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21st AIAA International Space Planes and Hypersonics Technologies Conference, Hypersonics 2017

作者： Ma, Shunjian Zhu, Kai Sun, Mingwei Wang, Zenghui Chen, Zengqiang Dept. of Automation and Intelligent Science Nankai University College of Computer and Control Engineering Tianjin300350 China Beijing Aerospace Technology Institute Tianjin Key Laboratory of Intelligent Robotics Tianjin300350 China Beijing Aerospace Technology Institute Beijing100074 China Department of Electrical and Mining Engineering University of South Africa FL1710 South Africa

ISBN: (数字)9781624104633

ISBN: (纸本)9781624104633

Nowadays, hypersonic flight vehicles are widely studied. Since their high nonlinearity, strong coupling and uncertain factors, the conventional three-channel independent control design method is often unable to work well. In this paper, an active disturbance rejection controller (ADRC) is utilized to cancel internal uncertainties and exogenous disturbances for longitudinal dynamics. Then, the MIMO robust controller is obtained by choosing proper sensitivity functions and weighting functions to reduce horizontal-lateral direction coupling. The conventional H robust controllor is high-order, which is difficult for practitioners to implement. With frequency transformation, both ADRC for the longitudinal dynamics and MIMO robust controller for the horizontal-lateral dynamics are reformed into the static output feedback structure to reduce the high order of controller. Finally, all parameters in the controllers can be optimized by HIFOO (H-Infinity Fixed Order Optimization). The Winged-Cone, a 6-freedom NASA hypersonic vehicle model, is used as a benchmark, and Monte Carlo simulations demonstrate the effectiveness of the proposed method. © 2017, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Controllers

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Author Correction: A CCG expansion in ABCD3 causes oculopharyngodistal myopathy in individuals of European ancestry

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Nature communications 2024年第1期15卷 8955页

作者： Andrea Cortese Sarah J Beecroft Stefano Facchini Riccardo Curro Macarena Cabrera-Serrano Igor Stevanovski Sanjog R Chintalaphani Hasindu Gamaarachchi Ben Weisburd Chiara Folland Gavin Monahan Carolin K Scriba Lein Dofash Mridul Johari Bianca R Grosz Melina Ellis Liam G Fearnley Rick Tankard Justin Read Ashirwad Merve Natalia Dominik Elisa Vegezzi Ricardo P Schnekenberg Gorka Fernandez-Eulate Marion Masingue Diane Giovannini Martin B Delatycki Elsdon Storey Mac Gardner David J Amor Garth Nicholson Steve Vucic Robert D Henderson Thomas Robertson Jason Dyke Vicki Fabian Frank Mastaglia Mark R Davis Marina Kennerson Ros Quinlivan Simon Hammans Arianna Tucci Melanie Bahlo Catriona A McLean Nigel G Laing Tanya Stojkovic Henry Houlden Michael G Hanna Ira W Deveson Paul J Lockhart Phillipa J Lamont Michael C Fahey Enrico Bugiardini Gianina Ravenscroft Department of Neuromuscular Diseases UCL Queen Square Institute of Neurology London UK. andrea.cortese@ucl.ac.uk. Department of Brain and Behavioral Sciences University of Pavia Pavia Italy. andrea.cortese@ucl.ac.uk. Pawsey Supercomputing Research Centre Kensington WA Australia. Department of Neuromuscular Diseases UCL Queen Square Institute of Neurology London UK. Department of Brain and Behavioral Sciences University of Pavia Pavia Italy. Harry Perkins Institute of Medical Research Nedlands WA Australia. Department of Neurology and Instituto de Biomedicina de Sevilla Hospital Universitario Virgen del Rocío/Universidad de Sevilla/CSIC Sevilla 41013 Spain. Genomics and Inherited Disease Program Garvan Institute of Medical Research Sydney NSW Australia. Centre for Population Genomics Garvan Institute of Medical Research and Murdoch Children's Research Institute Sydney NSW Australia. School of Computer Science and Engineering University of New South Wales Sydney NSW Australia. Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA. Centre for Medical Research University of Western Australia Nedlands WA Australia. Northcott Neuroscience Laboratory ANZAC Research Institute Sydney NSW 2139 Australia. Faculty of Medicine and Health University of Sydney Sydney NSW 2006 Australia. Population Health and Immunity Division The Walter and Eliza Hall Institute of Medical Research 1 G Royal Parade Parkville VIC 3052 Australia. Department of Medical Biology The University of Melbourne 1G Royal Parade Parkville VIC3052 Australia. Department of Mathematics and Statistics Curtin University Perth WA Australia. Bruce Lefroy Centre Murdoch Children's Research Institute Parkville VIC Australia. Department of Paediatrics University of Melbourne Royal Children's Hospital Parkville VIC Australia. Department of Neuropathology National Hospital for Neurology and Neurosurgery London United Kingdom. IRCCS Mondino Foundation

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Network Topology Mapping from Partial Virtual Coordinates and Graph Geodesics

arXiv

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arXiv 2017年

作者： Jayasumana, Anura P. Paffenroth, Randy Ramasamy, Sridhar Department of Electrical & Computer Engineering Colorado State University Fort CollinsCO80525 Department of Mathematical Sciences Department of Computer Science Data Science Program Worcester Polytechnic Institute WorcesterMA01609

For many important network types (e.g., sensor networks in complex harsh environments and social networks) physical coordinate systems (e.g., Cartesian), and physical distances (e.g., Euclidean), are either difficult to discern or inappropriate. Accordingly, Topology Preserving Maps (TPMs) derived from a Virtual-Coordinate (VC) system representing the distance to a small set of anchors is an attractive alternative to physical coordinates for many network algorithms. Herein, we present an approach, based on the theory of low-rank matrix completion, to recover geometric properties of a network with only partial information about the VCs of nodes. In particular, our approach is a combination of geodesic recovery concepts and low-rank matrix completion, generalized to the case of hop-distances in graphs. Distortion evaluated using the change of distance among node pairs shows that even with up to 40% to 60% of random coordinates missing, accurate TPMs can be obtained. TPM generation can now also be based on different context appropriate VC systems or measurements as long as they characterize each node with distances to a small set of random nodes (instead of a global set of anchors). The proposed method is a significant generalization that allows the topology to be extracted from a random set of graph geodesics, making it applicable in contexts such as social networks where VC generation may not be *** Codes 15A83 Copyright © 2017, The Authors. All rights reserved.

关键词： Sensor networks

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Forecasting: theory and practice

arXiv

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arXiv 2020年

作者： Petropoulos, Fotios Apiletti, Daniele Assimakopoulos, Vassilios Babai, Mohamed Zied Barrow, Devon K. Taieb, Souhaib Ben Bergmeir, Christoph Bessa, Ricardo J. Bijak, Jakub Boylan, John E. Browell, Jethro Carnevale, Claudio Castle, Jennifer L. Cirillo, Pasquale Clements, Michael P. Cordeiro, Clara Oliveira, Fernando Luiz Cyrino de Baets, Shari Dokumentov, Alexander Ellison, Joanne Fiszeder, Piotr Franses, Philip Hans Frazier, David T. Gilliland, Michael Gönül, M. Sinan Goodwin, Paul Grossi, Luigi Grushka-Cockayne, Yael Guidolin, Mariangela Guidolin, Massimo Gunter, Ulrich Guo, Xiaojia Guseo, Renato Harvey, Nigel Hendry, David F. Hollyman, Ross Januschowski, Tim Jeon, Jooyoung Jose, Victor Richmond R. Kang, Yanfei Koehler, Anne B. Kolassa, Stephan Kourentzes, Nikolaos Leva, Sonia Li, Feng Litsiou, Konstantia Makridakis, Spyros Martin, Gael M. Martinez, Andrew B. Meeran, Sheik Modis, Theodore Nikolopoulos, Konstantinos Önkal, Dilek Paccagnini, Alessia Panagiotelis, Anastasios Panapakidis, Ioannis Pavía, Jose M. Pedio, Manuela Pedregal, Diego J. Pinson, Pierre Ramos, Patrícia Rapach, David E. Reade, J. James Rostami-Tabar, Bahman Rubaszek, Michal Sermpinis, Georgios Shang, Han Lin Spiliotis, Evangelos Syntetos, Aris A. Talagala, Priyanga Dilini Talagala, Thiyanga S. Tashman, Len Thomakos, Dimitrios Thorarinsdottir, Thordis Todini, Ezio Arenas, Juan Ramón Trapero Wang, Xiaoqian Winkler, Robert L. Yusupova, Alisa Ziel, Florian School of Management University of Bath United Kingdom Politecnico di Torino Turin Italy Forecasting and Strategy Unit School of Electrical and Computer Engineering National Technical University of Athens Greece Kedge Business School France Department of Management Birmingham Business School University of Birmingham United Kingdom Belgium Faculty of Information Technology Monash University Melbourne Australia INESC TEC – Institute for Systems and Computer Engineering Technology and Science Porto Portugal Department of Social Statistics and Demography University of Southampton United Kingdom Centre for Marketing Analytics and Forecasting Lancaster University Management School Lancaster University United Kingdom School of Mathematics and Statistics University of Glasgow United Kingdom Department of Mechanical and Industrial Engineering University of Brescia Italy Magdalen College University of Oxford United Kingdom ZHAW School of Management and Law Zurich University of Applied Sciences Switzerland ICMA Centre Henley Business School University of Reading United Kingdom Faculdade de Ciências e Tecnologia Universidade do Algarve Portugal CEAUL Faculdade de Ciências Universidade de Lisboa Portugal Brazil Department of Business Informatics and Operations Management Faculty of Economics and Business Administration Universiteit Gent Belgium Let’s Forecast Australia Faculty of Economic Sciences and Management Nicolaus Copernicus University in Torun Poland Econometric Institute Erasmus School of Economics Rotterdam Netherlands Department of Econometrics and Business Statistics Monash University Melbourne Australia SAS United States Newcastle Business School Northumbria University Newcastle upon Tyne United Kingdom Department of Statistical Sciences University of Padua Italy Darden School of Business University of Virginia United States Finance Department Bocconi University Baffi-CAREFIN Centre Milan Italy Department of Tourism and Service Management MODUL Un

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases. © 2020, CC BY.

关键词： Forecasting

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Generating Stories that Include Failed Actions by Modeling False Character Beliefs 13

Generating Stories that Include Failed Actions by Modeling F...

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13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017

作者： Thorne, Brandon R. Michael Young, R. Liquid Narrative Group Department of Computer Science NC State University RaleighNC27695 United States Liquid Narrative Group School of Computing The Entertainment Arts and Engineering Program University of Utah Salt Lake CityUT84112 United States

ISBN: (纸本)9781577357926

Previous work on story planning has lacked a knowledge representation for characters that make mistakes in the execution of their actions. In particular, characters' execution mistakes that arise from errors in belief have not been modeled. In this paper, we describe a state-space planning system and its belief model, together called HEADSPACE, that generates stories that track and manipulates characters' belief about the story world around them. This model is used to produce actions in stories that are attempted but that fail. We show an example story plan that contains failed-action content that cannot be generated by typical planning-based approaches to story creation. Copyright © 2017, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Knowledge representation

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Narrative Mediation as Probabilistic Planning 13

Narrative Mediation as Probabilistic Planning

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13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017

作者： Robertson, Justus Michael Young, R. Liquid Narrative Group Department of Computer Science NC State University RaleighNC27695 United States Liquid Narrative Group School of Computing The Entertainment Arts and Engineering Program University of Utah Salt Lake CityUT84112 United States

ISBN: (纸本)9781577357926

Narrative mediation is a plan-based process that converts a planning problem into a mediation tree that models an interactive story. Probabilistic planning relaxes the classical planning constraint of deterministic action outcomes by containing domain operators with nondeterministic effects. This paper shows narrative mediation can be viewed as a probabilistic planning problem where the outcomes of user actions are modeled with nondeterministic effects in the domain. The paper gives a process for automatically converting a deterministic mediation planning problem into a probabilistic interactive narrative planning problem. Copyright © 2017, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Human robot interaction

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Iran in transition (vol 393, pg 1984, 2019)

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LANCET 2019年第10186期393卷 2124-2124页

作者： Danaei, G. Farzadfar, F. Kelishadi, R. [a]Department of Global Health and Population and Department of Epidemiology Harvard T H Chan School of Public Health Boston MA USA Department of Global Health and Population and Department of Epidemiology Harvard T H Chan School of Public Health Boston MA USA [b]Scientific Association for Public Health in Iran Boston MA USA Scientific Association for Public Health in Iran Boston MA USA [c]Non-Communicable Diseases Research Center Endocrinology and Metabolism Population Sciences Institute Tehran University of Medical Sciences Tehran Iran Non-Communicable Diseases Research Center Endocrinology and Metabolism Population Sciences Institute Tehran University of Medical Sciences Tehran Iran [d]Endocrinology and Metabolism Research Center Tehran University of Medical Sciences Tehran Iran Endocrinology and Metabolism Research Center Tehran University of Medical Sciences Tehran Iran [e]Diabetes Research Center Tehran University of Medical Sciences Tehran Iran Diabetes Research Center Tehran University of Medical Sciences Tehran Iran [f]Endocrinology and Metabolism Clinical Sciences Institute Department of Health Management and Economics Tehran University of Medical Sciences Tehran Iran Endocrinology and Metabolism Clinical Sciences Institute Department of Health Management and Economics Tehran University of Medical Sciences Tehran Iran [g]Department of Global Health and Public Policy Tehran University of Medical Sciences Tehran Iran Department of Global Health and Public Policy Tehran University of Medical Sciences Tehran Iran [h]Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran [i]School of Public Health Tehran University of Medical Sciences Tehran Iran School of Public Health Tehran University of Medical Sciences Tehran Iran [j]Faculty of Medicine Tehran University of Medical Sciences Tehran Iran Faculty of Medicine Te

Summary Being the second-largest country in the Middle East, Iran has a long history of civilisation during which several dynasties have been overthrown and established and health-related structures have been reorganised. Iran has had the replacement of traditional practices with modern medical treatments, emergence of multiple pioneer scientists and physicians with great contributions to the advancement of science, environmental and ecological changes in addition to large-scale natural disasters, epidemics of multiple communicable diseases, and the shift towards non-communicable diseases in recent decades. Given the lessons learnt from political instabilities in the past centuries and the approaches undertaken to overcome health challenges at the time, Iran has emerged as it is today. Iran is now a country with a population exceeding 80 million, mainly inhabiting urban regions, and has an increasing burden of non-communicable diseases, including cardiovascular diseases, hypertension, diabetes, malignancies, mental disorders, substance abuse, and road injuries.

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Directing Intentional Superposition Manipulation 13

Directing Intentional Superposition Manipulation

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13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017

作者： Robertson, Justus Amos-Binks, Adam Michael Young, R. Liquid Narrative Group Department of Computer Science NC State University RaleighNC27695 United States Liquid Narrative Group School of Computing The Entertainment Arts and Engineering Program University of Utah Salt Lake CityUT84112 United States

ISBN: (纸本)9781577357926

Strong story interactive narratives (IN) are stories that branch based on participant actions where all branches conform to a set of predefined constraints. However, participants in these systems may create branches where the constraints no longer hold. Strong story experience management, the process of generating IN trees, can be viewed as a game where the experience management agent wins if the story constraints hold during gameplay and loses if they are broken. In domains where the player has incomplete information of the story world, the experience manager can take action by shifting the player between alternate states that are consistent with the player's observations in order to maximize the probability that constraints will hold. This process is called superposition manipulation. In this paper we present a method of estimating the number of goal states reachable from different states in order to make informed decisions during superposition manipulation. Copyright © 2017, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Artificial intelligence

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Room temperature intrinsic ferromagnetism in epitaxial manganese selenide films in the monolayer limit

arXiv

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arXiv 2018年

作者： O'Hara, Dante J. Zhu, Tiancong Trout, Amanda H. Ahmed, Adam S. Luo, Yunqiu [Kelly] Lee, Choong Hee Brenner, Mark R. Rajan, Siddharth Gupta, Jay McComb, David W. Kawakami, Roland K. Program in Materials Science and Engineering University of California RiversideCA92521 United States Department of Physics Ohio State University 191 W. Woodruff Ave. ColumbusOH43210 United States Center for Electron Microscopy and Analysis Ohio State University ColumbusOH43212 United States Department of Materials Science and Engineering Ohio State University ColumbusOH43210 United States Department of Electrical and Computer Engineering Ohio State University ColumbusOH43210 United States Semiconductor Epitaxy and Analysis Laboratory Ohio State University ColumbusOH43210 United States

Monolayer van der Waals (vdW) magnets provide an exciting opportunity for exploring twodimensional (2D) magnetism for scientific and technological advances, but the intrinsic ferromagnetism has only been observed at low temperatures. Here, we report the observation of room temperature ferromagnetism in manganese selenide (MnSex) films grown by molecular beam epitaxy (MBE). Magnetic and structural characterization provides strong evidence that in the monolayer limit, the ferromagnetism originates from a vdW manganese diselenide (MnSe2) monolayer, while for thicker films it could originate from a combination of vdW MnSe2 and/or interfacial magnetism of α-MnSe(111). Magnetization measurements of monolayer MnSex films on GaSe and SnSe2 epilayers show ferromagnetic ordering with large saturation magnetization of ~ 4 Bohr magnetons per Mn, which is consistent with density functional theory calculations predicting ferromagnetism in monolayer 1T-MnSe2. Growing MnSex films on GaSe up to high thickness (~ 40 nm) produces α-MnSe(111), and an enhanced magnetic moment (~ 2x) compared to the monolayer MnSex samples. Detailed structural characterization by scanning transmission electron microscopy (STEM), scanning tunneling microscopy (STM), and reflection high energy electron diffraction (RHEED) reveal an abrupt and clean interface between GaSe(0001) and α-MnSe(111). In particular, the structure measured by STEM is consistent with the presence of a MnSe2 monolayer at the interface. These results hold promise for potential applications in energy efficient information storage and processing. Copyright © 2018, The Authors. All rights reserved.

关键词： Molecular beam epitaxy

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Planning Graphs for Efficient Generation of Desirable Narrative Trajectories 13

Planning Graphs for Efficient Generation of Desirable Narrat...

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13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017

作者： Amos-Binks, Adam Potts, Colin Michael Young, R. Liquid Narrative Group Department of Computer Science NC State University RaleighNC27695 United States Liquid Narrative Group School of Computing The Entertainment Arts and Engineering Program University of Utah Salt Lake CityUT84112 United States

ISBN: (纸本)9781577357926

A goal of Experience Managers (EM) is to guide users through a space of narrative trajectories, or story branches, in an Interactive Narrative (IN). When a user performs an action that deviates from the intended trajectory, the EM uses a mediation strategy called accommodation to transition the user to a new desirable trajectory. However, generating the trajectory options then selecting the appropriate one is computationally expensive and at odds with the low-latency needs of an IN. We define three desirable properties (exemplar trajectories, narrative-theoretic comparison, and efficiency) that general solutions would possess and demonstrate how our plan-based Intention Dependency Graph addresses them. Copyright © 2017, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Trajectories

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