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The 1995-2018 global evolution of the network of amicable and hostile relations among nation-states

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arXiv 2020年

作者： Askarisichani, Omid Singh, Ambuj K. Bullo, Francesco Friedkin, Noah E. Department of Computer Science University of California Santa BarbaraCA93106 United States Center for Control Dynamical Systems and Computation University of California Santa BarbaraCA93106 United States Department of Mechanical Engineering University of California Santa BarbaraCA93106 United States Department of Sociology University of California Santa BarbaraCA93106 United States

We draw on the data collected by the Integrated Crisis Early Warning System on millions of international and regional public news stories, and this system's indicators of the orientation toward a specific nation-state. We construct the networks of international amicable and hostile relations among nation-states that occur in specific time-periods in order to study the global evolution of the network of such international appraisals. Our analysis presents evidence of an evolution of the structure of this network and a model of the probabilistic micro-dynamics of the alterations of international appraisals during the 1995-2018 span of the available data. Our research provides empirical findings on long-standing debates in the interdisciplinary field of work on Structural Balance Theory. Also remarkably, we find that the trajectory of the Frobenius norm of sequential transition probabilities, which govern the evolution of international appraisals among nations, dramatically stabilizes. Copyright © 2020, The Authors. All rights reserved.

关键词： Convex optimization

Shifting H ∞ Linear Parameter Varying State-Feedback controllers Subject to Time-Varying Input Saturations ⁎

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IFAC-PapersOnLine 2020年第2期53卷 7338-7343页

作者： Adrián Ruiz Damiano Rotondo Bernardo Morcego Research Center for Supervision Safety and Automatic Control UPC Rambla Sant Nebridi 22 08222 Terrassa Spain Department of Electrical and Computer Engineering (IDE) University of Stavanger 4009 Norway Institut de Robòtica i Informàtica Industrial CSIC-UPC Llorens i Artigas 4-6 08028 Barcelona Spain

This paper establishes a methodology based on linear matrix inequalities (LMIs) to design a shifting H ∞ linear parameter varying (LPV) state-feedback controller for systems affected by time-varying input saturations. By means of the shifting paradigm, the instantaneous saturation values are linked to a scheduling parameter vector. Then, the disturbance rejection is dealt with the quadratic boundedness concept and the shifting H ∞ methodology. The design conditions are obtained within the LPV framework using ellipsoidal invariant sets, thus obtaining an LMI-based feasibility problem that can be solved via available solvers. Finally, the main characteristics of the proposed approach are validated by means of an illustrative example.

关键词： Linear parameter varying (LPV) Saturation Disturbance rejection Linear matrix inequalities (LMIs)

Expertise and confidence explain how social influence evolves along intellective tasks

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arXiv 2020年

作者： Askarisichani, Omid Huang, Elizabeth Y. Sato, Kekoa S. Friedkin, Noah E. Bullo, Francesco Singh, Ambuj K. Department of Computer Science University of California Santa BarbaraCA93106 United States Department of Mechanical Engineering University of California Santa BarbaraCA93106 United States Center for Control Dynamical Systems and Computation University of California Santa BarbaraCA93106 United States Department of Sociology University of California Santa BarbaraCA93106 United States

Discovering the antecedents of individuals’ influence in collaborative environments is an important, practical, and challenging problem. In this paper, we study interpersonal influence in small groups of individuals who collectively execute a sequence of intellective tasks. We observe that along an issue sequence with feedback, individuals with higher expertise and social confidence are accorded higher interpersonal influence. We also observe that low-performing individuals tend to underestimate their high-performing teammate’s expertise. Based on these observations, we introduce three hypotheses and present empirical and theoretical support for their validity. We report empirical evidence on longstanding theories of transactive memory systems, social comparison, and confidence heuristics on the origins of social influence. We propose a cognitive dynamical model inspired by these theories to describe the process by which individuals adjust interpersonal influences over time. We demonstrate the model’s accuracy in predicting individuals’ influence and provide analytical results on its asymptotic behavior for the case with identically performing individuals. Lastly, we propose a novel approach using deep neural networks on a pre-trained text embedding model for predicting the influence of individuals. Using message contents, message times, and individual correctness collected during tasks, we are able to accurately predict individuals’ self-reported influence over time. Extensive experiments verify the accuracy of the proposed models compared to baselines such as structural balance and reflected appraisal model. While the neural networks model is the most accurate, the dynamical model is the most interpretable for influence prediction. Copyright © 2020, The Authors. All rights reserved.

关键词： Forecasting

Affinely Parametrized State-space Models: Ways to Maximize the Likelihood Function

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IFAC-PapersOnLine 2018年第15期51卷 718-723页

作者： Wills, Adrian Yu, Chengpu Ljung, Lennart Verhaegen, Michel School of Electrical Engineering and Computer Science University of Newcastle Australia School iof Automation Beijing Institute of Technology China Division of Automatic Control Department of Electrical Engineering Linkoping University Sweden Delft Center for Systems and Control Delft University Delft2628CD Netherlands

Using Maximum Likelihood (or Prediction Error) methods to identify linear state space model is a prime technique. The likelihood function is a nonconvex function and care must be exercised in the numerical maximization. Here the focus will be on affine parameterizations which allow some special techniques and algorithms. Three approaches to formulate and perform the maximization are described in this contribution: (1) The standard and well known Gauss-Newton iterative search, (2) a scheme based on the EM (expectation-maximization) technique, which becomes especially simple in the affine parameterization case, and (3) a new approach based on lifting the problem to a higher dimension in the parameter space and introducing rank constraints. © 2018

关键词： Maximum likelihood estimation

Regular path-constrained time-optimal control problems in three-dimensional flow fields

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arXiv 2019年

作者： Chertovskih, R. Karamzin, D. Khalil, N.T. Pereira, F.L. Electrical and Computer Engineering Department Faculty of Engineering University of Porto 4200-465 Portugal Federal Research Center "Computer Science and Control" Russian Academy of Science Moscow Russia

This article concerns a class of time-optimal state constrained control problems with dynamics defined by an ordinary differential equation involving a three-dimensional steady flow vector field. The problem is solved via an indirect method based on the maximum principle in Gamkrelidze's form. The proposed computational method essentially uses a certain regularity condition imposed on the data of the problem. The property of regularity guarantees the continuity of the measure multiplier associated with the state constraint, and ensures the appropriate behavior of the corresponding numerical procedure which, in general, consists in computing the entire field of extremals for the problem in question. Several examples of vector fields are considered to illustrate the computational *** Codes 49K15, 49M05 Copyright © 2019, The Authors. All rights reserved.

关键词： Maximum principle

Atomically sharp interface enabled ultrahigh-speed, nonvolatile memory devices

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arXiv 2021年

作者： Wu, Liangmei Wang, Aiwei Shi, Jinan Yan, Jiahao Zhou, Zhang Bian, Ce Ma, Jiajun Ma, Ruisong Liu, Hongtao Chen, Jiancui Huang, Yuan Zhou, Wu Bao, Lihong Ouyang, Min Pennycook, Stephen J. Pantelides, Sokrates T. Gao, Hong-Jun Institute of Physics Chinese Academy of Sciences P. O. Box 603 Beijing100190 China Univ. of Chinese Acad. of Sciences and Cas Center for Excellence in Topological Quantum Computation Chinese Academy of Sciences P. O. Box 603 Beijing100190 China Songshan Lake Materials Laboratory Dongguan Guangdong523808 China Department of Physics College Park University of Maryland College ParkMD20742 United States Department of Materials Science and Engineering and Centre for Advanced 2D Materials National University of Singapore 117575 Singapore Department of Physics and Astronomy and Department of Electrical Engineering and Computer Science Vanderbilt University NashvilleTN37235 United States

Development of memory devices with ultimate performance has played a key role in innovation of modern electronics. As a mainstream technology nonvolatile memory devices have manifested high capacity and mechanical reliability, however current major bottlenecks include low extinction ratio and slow operational speed. Although substantial effort has been employed to improve their performance, a typical hundreds of micro-or even milli-second write time remains a few orders of magnitude longer than their volatile counterparts. We have demonstrated nonvolatile, floating-gate memory devices based on van der Waals heterostructures with atomically sharp interfaces between different functional elements, and achieved ultrahigh-speed programming/erasing operations verging on an ultimate theoretical limit of nanoseconds with extinction ratio up to 1010. This extraordinary performance has allowed new device capabilities such as multi-bit storage, thus opening up unforeseen applications in the realm of modern nanoelectronics and offering future fabrication guidelines for device scale-up. Copyright © 2021, The Authors. All rights reserved.

关键词： Light extinction

Time-Varying Convex Optimization: Time-Structured Algorithms and Applications

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arXiv 2020年

作者： Simonetto, Andrea Dall’Anese, Emiliano Paternain, Santiago Leus, Geert Giannakis, Georgios B. Optimization and Control Group of IBM Research Ireland Dublin Ireland College of Engineering and Applied Science University of Colorado BoulderCO80309 United States Department of Electrical and Systems Engineering University of Pennsylvania Faculty of Electrical Mathematics and Computer Science Delft University of Technology Delft2628CD Netherlands Digital Technology Center University of Minnesota MinneapolisMN55455 United States

Optimization underpins many of the challenges that science and technology face on a daily basis. Recent years have witnessed a major shift from traditional optimization paradigms grounded on batch algorithms for medium-scale problems to challenging dynamic, time-varying, and even huge-size settings. This is driven by technological transformations that converted infrastructural and social platforms into complex and dynamic networked systems with even pervasive sensing and computing capabilities. The present paper reviews a broad class of state-of-the-art algorithms for time-varying optimization, with an eye to both algorithmic development and performance analysis. It offers a comprehensive overview of available tools and methods, and unveils open challenges in application domains of broad interest. The real-world examples presented include smart power systems, robotics, machine learning, and data analytics, highlighting domain-specific issues and solutions. The ultimate goal is to exempify wide engineering relevance of analytical tools and pertinent theoretical foundations. Copyright © 2020, The Authors. All rights reserved.

关键词： Data Analytics

Verification of application of ANN modelling in study of compressive behaviour of aluminium sponges

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engineering Transactions 2019年第2期67卷 271-288页

作者： Stręk, Anna M. Dudzik, Marek Kwiecień, Arkadiusz Wańczyk, Krzysztof Lipowska, Barbara Cracow University of Technology Faculty of Civil Engineering Institute of Structural Mechanics Warszawska 24 Kraków31-155 Poland Cracow University of Technology Faculty of Electrical and Computer Engineering Department of Traction and Traffic Control Warszawska 24 Kraków31-155 Poland Foundry Research Institute Center for Design and Prototyping Zakopiańska 73 Kraków30-418 Poland Institute of Ceramics and Building Materials Refractory Materials Division in Gliwice Toszecka 99 Gliwice44-100 Poland

This article presents a preliminary neural network analysis of the compressive behaviour of aluminium open-cell sponges and answers the question of whether this phenomenon can be modelled using artificial intelligence. The research consisted of two phases: first – compression experiments, which in turn provided data for the second phase – the artificial neural network (ANN) analysis. A two-argument function was proposed and tested using the gathered experimental data with a two-layer feedforward network. The determination coefficient R2 for linear correlation between targets and modelling outputs was chosen as the criterion for the assessment of the quality of modelling. The obtained values were R2 > 0.96, which shows that neural networks hold the capacity to address the characterisation of the mechanical response of aluminium open-cell sponges in compression. Additionally, the mean absolute relative error (MARE) and the mean square error (MSE) were also determined. © 2019, Polish Academy of Sciences. All rights reserved.

关键词： Aluminum

Single pixel fourier computed tomography

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Single pixel fourier computed tomography

Novel Techniques in Microscopy, NTM 2019

作者： Stockton, Patrick A. Wernsing, Keith A. Field, Jeff J. Squier, Jeff Bartels, Randy A. Department of Electrical and Computer Engineering Colorado State University United States Department of Biochemistry and Molecular Biology Colorado State University United States Microscope Imaging Network Foundational Core Facility Colorado State University United States School of Biomedical Engineering Colorado State University United States Center for Microintegrated Optics for Advanced Biological Control Department of Physics Colorado School of Mines United States

ISBN: (纸本)9781943580545

关键词： computerized tomography