to support further research in the area of multimodal recognition for assistive social HRI, considering the difficulties of the specific task. Upon acceptance of the paper part of the data will be publicly available