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IEEE/CVF Conference on Computer Vision and Pattern Recognition

作者： Kwang In Kim Hyung Jin Chang UNIST University of Birmingham

ISBN: (纸本)9781728132945

We present a new predictor combination algorithm that improves a given task predictor based on potentially relevant reference predictors. Existing approaches are limited in that, to discover the underlying task dependence, they either require known parametric forms of all predictors or access to a single fixed dataset on which all predictors are jointly evaluated. To overcome these limitations, we design a new non-parametric task dependence estimation procedure that automatically aligns evaluations of heterogeneous predictors across disjoint feature sets. Our algorithm is instantiated as a robust manifold diffusion process that jointly refines the estimated predictor alignments and the corresponding task dependence. We apply this algorithm to the relative attributes ranking problem and demonstrate that it not only broadens the application range of predictor combination approaches but also outperforms existing methods even when applied to classical predictor combination settings.

关键词： algorithms Manifolds DECOUPLING composite algorithm Access

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A composite Estimation Method for State of Charge of Batteries in a Power Station Engineering

A Composite Estimation Method for State of Charge of Batteri...

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IEEE Conference on Energy Internet and Energy System Integration

作者： Yuanyuan Chen Zi Long Yang Lidong Guo Xinke Huang Yibo Wang Solar Thermal Technology and Photovoltaic System Laboratory Chinese Academy of Sciences

ISBN: (纸本)9781538614280

An energy storage power station combines with photovoltaic system, and the main role of power station are following time-of-use power price and smoothing photovoltaic power fluctuations. The energy storage batteries are the main part of the power station engineering. And the important parameters of batteries are voltage, current, temperature, state of charge (SOC) and so on. Among this parameters, the SOC is the most important parameter. This paper uses a composite method to estimate the SOC, which is the Extended Kalman estimation method combine the Ah integral and the Open Circuit Voltage method. And it finally verifies that this composite algorithm has a high accuracy, and the error within 6% in a power station engineering.

关键词： Power station composite algorithm SOC

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Application of a new algorithm using Doppler information to retrieve complex wind fields over the Black Sea from ENVISAT SAR images

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INTERNATIONAL JOURNAL OF REMOTE SENSING 2015年第3期36卷 863-881页

作者： Alpers, Werner Mouche, Alexis Horstmann, Jochen Ivanov, Andrei Yu. Barabanov, Vladyslav S. Univ Hamburg Inst Oceanog Hamburg Germany IFREMER Lab Oceanog Spatiale Plouzane France Helmholtz Zentrum Inst Coastal Res Geesthacht Germany Russian Acad Sci PP Shirshov Inst Oceanol Moscow Russia Marine Hydrophys Inst Sevastopol Russia

Several algorithms have been proposed to retrieve near-surface wind fields from C-band synthetic aperture radar (SAR) images acquired over the ocean. They mainly differ in the way they retrieve the wind direction. Conventionally, the wind direction is taken from atmospheric models or is extracted from the linear features sometimes visible in SAR images. Recently, a new wind retrieval algorithm has been proposed, which also includes the Doppler shift induced by motions of the sea surface. In this article, we apply three wind retrieval algorithms, including the one using Doppler information, to three complex wind events encountered over the Black Sea and compare the SAR-derived wind fields with model wind fields calculated using the high-resolution weather research and forecasting (WRF) model. It is shown that the new algorithm is very efficient in resolving the 180 degrees ambiguity in the wind direction, which is often a problem in the streak-based wind retrieval algorithms. However, the Doppler-based algorithm only yields good results for wind directions that have a significant component in the look direction of the SAR antenna. Furthermore, it is dependent on good separation of the contributions to the Doppler shift induced by surface currents and wind-related effects (wind drift and wind-sea components of the ocean wave spectrum). We conclude that an optimum wind retrieval algorithm should consist of a combination of the algorithms based on linear features and Doppler information.

关键词： Wind fields composite algorithm Atmospheric models Black Sea Wind algorithms Doppler effect Specific absorption rate retrieval Rescue wind direction sea surface

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algorithms for a novel touchless bimodal palm biometric system 8

Algorithms for a novel touchless bimodal palm biometric syst...

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International Conference on Biometrics (ICB)

作者： Nikisins, Olegs Eglitis, Teodors Pudzs, Mihails Greitans, Modris Inst Elect & Comp Sci 14 Dzerbenes St LV-1006 Riga Latvia

ISBN: (纸本)9781479978243

The paper introduces the combination of algorithms for possibly the first bimodal biometric system capable of touch-less capturing of two biometric parameters, palm veins and palm creases, synchronously with a single image sensor. The architecture of the proposed system is based on the Detection, Alignment and Recognition pipeline. The ROI detection and alignment stages are simplified with efficient combination of hardware (lighting sources) and software. A new feature descriptor, namely Histogram of Vectors is proposed in the recognition stage. Since the capturing of images requires special conditions, the database including images of 100 individuals and ground-truth data is introduced. The analysis of performance of the system utilizes the database leading to detailed understanding of the error propagation in the automatic recognition pipeline.

关键词： Error propagation biological recognition system palm trees palm (hand) Database Recognition (Psychology) algorithms Bimodal images Sensors (image) ground truth System performance mineral dyke Veins composite algorithm

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Applying Fuzzy Sets to composite algorithm for Remote Sensing Data

Applying Fuzzy Sets to Composite Algorithm for Remote Sensin...

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14th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems

作者： Mackin, Kenneth J. Yamaguchi, Takashi Park, Jong Geol Nunohiro, Eiji Matsushita, Kotaro Yanagisawa, Yukio Igarashi, Masao Tokyo Univ Informat Sci Dept Informat Syst Wakaba Ku 1200-2 Yatoh Cho Chiba Japan Tokyo Univ Informat Sci Dept Environm Informat Chiba Japan Nihon Univ Coll Bioresource Sci Tokyo 102 Japan

ISBN: (纸本)9783642153921

Remote sensing of the earth surface using satellite mounted sensor data is a major method for global environmental monitoring today. However, when using satellite sensor data, clouds in the atmosphere can interfere with the readings, and specific land points may not be correctly monitored on a given day. In order to overcome this problem, multiple day composite data is frequently used. Multiple day composite data uses several consecutive days' remote sensing data, and picks the most accurate data within the temporal dataset for the same land point. This allows creating a more complete dataset by patching together data not interfered by clouds during a specified time period, to create a clearer, more usable dataset. In this paper, we propose applying fuzzy set logic in order to select the clearest data in the temporal interval for the composite data. Moderate resolution remote sensing data of areas in Japan were used for evaluation.

关键词： Fuzzy Sets remote sensing MODIS composite algorithm

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An Adaptive algorithm for Public Transport Arrival Time Prediction Based on Hierarhical Regression

An Adaptive Algorithm for Public Transport Arrival Time Pred...

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International IEEE Conference on Intelligent Transportation Systems

作者： Anton Agafonov Vladislav Myasnikov Samara State Aerospace University (SSAU) Image Processing Systems Institute of the Russian Academy of Sciences (IPSI RAS) Samara Russia

ISBN: (纸本)9781467365970

In this paper we consider a problem of public transport arrival time prediction for a large city in real time. We propose a new prediction algorithm based on a model of an adaptive combination of elementary prediction algorithms, each of which is characterized by a small number of adjustable parameters. Adaptability means that parameters of the constructed combination depend on a number of control parameters of the model, which includes the following factors: weather conditions, traffic density, driving dynamics, prediction horizon, and others. Adaptability is achieved by the use of a hierarchical regression (similar to a regression tree). The proposed arrival prediction algorithm has been tested with the data of all the public transport routes in Samara, Russia.

关键词： public transport arrival time prediction combination of algorithms hierarchical regression Public Transit control parameter Prediction algorithms composite algorithm arrival time Adaptive algorithms metropolis Traffic density Regression (Psychology)

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Distributed Cohesive Configuration Control for Swarm Robots with Boundary Information and Network Sensing

Distributed Cohesive Configuration Control for Swarm Robots ...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Seoung Kyou Lee James McLurkin Graduate Student of Computer Science Rice University Houston TX USA Faculty of Computer Science Rice University Houston TX USA

ISBN: (纸本)9781479969357

In this paper, we present flocking with cohesive configuration control -- motion controllers that allow multiple robots to move through the environment as a coherent group while maintaining connectivity and density invariants. We start with a flocking controller from the literature. First, we produce a boundary force on robots that are on the internal and external boundaries of the configuration. This removes concave regions of the boundary, producing a convex configuration with uniform density. Second, we solve interstitial lattice errors caused by robots clumping too close together by moving them towards the boundary with a clump remover algorithm. Finally, we determine when a configuration is on the verge of disconnecting by identifying local articulation points;regions where the removal of a single robot will change the local topology. When one is detected, we switch modes to a clustering algorithm that draws robots to the vulnerable region. The combination of these algorithms produces a cohesive configuration controller. We verify our resulting controller with simulations from random initial conditions and selected extreme cases. Simulation results show the controller successfully forms a configuration with natural resting density in twelve of trials and maintains connectivity in twelve trials. We also provide real-world experiments to show that proposed algorithms work under low-resolution sensor platforms.

关键词： Configuration control Robot Controllers Clustering algorithms Cooperating robots Boundary INITIAL CONDITIONS experimentation FLOCKING composite algorithm

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A General composite algorithms for Solving General Equilibrium Problems and Fixed Point Problems in Hilbert Spaces

ABSTRACT AND APPLIED ANALYSIS

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ABSTRACT AND APPLIED ANALYSIS 2011年第unknown期2011卷 1-25页

作者： Wangkeeree, Rattanaporn Kamraksa, Uthai Wangkeeree, Rabian Naresuan Univ Dept Math Fac Sci Phitsanulok 65000 Thailand

We introduce a general composite algorithm for finding a common element of the set of solutions of a general equilibrium problem and the common fixed point set of a finite family of asymptotically nonexpansive mappings in the framework of Hilbert spaces. Strong convergence of such iterative scheme is obtained which solving some variational inequalities for a strongly monotone and strictly pseudocontractive mapping. Our results extend the corresponding recent results of Yao and Liou (2010).

关键词： composite algorithm Minimization Equilibrium problem Fixed point problem Asymptotically nonexpansive mapping

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Herpes Zoster and Postherpetic Neuralgia Surveillance Using Structured Electronic Data

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MAYO CLINIC PROCEEDINGS 2011年第12期86卷 1146-1153页

作者： Klompas, Michael Kulldorff, Martin Vilk, Yury Bialek, Stephanie R. Harpaz, Rafael Harvard Univ Sch Med Dept Populat Med Boston MA 02215 USA Harvard Pilgrim Hlth Care Inst Boston MA 02215 USA Ctr Dis Control & Prevent Div Viral Dis Atlanta GA USA

OBJECTIVE: To develop electronic algorithms for rapid, automated surveillance for herpes zoster and postherpetic neuralgia (PHN) using codified electronic health data. PATIENTS AND METHODS: We attempted to identify every case of herpes zoster and PHN arising between January 1 and December 31, 2008, within the electronic medical record of a 560,000-patient ambulatory practice using an array of diagnosis codes;intervals between herpes zoster encounters;and prescriptions for analgesics, anticonvuisants, and antidepressants. We assessed the sensitivity and positive predictive value (PPV) of each screening criterion by medical record review and then integrated multiple criteria into combination algorithms to optimize sensitivity and PPV. We applied the optimized algorithms to the practice's historical data spanning January 1, 1996, to December 31, 2008, to assess for changes in the annual incidence of PHN. RESULTS: The International Classification of Diseases, Ninth Revision, code 053 detected herpes zoster with 98% sensitivity and 93% PPV. A combination algorithm including diagnosis codes, visit intervals, and prescriptions detected PHN with 86% sensitivity and 78% PPV. Between 1996 and 2008, the age- and sex-adjusted annual incidence of PHN rose from 0.18 to 0.47 cases per 1000 patients, and the proportion of herpes zoster patients progressing to PHN rose from 5.4% to 17.6%. CONCLUSION: Novel algorithms incorporating multiple streams of electronic health data can reasonably detect herpes zoster and PHN. These algorithms could facilitate meaningful public health surveillance using electronic health data. The incidence of PHN may be increasing. Mayo din Proc. 2011;86(12):1146-1/53

关键词： Prescriptions Electronic Health Records PHN composite algorithm p-phenyl vinyl Herpes Zoster

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Applying soft computing for remote sensing data composite algorithms

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ARTIFICIAL LIFE AND ROBOTICS 2010年第4期15卷 512-514页

作者： Mackin, Kenneth J. Yamaguchi, Takashi Park, Jong Geol Nunohiro, Eiji Matsushita, Kotaro Yanagisawa, Yukio Igarashi, Masao Tokyo Univ Informat Sci Dept Informat Syst Wakaba Ku 4-1 Onaridai Chiba Japan Tokyo Univ Informat Sci Dept Environm Informat Chiba Japan Nihon Univ Coll Bioresource Sci Kanagawa Japan

Remote sensing of the earth's surface using satellite-mounted sensor data is one of the most important methods for global environmental monitoring today. However, when using satellite sensor data, clouds in the atmosphere can interfere with the remote sensing, and specific land points may not be correctly monitored on any given day. In order to overcome this problem, a common alternative is to use multiple day composite data. Multiple day composite data use several consecutive days' remote sensing data, and choose the most accurate data within the temporal dataset for the same land point. This allows the creation of a more complete dataset by patching together data which have had no cloud interference during a specified time period in order to create a clearer, more usable dataset. In this article, we propose the application of soft computing, namely fuzzy logic, in order to select the clearest data in the temporal interval to use for the composite data. Moderate resolution remote sensing data of areas in Japan were used for the evaluation, and the results were compared with previous composite methods.

关键词： Remote sensing composite algorithm MODIS Fuzzy logic

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