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TOI-2458 b: A mini-Neptune consistent with in situ hot Jupiter formation

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arXiv 2024年

作者： Šubjak, Jan Gandolfi, Davide Goffo, Elisa Rapetti, David Jankowski, Dawid Mizuki, Toshiyuki Dai, Fei Serrano, Luisa M. Wilson, Thomas G. Goździewski, Krzysztof Nowak, Grzegorz Jenkins, Jon M. Twicken, Joseph D. Winn, Joshua N. Bieryla, Allyson Ciardi, David R. Cochran, William D. Collins, Karen A. Deeg, Hans J. Garcia, Rafael A. Guenther, Eike W. Hatzes, Artie P. Kabath, Petr Korth, Judith Latham, David W. Livingston, John H. Lund, Michael B. Mathur, Savita Narita, Norio Orell-Miquel, Jaume Palle, Enric Persson, Carina M. Redfield, Seth Schwarz, Richard P. Watanabe, David Ziegler, Carl Astronomical Institute Czech Academy of Sciences Fričova 298 Ondřejov251 65 Czech Republic Center for Astrophysics | Harvard & Smithsonian 60 Garden Street CambridgeMA02138 United States Dipartimento di Fisica Universita degli Studi di Torino via Pietro Giuria 1 TorinoI-10125 Italy Thuringer Landessternwarte Tautenburg Sternwarte 5 Tautenburg07778 Germany NASA Ames Research Center Moffett FieldCA94035 United States Research Institute for Advanced Computer Science Universities Space Research Association WashingtonDC20024 United States Institute of Astronomy Faculty of Physics Astronomy and Informatics Nicolaus Copernicus University Grudziadzka 5 Toruń87-100 Poland Astrobiology Center of NINS 2-21-1 Osawa Mitaka Tokyo181-8588 Japan National Astronomical Observatory of Japan 2-21-2 Osawa Mitaka Tokyo181-8588 Japan Institute for Astronomy University of Hawai'i 2680 Woodlawn Drive HonoluluHI96822 United States Department of Physics University of Warwick Gibbet Hill Road CoventryCV4 7AL United Kingdom SETI Institute Mountain ViewCA94043 United States Department of Astrophysical Sciences Princeton University PrincetonNJ08544 United States NASA Exoplanet Science Institute-Caltech/IPAC PasadenaCA91125 United States McDonald Observatory The University of Texas AustinTX United States Center for Planetary Systems Habitability The University of Texas AustinTX United States C. Via Lactea S/N Tenerife La LagunaE-38205 Spain Dept. de Astrofisica Tenerife La LagunaE-38206 Spain Universite Paris-Saclay Universite Paris Cite CEA CNRS AIM Gif-sur-Yvette91191 France Lund Observatory Division of Astrophysics Department of Physics Lund University Box 118 Lund22100 Sweden Astronomical Science Program Graduate University for Advanced Studies SOKENDAI 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Komaba Institute for Science The University of Tokyo 3-8-1 Komaba Meguro Tokyo153-8902 Japan Chalmers University of Technology Departmen

We report on the discovery and spectroscopic confirmation of TOI-2458 b, a transiting mini-Neptune around an F-type star leaving the mainsequence with a mass of M*= 1.05 ± 0.03Mo, a radius of R*= 1.31 ± 0.03 Ro, an effective temperature of Teff = 6005 ± 50 K, and a metallicity of -0.10 ± 0.05 dex. By combining TESS photometry with high-resolution spectra acquired with the HARPS spectrograph, we found that the transiting planet has an orbital period of ∼3.74 days, a mass of Mp = 13.31±0.99M⊕ and a radius of Rp = 2.83±0.20 R⊕. The host star TOI-2458 shows a short activity cycle of ∼54 days revealed in the HARPS S-index and Hα times series. We took the opportunity to investigate other F stars showing activity cycle periods comparable to that of TOI-2458 and found that they have shorter rotation periods than would be expected based on the gyrochronology predictions. In addition, we determined TOI-2458's stellar inclination angle to be i*= 10.6+13.3 -10.6 degrees. We discuss that both phenomena (fast stellar rotation and planet orbit inclination) could be explained by in situ formation of a hot Jupiter interior to TOI-2458 b. It is plausible that this hot Jupiter was recently engulfed by the star. Analysis of HARPS spectra has identified the presence of another planet with a period of P = 16.55 ± 0.06 days and a minimum mass of Mp sin i = 10.22 ± 1.90M⊕. Using dynamical stability analysis, we constrained the mass of this planet to the range Mc (10, 25)M⊕. © 2024, CC BY.

关键词： Stars

Thermal Image Enhancement Algorithm Using Local And Global Logarithmic Transform Histogram Matching With Spatial Equalization

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Thermal Image Enhancement Algorithm Using Local And Global L...

IEEE Southwest Symposium on Image Analysis and Interpretation

作者： Viacheslav Voronin Svetlana Tokareva Evgenii Semenishchev Sos Agaian Lab. "Mathematical methods of image processing and intelligent computer vision systems" Don State Technical University Rostov-on-Don Russian Federation Dept. of Computer Science CUNY/The College of Staten Island Staten Island New York United States

This paper presents a new thermal image enhancement algorithm based on combined local and global image processing in the frequency domain. The presented approach uses the fact that the relationship between stimulus and perception is logarithmic. The basic idea is to apply logarithmic transform histogram matching with spatial equalization approach on different image blocks. The resulting image is a weighted mean of all processing blocks. The weights for every local and global enhanced image driven through optimization of measure of enhancement (EME). Some presented experimental results illustrate the performance of the proposed algorithm on real thermal images in comparison with the traditional methods.

关键词： Histograms Transforms Image enhancement Adaptive equalizers Frequency-domain analysis computer vision

A value driven agent: Instantiation of a case-supported principle-based behavior paradigm 31

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A value driven agent: Instantiation of a case-supported prin...

31st AAAI Conference on Artificial Intelligence, AAAI 2017

作者： Anderson, Michael Anderson, Susan Leigh Berenz, Vincent Dept. of Computer Science University of Hartford West HartfordCT United States Dept. of Philosophy University of Connecticut StorrsCT United States Autonomous Motion Dept. Max Planck Institute for Intelligent Systems Tuebingen Germany

ISBN: (纸本)9781577357865

We have implemented a simulation of a robot functioning in the domain of eldercare whose behavior is completely determined by an ethical principle. Using a subset of the perceptions and duties that will be required of such a robot, this simulation demonstrates selection of ethically preferable actions in real time using a case-supported principle-based paradigm. We believe that this work could serve as the basis for ensuring that the behavior of all eldercare robots that are created in the future will be ethically justifiable. Further, we believe that the methods used in this project can be employed in other domains as well, to ensure that the robots that humans interact with in these domains will behave ethically. © Copyright 2017, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Human robot interaction

Symbol Emergence in Cognitive Developmental systems: A Survey

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arXiv 2018年

作者： Taniguchi, Tadahiro Ugur, Emre Hoffmann, Matej Jamone, Lorenzo Nagai, Takayuki Rosman, Benjamin Matsuka, Toshihiko Iwahashi, Naoto Oztop, Erhan Piater, Justus Wörgötter, Florentin College of Information Science and Engineering Ritsumeikan University 1-1-1 Noji Higashi Shiga Kusatsu525-8577 Japan Dept. of Computer Engineering Bogazici University Istanbul Turkey Dept. Cybernetics Faculty of Electrical Engineering Czech Technical University Prague Czech Republic School of Electronic Engineering and Computer Science Queen Mary University of London United Kingdom Faculty of Informatics and Engineering The University of Electro-communications Japan Mobile Intelligent Autonomous Systems The Council for Scientific and Industrial Research The School of Computer Science and Applied Mathematics The University of the Witwatersrand South Africa Department of Cognitive and Information Science Chiba University Japan Faculty of Computer Science and Systems Engineering Okayama Prefectural University Japan Dept. of Computer Science Ozyegin University Istanbul Turkey The Dept. of Computer Science Universität Innsbruck Austria The Department for Computational Neuroscience The Bernstein Center of the University of Göttingen Inst. F. Physics Iii Germany

Humans use signs, e.g., sentences in a spoken language, for communication and thought. Hence, symbol systems like language are crucial for our communication with other agents and adaptation to our real-world environment. The symbol systems we use in our human society adaptively and dynamically change over time. In the context of artificial intelligence (AI) and cognitive systems, the symbol grounding problem has been regarded as one of the central problems related to symbols. However, the symbol grounding problem was originally posed to connect symbolic AI and sensorimotor information and did not consider many interdisciplinary phenomena in human communication and dynamic symbol systems in our society, which semiotics considered. In this paper, we focus on the symbol emergence problem, addressing not only cognitive dynamics but also the dynamics of symbol systems in society, rather than the symbol grounding problem. We first introduce the notion of a symbol in semiotics from the humanities, to leave the very narrow idea of symbols in symbolic AI. Furthermore, over the years, it became more and more clear that symbol emergence has to be regarded as a multifaceted problem. Therefore, secondly, we review the history of the symbol emergence problem in different fields, including both biological and artificial systems, showing their mutual relations. We summarize the discussion and provide an integrative viewpoint and comprehensive overview of symbol emergence in cognitive systems. Additionally, we describe the challenges facing the creation of cognitive systems that can be part of symbol emergence systems. Copyright © 2018, The Authors. All rights reserved.

关键词： Cognitive systems

A conditional gradient framework for composite convex minimization with applications to semidefinite programming

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arXiv 2018年

作者： Yurtsever, Alp Fercoq, Olivier Locatello, Francesco Cevher, Volkan LIONS Ecole Polytechnique Fédérale de Lausanne Switzerland LTCI Télécom ParisTech Université Paris-Saclay France BMI Dept. of Computer Science ETH Zurich Switzerland Empirical Inference Max Planck Institute for Intelligent Systems Germany

We propose a conditional gradient framework for a composite convex minimization template with broad applications. Our approach combines smoothing and homotopy techniques under the CGM framework, and provably achieves the optimal O(1/√k) convergence rate. We demonstrate that the same rate holds if the linear subproblems are solved approximately with additive or multiplicative error. In contrast with the relevant work, we are able to characterize the convergence when the non-smooth term is an indicator function. Specific applications of our framework include the non-smooth minimization, semidefinite programming, and minimization with linear inclusion constraints over a compact domain. Numerical evidence demonstrates the benefits of our framework. Copyright © 2018, The Authors. All rights reserved.

关键词： Machine learning

Smart Cloud System for Forensic Thermal Image Enhancement Using Local and Global Logarithmic Transform Histogram Matching

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Smart Cloud System for Forensic Thermal Image Enhancement Us...

IEEE International Conference on Smart Cloud (SmartCloud)

作者： Viacheslav Voronin Evgenii Semenishchev Vladimir Frants Sos Agaian Lab. “Mathematical methods of image processing and intelligent computer vision systems” Don State Technical University Rostov-on-Don Russian Federation “STANKIN” Moscow State University of Technology Moscow Russian Federation Dept. of Computer Science CUNY/The College of Staten Island Staten Island New York United States

Digital images used in the investigation of a crime often undergo several concurrent enhancement operations for improved automated analysis. The challenges are related to the big size of data and complexity of the forensic image processing. Our purpose is providing a smart cloud system to image processing for PC and Smartphones with limited computation complexity. This paper presents a new thermal image enhancement algorithm based on combined local and global image processing in the frequency domain. The presented approach uses the fact that the relationship between stimulus and perception is logarithmic. The basic idea is to apply logarithmic transform histogram matching with spatial equalization approach on different image blocks. The resulting image is a weighted mean of all processing blocks. The weights for every local and global enhanced image driven through optimization of measure of enhancement (EME). Some presented experimental results illustrate the performance of the proposed cloud system on real thermal images in comparison with the traditional methods.

关键词： Histograms Transforms Image enhancement Forensics Adaptive equalizers Clouds

Detailed, accurate, human shape estimation from clothed 3D scan sequences

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arXiv 2017年

作者： Zhang, Chao Pujades, Sergi Black, Michael Pons-Moll, Gerard MPI for Intelligent Systems Tübingen Germany Dept. of Computer Science University of York United Kingdom

We address the problem of estimating human pose and body shape from 3D scans over time. Reliable estimation of 3D body shape is necessary for many applications including virtual try-on, health monitoring, and avatar creation for virtual reality. Scanning bodies in minimal clothing, however, presents a practical barrier to these applications. We address this problem by estimating body shape under clothing from a sequence of 3D scans. Previous methods that have exploited body models produce smooth shapes lacking personalized details. We contribute a new approach to recover a personalized shape of the person. The estimated shape deviates from a parametric model to fit the 3D scans. We demonstrate the method using high quality 4D data as well as sequences of visual hulls extracted from multi-view images. We also make available BUFF, a new 4D dataset that enables quantitative evaluation http://***/. Our method outperforms the state of the art in both pose estimation and shape estimation, qualitatively and quantitatively. Copyright © 2017, The Authors. All rights reserved.

关键词： Virtual reality

CHAOS Challenge - Combined (CT-MR) healthy abdominal organ segmentation

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arXiv 2020年

作者： Kavur, A. Emre Gezer, N. Sinem Barış, Mustafa Conze, Pierre-Henri Groza, Vladimir Pham, Duc Duy Chatterjee, Soumick Ernst, Philipp Özkan, Savaş Baydar, Bora Lachinov, Dmitry Han, Shuo Pauli, Josef Isensee, Fabian Perkonigg, Matthias Sathish, Rachana Rajan, Ronnie Aslan, Sinem Sheet, Debdoot Dovletov, Gurbandurdy Speck, Oliver Nürnberger, Andreas Maier-Hein, Klaus H. Akar, Gözde Bozdagı Ünal, Gözde Dicle, Oguz Selver, M. Alper Graduate School of Natural and Applied Sciences Dokuz Eylul University Izmir Turkey Department of Radiology Faculty Of Medicine Dokuz Eylul University Izmir Turkey Dept. of Ophthalmology and Optometry Medical Uni. of Vienna Austria Intelligent Systems Faculty of Engineering University of Duisburg-Essen Germany Division of Medical Image Computing German Cancer Research Center Heidelberg Germany CIR Lab Dept of Biomedical Imaging and Image-guided Therapy Medical Uni. of Vienna Austria IMT Atlantique LaTIM UMR 1101 Brest France Department of Electrical and Electronics Engineering Middle East Technical University Ankara Turkey Department of Electrical Engineering Indian Institute of Technology Kharagpur India School of Medical Science and Technology Indian Institute of Technology Kharagpur India Ca’ Foscari University of Venice ECLT DAIS Venice Italy Ege University International Computer Institute Izmir Turkey Johns Hopkins University Baltimore United States Data and Knowledge Engineering Group Otto von Guericke University Magdeburg Germany Magnetic Resonance Otto von Guericke University Magdeburg Germany Median Technologies Valbonne France Department of Computer Engineering Istanbul Technical University Istanbul Turkey Department of Electrical and Electronics Engineering Dokuz Eylul University Izmir Turkey

—Segmentation of abdominal organs has been a comprehensive, yet unresolved, research field for many years. In the last decade, intensive developments in deep learning (DL) have introduced new state-of-the-art segmentation systems. Despite outperforming the overall accuracy of existing systems, the effects of DL model properties and parameters on the performance is hard to interpret. This makes comparative analysis a necessary tool to achieve explainable studies and systems. Moreover, the performance of DL for emerging learning approaches such as cross-modality and multi-modal tasks have been rarely discussed. In order to expand the knowledge in these topics, CHAOS – Combined (CT-MR) Healthy Abdominal Organ Segmentation challenge has been organized in the IEEE International Symposium on Biomedical Imaging (ISBI), 2019, in Venice, Italy. Despite a large number of the previous abdomen related challenges, the majority of which are focused on tumor/lesion detection and/or classification with a single modality, CHAOS providesboth abdominal CT and MR data from healthy subjects. Five different and complementary tasks have been designed to analyze the capabilities of the current approaches from multiple perspectives. The results are investigated thoroughly, compared with manual annotations and interactive methods. The outcomes are reported in detail to reflect the latest advancements in the field. CHAOS challenge and data will be available online to provide a continuous benchmark resource for segmentation. Copyright © 2020, The Authors. All rights reserved.

关键词： Medical imaging

Unsupervised detection of epileptic seizures from EEG signals: A channel-specific analysis of long-term recordings

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Unsupervised detection of epileptic seizures from EEG signal...

2018 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2018

作者： Tsiouris, Kostas M. Konitsiotis, Spiros Markoula, Sofia Rigas, Georgios Koutsouris, Dimitrios D. Fotiadis, Dimitrios I. Biomedical Engineering Laboratory School of Electrical and Computer Engineering National Technical University of Athens AthensGR15773 Greece Department of Neurology Medical School University of Ioannina IoanninaGR45110 Greece University Hospital of Ioannina IoanninaGR45110 Greece Unit of Medical Technology and Intelligent Information Systems Dept. of Material Science and Engineering University of Ioannina IoanninaGR45110 Greece Department of Biomedical Research Institute of Molecular Biology and Biotechnology FORTH University of Ioannina IoanninaGR45110 Greece

ISBN: (纸本)9781538624050

As long-term EEG recordings are becoming more and more frequent in clinical practice, the volume of EEG data that require annotation by clinical experts is growing exponentially, highlighting the need for automated epileptic seizure detection systems. Supervised methodologies based on machine learning techniques have been proposed as a solution, but they require annotated EEG data from multiple patients for training, while unsupervised methodologies, which do not have such limitations, are scarce in the literature. Thus, an unsupervised seizure detection methodology is developed to offer high seizure detection performance with substantial reduction in the time and effort required to inspect large volumes of EEG signals. The ictal rhythmical activity is detected by analyzing the spectral information of each EEG channel independently in order to find intensive accumulation of signal energy over the fundamental delta, theta and alpha frequency bands. The ictal rhythmical activity that is expressed during a seizure is detected using a set of four simple seizure detection conditions. The proposed methodology is validated using the public CHB-MIT EEG database, and the results suggest that an average sensitivity of 95.1% can be obtained with a false detection rate of 10.13 FP/h, while 95% of the each patient's EEG recordings is automatically rejected as non-ictal. © 2018 IEEE.

关键词： Neurophysiology