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2nd international Scientific Symposium "Intelligent Solutions", IntSol 2021

作者： Kondruk, Natalia Malyar, Mykola Uzhhorod National University Narodna Square 3 Uzhhorod88000 Ukraine

A characteristic feature of many practical decision-making tasks is their multicriteria, which leads to the complexity of information processing when finding a solution. Failure to consider many criteria can lead to inconsistency of the constructed model with the real problem and impossibility to find its solution. Therefore, improving the effectiveness of methods for solving such problems is an urgent research problem. This work is a continuation of research on the use of the clustering method based on fuzzy binary relations in solving different classes of applied problems. It is devoted to the urgent problem of increasing the efficiency of methods for solving multi-objective problems of linear programming by applying the approach of clustering the criterion space, identifying strongly dependent efficiency criteria, further reduction of the criterion space of the problem into a smaller centroid space. In this paper we analyzes the current state of research of multi-objective optimization problem. The clustering method based on fuzzy binary relations has been adapted to detect groups of vectors by angular similarity measure. At the same time, a new kind of membership function was proposed. The approach of criterion space reduction of the problem by the space of centroids is described. At the same time centroids no longer need normalization. Based on this approach, the weighted sum scalarization method in the selection of the decision maker who decides the weights of the efficiency criteria is modified. Some approaches for determining the weights of centroids representing the criteria in the respective clusters are proposed. The scheme of the complex approach to the decision of multi-objective linear optimization problem with use of the approach of criterion space reduction is presented. © 2021 Copyright for this paper by its authors.

关键词： Membership functions

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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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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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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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Parallelizing highly complex engine management systems

Parallelizing highly complex engine management systems

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Euro-Par Conference / 7th international workshop on Programming models and Applications for Multicores and Manycores (PMAM) held in conjunction with the 21st SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP)

作者： Kienberger, Julian Schmidhuber, Stefan Saad, Christian Kuntz, Stefan Bauer, Bernhard Univ Augsburg Dept Comp Sci Augsburg Germany Timing Architects Embedded Syst GmbH Regensburg Germany Continental Automot GmbH Regensburg Germany

The automotive industry seeks to include more and more features in its vehicles. For this purpose, the necessary policy shift towards multi-core technology is in full swing. To eventually exploit the extra processing power, there is much additional effort needed for coping with the tremendously increased complexity. This is largely due to the elaborate parallelization process that spans a vast search space. Consequently, there is a strong need for innovative methods and appropriate tools for the migration of legacy single-core software. We use the results of a data dependency analysis performed on AUTOSAR system descriptions to determine advantageous partitions as well as initial task-to-core mappings. Afterwards, the extracted information serves as input for the simulation within a multi-core timing tool suite. Here, the initial solution is evaluated with respect to proper scheduling and metrics like cross-core communication rates, communication latencies, or core load distribution. A subsequent optimization process improves the initial solution and enables a comparative assessment. To demonstrate the benefit, we substantially expand a previous case study by applying our approach to two complex engine management systems and by showing the advantages compared to a parallelization process without preceding dependency analysis and initial partition/mapping suggestions.

关键词： multi-core model-based design data dependency analysis timing simulation design spaceexploration semi-automated parallelization

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Inter-model analysis of tsunami-induced coastal currents

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OCEAN modelLING 2017年 114卷 14-32页

作者： Lynett, Patrick J. Gately, Kara Wilson, Rick Montoya, Luis Arcas, Diego Aytore, Betul Bai, Yefei Bricker, Jeremy D. Castro, Manuel J. Cheung, Kwok Fai David, C. Gabriel Dogan, Gozde Guney Escalante, Cipriano Gonzalez-Vidak, Jose Manuel Grilli, Stephan T. Heitmann, Troy W. Horrillo, Juan Kanoglu, Utku Kian, Rozita Kirby, James T. Li, Wenwen Macias, Jorge Nicolsky, Dmitry J. Ortega, Sergio Pampell-Manis, Alyssa Park, Yong Sung Roeber, Volker Sharghivand, Naeimeh Shelby, Michael Shi, Fengyan Tehranirad, Babak Tolkova, Elena Thio, Hong Kie Velioglu, Deniz Yalciner, Ahmet Cevdet Yamazaki, Yoshiki Zaytsev, Andrey Zhang, Y. J. Univ Southern Calif Sonny Astani Dept Civil & Environm Engn Tsunami Res Ctr Los Angeles CA 90089 USA NOAA Natl Tsunami Warning Ctr Palmer AK 99645 USA Calif Geol Survey Seism Hazards Mapping Program Tsunami Projects Sacramento CA 95814 USA NOAA Ctr Tsunami Res 7600 Sand Point Way NE Seattle WA 98115 USA Univ Washington JISAO 3737 Brooklyn Ave NE Seattle WA 98105 USA Middle East Tech Univ Ocean Engn Res Ctr Dept Civil Engn Dumlupinar Blvd1 Cankaya TR-06800 Ankara Turkey Univ Hawaii Sch Ocean & Earth Sci & Technol Dept Ocean & Resources Engn Holmes Hall 4022540 Dole St Honolulu HI 96822 USA Tohoku Univ Int Res Inst Disaster Sci IRIDeS Aoba Ku 468-1 E304 AzaAoba Sendai Miyagi 9800845 Japan Univ Malaga Dept Anal Matemat Fac Ciencias Campus Teatinos S-N Malaga 29080 Spain Leibniz Univ Hannover Franzius Inst Hydraul Estuarine & Coastal Engn Nienburger Str 4 D-30167 Hannover NH Germany Univ Malaga Dept Matemat Aplicada ETS Telecomun Campus Teatinos S-N Malaga 29080 Spain Univ Rhode Isl Dept Ocean Engn Narragansett RI 02882 USA Texas A&M Univ Dept Ocean Engn Tsunami Res Grp 200 Seawolf Pkwy Galveston TX 77553 USA Middle East Tech Univ Dept Engn Sci Dumlupinar Blvd 1 TR-06800 Ankara Turkey Univ Delaware Dept Civil & Environm Engn Ctr Appl Coastal Res Newark DE 19716 USA AECOM 300 S Grand Ave Los Angeles CA 90017 USA Univ Alaska Fairbanks Geophys Inst 903 Koyokuk Dr Fairbanks AK 99775 USA Univ Malaga SCAI Lab Metodos Numericos Campus Teatinos S-N Malaga 29080 Spain Univ Dundee Sch Sci & Engn Div Civil Engn Perth Rd Dundee DD1 4HN Scotland NorthWest Res Associates 4118 148th Ave NE Redmond WA 98052 USA Russian Acad Sci Far Eastern Branch Special Res Bur Automat Marine Res Gorkiy Str 25 Uzhno Sakhalinsk 693013 Russia Virginia Inst Marine Sci Ctr Coastal Resource Management Coll William & Mary 1375 Greate Rd Gloucester Point VA 23062 USA Nizhnii Novgorod State Tech Univ Nizhnii Novgorod 603155 Russia Delft Univ Technol Dept Hyd

To help produce accurate and consistent maritime hazard products, the National Tsunami Hazard Mitigation Program organized a benchmarking workshop to evaluate the numerical modeling of tsunami currents. Thirteen teams of international researchers, using a set of tsunami models currently utilized for hazard mitigation studies, presented results for a series of benchmarking problems;these results are summarized in this paper. Comparisons focus on physical situations where the currents are shear and separation driven, and are thus de-coupled from the incident tsunami waveform. In general, we find that models of increasing physical complexity provide better accuracy, and that low-order three-dimensional models are superior to high-order two-dimensional models. Inside separation zones and in areas strongly affected by eddies, the magnitude of both model-data errors and inter-model differences can be the same as the magnitude of the mean flow. Thus, we make arguments for the need of an ensemble modeling approach for areas affected by large-scale turbulent eddies, where deterministic simulation may be misleading. As a result of the analyses presented herein, we expect that tsunami modelers now have a better awareness of their ability to accurately capture the physics of tsunami currents, and therefore a better understanding of how to use these simulation tools for hazard assessment and mitigation efforts. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： HAZARDOUS substances TSUNAMIS HAZARD mitigation OCEAN currents EDDIES

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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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CLUSTER-BASED REGULARIZED SLICED INVERSE REGRESSION FOR FORECASTING MACROECONOMIC VARIABLES

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Journal of Systems Science & complexity 2014年第1期27卷 75-91页

作者： YU Yue CHEN Zhihong YANG Jie TradeLink L.L.CS. Wacker Drive Suite 1900 Chicago Illinois USA. School of International Trade and: Economics University of International Business and Economics BeijingChina. Department of Mathematics Statistics and Computer Science University of Illinois at Chicago Chicago Illinois USA.

This paper concerns the dimension reduction in regression for large data set. The authors introduce a new method based on the sliced inverse regression approach, cMled cluster-based regularized sliced inverse regression. The proposed method not only keeps the merit of considering both response and predictors＇ information, but also enhances the capability of handling highly correlated variables. It is justified under certain linearity conditions. An empirical application on a macroeconomic data set shows that the proposed method has outperformed the dynamic factor model and other shrinkage methods.

关键词： Cluster-based forecast macroeconomics sliced inverse regression.

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coping with complexity: model reduction and data analysis

Coping with Complexity: Model Reduction and Data Analysis

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

ISBN: (纸本)9783642149405

The proceedings contain 17 papers. The topics discussed include: the use of global sensitivity methods for the analysis, evaluation and improvement of complex modeling systems;optimization and linear control of large scale nonlinear systems: a review and a suite of model reduction-based techniques;universal algorithms, mathematics of semirings and parallel computations;scaling invariant interpolation for singularly perturbed vector fields (SPVF);think globally, move locally: coarse graining of effective free energy surfaces;extracting functional dependence from sparse data using dimensionality reduction: application to potential energy surface construction;a multilevel algorithm to compute steady states of lattice Boltzmann models;time step expansions and the invariant manifold approach to lattice Boltzmann models;and adaptive simplification of complex systems: a review of the relaxation- redistribution approach.

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