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international research workshop: coping with complexity: model reduction and data analysis

作者： Bountis, Tassos Van Der Weele, Ko Kanellopoulos, Giorgos Andriopoulos, Kostis Department of Mathematics Centre for Research and Applications of Nonlinear Systems University of Patras Patras 26500 Greece Centre for Education in Science Platani - Rio 26504 Greece

ISBN: (纸本)9783642149405

We present novel results on a non-integrable generalized KdV equation proposed by Fokas [A.S. Fokas, Physica D87, 145 (1995)], aiming to describe unidirectional solitary water waves with greater accuracy than the standard KdV equation. The profile of the solitary wave solutions is determined via a reduction of the partial differential equation (PDE) to a set of ordinary differential equations (ODEs). Subsequently, we study the stability of the wave using this profile as initial condition for the PDE. In the case of the standard KdV equation it is well-known that the solitary wave solutions are always stable, irrespective of their height. However, in the case of our higher-order KdV equation we find that the stability of the solutions breaks down beyond a certain critical height, just like solitary waves in real water experiments.

关键词： Solitons

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Optimisation and linear control of large scale nonlinear systems: A review and a suite of model reduction-based techniques

Optimisation and linear control of large scale nonlinear sys...

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international research workshop: coping with complexity: model reduction and data analysis

作者： Theodoropoulos, Constantinos School of Chemical Engineering and Analytical Science University of Manchester Manchester M60 1QD United Kingdom

ISBN: (纸本)9783642149405

The purpose of this paper is twofold: (1) To provide a conciseaut] Constantinos Theodoropoulos review of methods, recently presented in the literature, which have developed and/or used model reduction technologies for the optimisation and control of large-scale linear and nonlinear systems and (2) to present an overview of the collection of related technologies that have been developed within our group at the University of Manchester concerning the model reduction-based steady-state and dynamic optimisation of large-scale systems, modelled with black-box dynamic and steady state solvers. Furthermore, a new methodology for the linear model predictive control of large-scale non-linear systems will be presented. It relies on adaptive linearisations of the discretised state-space equations using low-order projections of the system's gradients. Thetubular reactor has been used as an illustrative example to demonstrate the capabilities of all the above methods due to its high nonlinearity, exhibited through a number of bifurcations at different parameter combinations, and distributed parameter characteristics.

关键词： model predictive control

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Prospective data model and Distributed Query Processing for Mobile Sensing data Streams 1

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1st international workshop on Multiple-Aspect analysis of Semantic Trajectories (MASTER)

作者： Brahem, Mariem Zeitouni, Karine Yeh, Laurent El Hafyani, Hafsa Univ Versailles St Quentin En Yvelines DAVID Lab Paris Saclay Univ St Aubin France

ISBN: (数字)9783030380816

ISBN: (纸本)9783030380816;9783030380809

With the rapid advancements of sensor technologies and mobile computing, Mobile Crowd-Sensing (MCS) has emerged as a new paradigm to collect massive-scale rich trajectory data. Nomadic sensors empower people and objects with the capability of reporting and sharing observations on their state, their behavior and/or their surrounding environments. Processing and analyzing this continuously growing data raise several challenges due not only to their volume, their velocity, and their complexity but also to the gap between raw data samples and the desired application view in terms of correlation between observations and in terms of granularity. In this paper, we put forward a proposal that offers an abstract view of any spatio-temporal data series as well as their manipulation. Our approach allows to support this high-level logical view and provides efficient processing by mapping both the representation and the manipulation to an internal physical model. We explore an implementation within a distributed framework and envision the adaptation of data organization methods combining aggressive indexing and partitioning over time and space. The mapping from the logical view and the actual data storage will lead to revisiting the traditional database query rewriting and optimization techniques. This proposal is a first step in the objective of coping with the complexity, the imperfection of large data sizes in the MCS context.

关键词： Spatio-temporal data modeling Mobile crowd-sensing Query processing

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Speeding up prediction performance of BDT-based models 18

Speeding up prediction performance of BDT-based models

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18th international workshop on Advanced Computing and analysis Techniques in Physics research (ACAT)

作者： Khairullin, E. Ustyuzhanin, A. Moscow Inst Phys & Technol Inst Skiy Per 9 Dolgoprudnyi 141700 Moscow Region Russia Natl Res Univ Higher Sch Econ 20 Myasnitskaya St Moscow 101000 Russia Yandex Sch Data Anal 11-2 Timura Frunze St Moscow 119021 Russia

The outcome of a machine learning algorithm is a prediction model. Typically, these models are computationally expensive, where improving of the quality the prediction leads to a decrease in the inference speed. However it is not always tradeoff between quality and speed. In this paper we show it is possible to speed up the model by using additional memory without losing significat prediction quality for a novel boosted trees algorithm called CatBoost. The idea is to combine two approaches: training fewer trees and merging trees into a kind of hashmaps called DecisionTensors. The proposed method allows for pareto-optimal reduction of the computational complexity of the decision tree model with regard to the quality of the model. In the considered example the number of lookups was decreased from 5000 to only 6 (speedup factor of 1000) while AUC score of the model was reduced by less than 10(-3).

关键词： Decision trees

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Universal algorithms, mathematics of semirings and parallel computations

Universal algorithms, mathematics of semirings and parallel ...

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international research workshop: coping with complexity: model reduction and data analysis

作者： Litvinov, Grigory L. Maslov, Victor P. Rodionov, Anatoly Ya. Sobolevski, Andrei N. Independent University of Moscow Moscow Russia D. V. Skobeltsyn Research Institute for Nuclear Physics Moscow State University Moscow Russia Faculty of Physics Moscow State University Moscow Russia A. A. Kharkevich Institute for Information Transmission Problems Moscow Russia

ISBN: (纸本)9783642149405

This isaut]Grigory L. Litvinovaut]Victor P. Maslovaut]Anatoly Ya. Rodionovaut]Andrei N. Sobolevskii a survey paper on applications of mathematics of semirings to numerical analysis and computing. Concepts of universal algorithm and generic program are discussed. Relations between these concepts and mathematics of semirings are examined. A very brief introduction to mathematics of semirings (including idempotent and tropical mathematics) is presented. Concrete applications to optimization problems, idempotent linear algebra and interval analysis are indicated. It is known that some nonlinear problems (and especially optimization problems) become linear over appropriate semirings with idempotent addition (the so-called idempotent superposition principle). This linearity over semirings is convenient for parallel computations.

关键词： Linear algebra

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Novel functional and distributed approaches to data analysis available in ROOT 18

Novel functional and distributed approaches to data analysis...

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18th international workshop on Advanced Computing and analysis Techniques in Physics research (ACAT)

作者： Amadio, G. Blomer, J. Canal, P. Ganis, G. Guiraud, E. Vila, P. Mato Moneta, L. Piparo, D. Tejedor, E. Valls Pla, X. CERN Geneva Switzerland FNAL Batavia IL USA Carl von Ossietzky Univ Oldenburg Oldenburg Germany Univ Jaume 1 Castellon De La Plana Spain

The bright future of particle physics at the Energy and Intensity frontiers poses exciting challenges to the scientific software community. The traditional strategies for processing and analysing data are evolving in order to (i) offer higher-level programming model approaches and (ii) exploit parallelism to cope with the ever increasing complexity and size of the datasets. This contribution describes how the ROOT framework, a cornerstone of software stacks dedicated to particle physics, is preparing to provide adequate solutions for the analysis of large amount of scientific data on parallel architectures. The functional approach to parallel data analysis provided with the ROOT TdataFrame interface is then characterised. The design choices behind this new interface are described also comparing with other widely adopted tools such as Pandas and Apache Spark. The programming model is illustrated highlighting the reduction of boilerplate code, composability of the actions and data transformations as well as the capabilities of dealing with different data sources such as ROOT, JSON, CSV or databases. Details are given about how the functional approach allows transparent implicit parallelisation of the chain of operations specified by the user. The progress done in the field of distributed analysis is examined. In particular, the power of the integration of ROOT with Apache Spark via the PyROOT interface is shown. In addition, the building blocks for the expression of parallelism in ROOT are briefly characterised together with the structural changes applied in the building and testing infrastructure which were necessary to put them in production.

关键词： Parallel architectures

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Uncertainty management in enroute air traffic control: a field study exploring controller strategies and requirements for automation

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COGNITION TECHNOLOGY & WORK 2016年第3期18卷 541-565页

作者： Corver, Sifra Grote, Gudela Skyguide CH-8602 Wangen Bei Dubendorf Switzerland ETH Dept Management Technol & Econ CH-8092 Zurich Switzerland

The management of uncertainty is a critical aspect of current as well as future air traffic control operations. This study investigated: (1) sources of uncertainty in enroute air traffic control, (2) strategies that air traffic controllers adopt to cope with uncertainty, (3) the trade-offs and contingencies that influences the adoption of these uncertainties, and (4) the requirements for system design that support controllers in following these strategies. The data were collected using a field study in two enroute air traffic control centres, involving "over the shoulder" observation sessions, discussions with air traffic controllers, and document analysis. Three types of uncertainty coping strategies were identified: reducing uncertainty, acknowledging uncertainty, and increasing uncertainty. The RAWFS heuristic (Lipshitz and Strauss in Organ Behav Hum Decis Process 69:149-163, 1997) and anticipatory thinking (Klein et al. in Anticipatory thinking, Proceedings of the eighth international NDM conference, Pacific Grove, CA, 2007) were used to identify reduction and acknowledgement strategies. Recent suggestions by Grote (Saf Sci 71:71-79, 2015) were used to further explore strategies that increase uncertainty. The study presents a new framework for the classification of uncertainties in enroute air traffic control and identified the uncertainty management strategies and underlying tactics, in context of contingencies and trade-offs between operational goals. The results showed that controllers, in addition to reducing and acknowledging uncertainty, may deliberately increase uncertainty in order to increase flexibility for other actors in the system to meet their operational goals. The study describes new tactics for acknowledging and increasing uncertainty. The findings were summarized in the air traffic controller complexity and uncertainty management model. Additionally, the results bring to light system design recommendations that allow controllers to follow these

关键词： Uncertainty management coping with uncertainty Air traffic control Adaptive strategies System design Naturalistic decision-making

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On-the-fly dynamic dead variable analysis

On-the-fly dynamic dead variable analysis

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14th international SPIN workshop: model Checking Software, 2007

作者： Self, Joel P. Mercer, Eric G. Department of Computer Science Brigham Young University Provo UT United States

State explosion in model checking continues to be the primary obstacle to widespread use of software model checking. The large input ranges of variables used in software is the main cause of state explosion. As software grows in size and complexity, the problem only becomes worse. As such, model checking research into data abstraction as a way of mitigating state explosion has become more and more important. data abstractions aim to reduce the effect of large input ranges. This work focuses on a static program analysis technique called dead variable analysis. The goal of dead variable analysis is to discover variable assignments that are not used. When applied to model checking, this allows us to ignore the entire input range of dead variables and thus reduce the size of the explored state space. Prior research into dead variable analysis for model checking does not make full use of dynamic run-time information that is present during model checking. We present an algorithm for intraprocedural dead variable analysis that uses dynamic run-time information to find more dead variables on-the-fly and further reduce the size of the explored state space. We introduce a definition for the maximal state space reduction possible through an on-the-fly dead variable analysis and then show that our algorithm produces a maximal reduction in the absence of non-determinism. © Springer-Verlag Berlin Heidelberg 2007.

关键词： model checking

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General refinement strategy for magnetic structures using spherical neutron polarimetry and representation analysis

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PHYSICA B-CONDENSED MATTER 2009年第17期404卷 2535-2538页

作者： Poole, A. Lelievre-Berna, E. Wills, A. S. UCL Dept Chem 20 Gordon St London WC1H 0AJ England London Ctr Nanotechnol London WC1H 0AH England Inst Max Von Laue Paul Langevin F-38042 Grenoble 9 France

Spherical neutron polarimetry (SNP) is a powerful technique for the determination of magnetic structures which may otherwise be intractable. The complexity of the neutron scattering process and the large number of different possible trial structures typically leads to refinements based on a simple trial and error generation of possible models and a possible failure to explore valid possible models. The combination of the model symmetry types determined from representational analysis and reverse-Monte Carlo refinement creates a generalized refinement strategy for SNP data that allows refinement in terms of symmetry adapted modes built up from the basis vectors that describe the orientations of the magnetic moments on the different magnetic sites, and those of the different domains that are possible in a sample: spin (S)-domains and K-domains. This methodology typically leads to a large reduction in the number of refined parameters as well as the rigorous inclusion of any symmetry related domains. In combination with reverse-Monte Carlo refinement algorithms a general strategy for refining complex magnetic structures can be created. We present an example of a frustrated magnetic structure that have been determined using this approach Er2Ti2O7. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Spherical neutron polarimetry SNP Frustrated magnetism Representational theory Symmetry analysis

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Security analysis of Key Extraction from Physical Measurements with Multiple Adversaries

Security Analysis of Key Extraction from Physical Measuremen...

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IEEE international Conference on Communications (ICC) / workshop on Integrating UAVs into 5G

作者： Wang, Xiaoxue Hou, Yanzhao Huang, Xueqing Li, Dongru Tao, Xiaofeng Xu, Jin Beijing Univ Posts & Telecommun Natl Engn Lab Mobile Network Technol Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun Res Inst Shenzhen Peoples R China New York Inst Technol Dept Comp Sci New York NY USA

ISBN: (纸本)9781538643280

In this paper, security of secret key extraction scheme is evaluated for private communication between legitimate wireless devices. Multiple adversaries that distribute around these legitimate wireless devices eavesdrop on the data transmitted between them, and deduce the secret key. Conditional min-entropy given the view of those adversaries is utilized as security evaluation metric in this paper. Besides, the wiretap channel model and hidden Markov model (HMM) are regarded as the channel model and a dynamic programming approach is used to approximate conditional min-entropy. Two algorithms are proposed to mathematically calculate the conditional minentropy by combining the Viterbi algorithm with the Forward algorithm. Optimal method with multiple adversaries (OME) algorithm is proposed firstly, which has superior performance but exponential computation complexity. To reduce this complexity, suboptimal method with multiple adversaries (SOME) algorithm is proposed, using performance degradation for the computation complexity reduction. In addition to the theoretical analysis, simulation results further show that the OME algorithm indeed has superior performance as well as the SOME algorithm has more efficient computation.

关键词： physical layer security key extraction HMM conditional min-entropy

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