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Experimental Astronomy 2025年第3期59卷 1-111页

作者： Rauer, Heike Aerts, Conny Cabrera, Juan Deleuil, Magali Erikson, Anders Gizon, Laurent Goupil, Mariejo Heras, Ana Walloschek, Thomas Lorenzo-Alvarez, Jose Marliani, Filippo Martin-Garcia, César Mas-Hesse, J. Miguel O’Rourke, Laurence Osborn, Hugh Pagano, Isabella Piotto, Giampaolo Pollacco, Don Ragazzoni, Roberto Ramsay, Gavin Udry, Stéphane Appourchaux, Thierry Benz, Willy Brandeker, Alexis Güdel, Manuel Janot-Pacheco, Eduardo Kabath, Petr Kjeldsen, Hans Min, Michiel Santos, Nuno Smith, Alexis Suarez, Juan-Carlos Werner, Stephanie C. Aboudan, Alessio Abreu, Manuel Acuña, Lorena Adams, Moritz Adibekyan, Vardan Affer, Laura Agneray, François Agnor, Craig Aguirre Børsen-Koch, Victor Ahmed, Saad Aigrain, Suzanne Al-Bahlawan, Ashraf Alcacera Gil, Ma de los Angeles Alei, Eleonora Alencar, Silvia Alexander, Richard Alfonso-Garzón, Julia Alibert, Yann Allende Prieto, Carlos Almeida, Leonardo Alonso Sobrino, Roi Altavilla, Giuseppe Althaus, Christian Alvarez Trujillo, Luis Alonso Amarsi, Anish Ammler-von Eiff, Matthias Amôres, Eduardo Andrade, Laerte Antoniadis-Karnavas, Alexandros António, Carlos Aparicio del Moral, Beatriz Appolloni, Matteo Arena, Claudio Armstrong, David Aroca Aliaga, Jose Asplund, Martin Audenaert, Jeroen Auricchio, Natalia Avelino, Pedro Baeke, Ann Baillié, Kevin Balado, Ana Ballber Balagueró, Pau Balestra, Andrea Ball, Warrick Ballans, Herve Ballot, Jerome Barban, Caroline Barbary, Gaële Barbieri, Mauro Barceló Forteza, Sebastià Barker, Adrian Barklem, Paul Barnes, Sydney Barrado Navascues, David Barragan, Oscar Baruteau, Clément Basu, Sarbani Baudin, Frederic Baumeister, Philipp Bayliss, Daniel Bazot, Michael Beck, Paul G. Belkacem, Kevin Bellinger, Earl Benatti, Serena Benomar, Othman Bérard, Diane Bergemann, Maria Bergomi, Maria Bernardo, Pierre Biazzo, Katia Bignamini, Andrea Bigot, Lionel Billot, Nicolas Binet, Martin Biondi, David Biondi, Federico Birch, Aaron C. Bitsch, Bertram Bluhm Ceballos, Paz Victoria Bódi, Attila Bognár, Zsófia Boisse, Isabelle Bolmont, Emeline Bonanno, Alfio Bonavita, Institut für Planetenforschung Deutsches Zentrum für Luft- und Raumfahrt DLR Rutherfordstrasse 2 Berlin 12489 Germany Fachbereich Geowissenschaften Institut für Geologische Freie Universität Berlin Malteserstr. 74-100 Berlin 12249 Germany Institute of Astronomy KU Leuven Leuven Belgium CNRS CNES LAM Aix Marseille University Marseille France Max Planck Institute for Solar System Research Göttingen Germany LESIA Paris Observatory PSL University Sorbonne University Paris Cité University CNRS Meudon France ESTEC European Space Agency Noordwijk Netherlands ESAC European Space Agency Madrid Spain Centro de Astrobiología CSIC-INTA Campus ESAC Madrid Spain Center for Space and Habitability University of Bern Bern Switzerland INAF - Osservatorio Astrofisico di Catania Catania Italy Department of Physics and Astronomy University of Padua Padua Italy Department of Physics University of Warwick Coventry United Kingdom Astronomical Observatory of Padova INAF - Italian National Institute for Astrophysics Padua Italy Armagh Observatory and Planetarium College Hill Armagh United Kingdom Geneve Observatory University of Geneve Geneve Switzerland IAS University of Paris-Saclay Orsay France AlbaNove University Centre Stockholm University Stockholm Sweden Department of Astrophysics University of Vienna Vienna Austria Department of Astronomy University of Sao Paulo Sao Paulo Brazil Astronomical Institute of the Czech Academy of Sciences Ondřejov Czech Republic Department of Physics and Astronomy Aarhus University Aarhus Denmark Institute for Space Research SRON Leiden Netherlands Instituto de Astrofísica e Ciências do Espaço CAUP Universidade do Porto Porto Portugal Departamento de Física e Astronomia Faculdade da Ci ncias Universidade do Porto Porto Portugal Mullard Space Science Laboratory University College London Holmbury Saint Mary United Kingdom Dept. Theoretical Physics and the Cosmos University of Granada Granada Spain Centre for Plan

PLATO (PLAnetary Transits and Oscillations of stars) is ESA’s M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2REarth) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5%, 10%, 10% for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar system planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO‘s target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile towards the end of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases. © The Author(s) 2025.

关键词： Asteroseismology Exoplanets PLATO mission

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Application-level security for ROS-based applications

Application-level security for ROS-based applications

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IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Bernhard Dieber Severin Kacianka Stefan Rass Peter Schartner ROBOTICS institute at JOANNEUM RESEARCH Austria Software Engineering Group at the Technical University of Munich Germany System Security Group in the Institute of Applied Informatics at the Alpen-Adria-University Klagenfurt Austria

ISBN: (纸本)9781509037636

While the topic of security in industrial applications has gained some momentum in recent years, there are still severe security vulnerabilities which are actively exploited for attacks. The robot operating system (ROS) is expected to further grow in usage and to be used in many industrial applications. Analysis, however, shows that it lacks several security enhancements in order to make it suitable for industrial use. In its current state, false data and commands can be injected posing a possible safety risk for the resulting product and humans in the production. In addition, data may be eavesdropped and used by outsiders to gain insight into the production process. In this paper we propose a security architecture intended for use on top of ROS on the application level. We use a dedicated authorization server to ensure that only valid nodes are part of the application. Cryptographic methods ensure data confidentiality and integrity. We show in a demonstration with a collaborative robot how our architecture can be used to secure a ROS-based application.

关键词： Cryptography Authentication Production Digital signatures Service robots

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Research on Highly Consumable Platform for Business Analytics

Research on Highly Consumable Platform for Business Analytic...

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2016 IEEE International Conference on Progress in Informatics and Computing

作者： Qingwei Wu Zhen Gao Enzhong Wang Hong Min Zhihua Wei School of Software Engineering Tongji University System and Technology Group IBM T.J.Watson Research Center IBM Dept.of Computer Science and Technology Tongji University

Business analytics is an important means of gaining new insights and understanding of business performance. Data mining technology provides information needed by business analytics based on data. But due to the barriers of skill, resource and cost, business analytics is hard to carry out and put into practice for small and even medium sized enterprises. This paper presents a novel concept named Highly Consumable Business Analytics(HCBA) aiming to improve consumability of business analytics. We discuss the ways to simplify the use of data mining algorithms, establish end-to-end integrated lifecycle management of model and ultimately wrap models into web service to provide model-wise services. We propose a general reference architecture of HCBA. And a prototype is designed and implemented based on this architecture.

关键词： data mining model consumability R Spark MLlib

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An automated collaborative requirements engineering tool for better validation of requirements

An automated collaborative requirements engineering tool for...

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IEEE International Conference on Automated software engineering (ASE)

作者： Nor Aiza Moketar Massila Kamalrudin Safiah Sidek Mark Robinson John Grundy Innovative Software System and Services Group Universiti Teknikal Malaysia Melaka Melaka Malaysia Fulgent Corporation USA Faculty of Science Engineering and Built Environment Deakin University Victoria Australia

ISBN: (纸本)9781509055715

This demo introduces an automated collaborative requirements engineering tool, called TestMEReq, which is used to promote effective communication and collaboration between client-stakeholders and requirements engineers for better requirements validation. Our tool is augmented with real time communication and collaboration support to allow multiple stakeholders to collaboratively validate the same set of requirements. We have conducted a user study focusing on validating requirements using TestMEReq with a few groups of requirements engineers and client stakeholders. The study shows that our automated tool support is able to assist requirements engineers to effectively communicate with client-stakeholders to better validate the requirements virtually in real time. (Demo video: https://***/watch?v=7sWLOx-N4Jo).

关键词： Collaboration Stakeholders software Testing User interfaces Libraries Prototypes

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Representation and reproduction of skills to adapt affine variations in programming by demonstration

Representation and reproduction of skills to adapt affine va...

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International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

作者： Jaepyung Hwang Sang Hyoung Lee Il Hong Suh Department of Computer and Software Hanyang University Seoul Korea Smart System Research Group KITECH CheonAn ChungNam Korea Department of Electronics and Computer Engineering Hanyang University Seoul Korea

In this paper, we propose methods for representing and reproducing skills for a robot to adapt scale and position variations and external perturbations. The robot skill should be adaptable and reusable when there exist variation in scale and position (e.g. isotropic scaling, anisotropic scaling, rotation, deformation and so on) and under external perturbation. For example, consider a robot that learns the skill of drawing a square on a sketchpad placed on a table. The robot should be able to draw a square on a sketchpad moved in real-time and on a sketchpad placed at different angles and positions (e.g. a sketchpad hanging on the wall). The robot should also be able to draw a smaller or larger square using the same skill. It should also be able to draw deformed squares using the same skill, if the geometrical properties of the rectangle or the trapezoid are given. The most similar work for this was the method to use the product of the mixture models based on both global coordinated trajectory and the local coordinated trajectory [1]. Unlike the previous work, our representation afford each mixture model to be controllable by separately modeling one transformation matrix at one mixture model, not the whole mixture models. In our approach, the skill is first modeled as a Gaussian Mixture Model (GMM) using training data. Based on geometric interpretation of the GMM, its mixture components are represented as the priors, the means, and the eigenvectors and eigenvalues of the covariances. This is because the means and the covariances need to be geometrically transformed according to variations and perturbations (see Fig. 1 (b)-(d)). A skill is represented by combining the set of these mixture components with the transformation matrices. The skill is renewed by transforming mixture components based on the transformation matrices that are constructed to reflect the variations and the perturbations. We also propose a method for reproducing a skill that is based on a dynamica

关键词： Deformable models

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Finding database contention hotspots under large-scale workloads - A big data approach

Finding database contention hotspots under large-scale workl...

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IEEE International Conference on Big Data Analysis (ICBDA)

作者： An Lei Ping Sun Weixiong Rao Hong Min Gong Su Zhenhua Dong School of Software Engineering Tongji University Shanghai China IBM T. J. Watson Research Center Yorktown Heights NY USA IBM System and Technology Group Beijing China

ISBN: (纸本)9781467395922

Database plays an important role in transactional information systems. One significant performance impacting factor is data lock contention in transaction processing. In order to guide better database design, we propose a novel solution to identify contention hotspots displayed in DBMS transaction logs. To analyze the large volume of data collected in the transaction log, our solution employees big data engine Spark for better computation performance and scalability. A novel algorithm is also introduced to optimize computation for analyzing hotspots in the distributed cluster. The experimental results from a benchmark OLTP workload demonstrate the effectiveness and high scalability of our solution.

关键词： Sparks Algorithm design and analysis Scalability Clustering algorithms Engines Distributed databases

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Towards the automatic verification of behavior preservation at the transformation level for operational model transformations 4

Towards the automatic verification of behavior preservation ...

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4th Workshop on the Analysis of Model Transformations, AMT 2015 - co-located with the 18th International Conference on Model Driven engineering Languages and systems, MODELS 2015

作者： Dyck, Johannes Giese, Holger Lambers, Leen Schlesinger, Sebastian Glesner, Sabine System Analysis and Modeling Group Hasso Plattner Institute at the University of Potsdam Germany Software Engineering for Embedded Systems Technical University of Berlin Germany

The correctness of model transformations and, in particular, behavior preservation is important for model-driven engineering of high quality software. Behavior preservation verification techniques have been pre-sented with automatic tool support for the instance level, i.e. for a given source and target model specified by the model transformation. However, up until now there is no automatic verification approach avail-able for operational model transformations at the transformation level, i.e. for all source and target models specified by an operational model transformation. In this paper, we outline a first approach towards the automatic verification of behavior preservation for operational model transformations at the transformation level extending our previous re-sults for relational model transformations. In particular, we show that in restricted cases the behavior preservation problem for an operational model transformation can be reduced to invariant checking for graph transformation with priorities illustrated by a simple example.

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Research on highly consumable platform for business analytics

Research on highly consumable platform for business analytic...

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IEEE International Conference on Progress in Informatics and Computing (PIC)

作者： Qingwei Wu Zhen Gao Enzhong Wang Hong Min Zhihua Wei School of Software Engineering Tongji University Shanghai China System and Technology Group IBM Beijing China T. J. Watson Research Center IBM Yorktown Heights NY USA Dept. of Computer Science and Technology Tongji University Shanghai China

ISBN: (纸本)9781509034857

Business analytics is an important means of gaining new insights and understanding of business performance. Data mining technology provides information needed by business analytics based on data. But due to the barriers of skill, resource and cost, business analytics is hard to carry out and put into practice for small and even medium sized enterprises. This paper presents a novel concept named Highly Consumable Business Analytics (HCBA) aiming to improve consumability of business analytics. We discuss the ways to simplify the use of data mining algorithms, establish end-to-end integrated lifecycle management of model and ultimately wrap models into web service to provide model-wise services. We propose a general reference architecture of HCBA. And a prototype is designed and implemented based on this architecture.

关键词： Data models Data mining Business Production facilities Servers Engines Web services

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Cognitive science based scheduling in grid environment

Advances in Intelligent Systems and Computing

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Advances in Intelligent systems and Computing 2015年 330卷 199-203页

作者： Iswarya, N.D. Mohamed, M. A. Maluk Vijaya, N. Software System Group Dept of CSE MAM College of Engineering TiruchirappalliTamil Nadu India Software System Group M.A.M college of engineering TiruchirappalliTamil Nadu India

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Digital health technologies in the accelerating medicines Partnership® Schizophrenia Program

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Schizophrenia (Heidelberg, Germany) 2025年第1期11卷 83页

作者： Johanna T W Wigman Ann Ee Ching Yoonho Chung Habiballah Rahimi Eichi Erlend Lane Carsten Langholm Aditya Vaidyam Andrew Jin Soo Byun Anastasia Haidar Jessica Hartmann Angela Nunez Dominic Dwyer Adibah Amani Nasarudin Owen Borders Isabelle Scott Zailyn Tamayo Priya Matneja Kang-Ik Cho Jean Addington Luis K Alameda Celso Arango Nicholas J K Breitborde Matthew R Broome Kristin S Cadenhead Monica E Calkins Eric Yu Hai Chen Jimmy Choi Philippe Conus Cheryl M Corcoran Barbara A Cornblatt Covadonga M Diaz-Caneja Lauren M Ellman Paolo Fusar-Poli Pablo A Gaspar Carla Gerber Louise Birkedal Glenthøj Leslie E Horton Christy Lai Ming Hui Joseph Kambeitz Lana Kambeitz-Ilankovic Matcheri S Keshavan Sung-Wan Kim Nikolaos Koutsouleris Kerstin Langbein Daniel Mamah Daniel H Mathalon Vijay A Mittal Merete Nordentoft Godfrey D Pearlson Jesus Perez Diana O Perkins Albert R Powers Jack Rogers Fred W Sabb Jason Schiffman Jai L Shah Steven M Silverstein Stefan Smesny Walid Yassin William S Stone Gregory P Strauss Judy L Thompson Rachel Upthegrove Swapna Verma Jijun Wang Daniel H Wolf Phillip Wolff Laura M Rowland Simon D'Alfonso Ofer Pasternak Sylvain Bouix Patrick D McGorry Rene S Kahn John M Kane Carrie E Bearden Scott W Woods Martha E Shenton Barnaby Nelson Justin T Baker John Torous University of Groningen University Medical Center Groningen Department of Psychiatry Interdisciplinary Centre of Psychopathology and Emotion regulation Groningen The Netherlands. Centre for Youth Mental Health The University of Melbourne Parkville VIC Australia. Orygen Parkville VIC Australia. McLean Hospital Belmont MA USA. Harvard Medical School Boston MA USA. Beth Israel Deaconess Medical Center Harvard Medical School Boston MA USA. Brigham and Women's Hospital Harvard Medical School Boston MA USA. Yale University New Haven CT USA. Northwell Health Glen Oaks NY USA. Department of Psychiatry Hotchkiss Brain Institute University of Calgary Calgary AB Canada. Service de Psychiatrie Générale Dép. de Psychiatrie CHUV Lausanne Lausanne Switzerland. Department of Child and Adolescent Psychiatry Institute of Psychiatry and Mental Health Hospital General Universitario Gregorio Marañón Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM) CIBERSAM ISCIII School of Medicine Universidad Complutense Madrid Spain. Department of Psychiatry and Behavioral Health Ohio State University Columbus OH USA. Department of Psychology Ohio State University Columbus OH USA. Institute for Mental Health School of Psychology University of Birmingham Birmingham UK. Birmingham Women's and Children's NHS Foundation Trust Birmingham UK. University of California San Diego CA USA. Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Psychiatry School of Clinical Medicine Li Ka Shing Faculty of Medicine University of Hong Kong Hong Kong Hong Kong. Olin Neuropsychiatry Research Center Hartford HealthCare Behavioral Health Network Hartford CT USA. Department of Psychiatry Icahn School of Medicine at Mount Sinai New York NY USA. Department of Psychiatry Donald and Barbara Zucker School of Medicine Hempstead NY USA. Feinstein Institute for Medical Research Manhasset NY USA. Department of Psych

Although meta-analytic studies have shown that 25-33% of those at Clinical High Risk (CHR) for psychosis transition to a first episode of psychosis within three years, less is known about estimating the risk of transition at an individual level. Digital phenotyping offers a novel approach to explore the nature of CHR and may help to improve personalized risk prediction. Specifically, digital data enable detailed mapping of experiences, moods and behaviors during longer periods of time (e.g., weeks, months) and offer more insight into patterns over time at the individual level across their routine daily life. However, while novel digital health technologies open up many new avenues of research, they also come with specific challenges, including replicability of results and the adherence of participants. This paper outlines the design of the digital component of the Accelerating Medicines Partnership® Schizophrenia Program (AMP SCZ) project, a large international collaborative project that follows individuals at CHR for psychosis over a period of two years. The digital component comprises one-year smartphone-based digital phenotyping and actigraphy. Smartphone-based digital phenotyping includes 30-item short daily self-report surveys and voice diaries as well as passive data capture (geolocation, on/off screen state, and accelerometer). Actigraphy data are collected via an Axivity wristwatch. The aim of this paper is to describe the design and the three goals of the digital measures used in AMP SCZ to: (i) better understand the symptoms, real-life experiences, and behaviors of those at CHR for psychosis, (ii) improve the prediction of transition to psychosis and other health outcomes in this population based on digital phenotyping and, (iii) serve as an example for replicable and ethical research across geographically diverse regions and cultures. Accordingly, we describe the rationale, protocol and implementation of these digital components of the AMP SCZ project. **

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