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Application of the Multistep Generalized Differential Transform Method to Solve a Time-Fractional Enzyme Kinetics

DISCRETE DYNAMICS IN NATURE AND SOCIETY 2013年第unknown期2013卷 592938-1-592938-7页

作者： Alawneh, Ahmed Princess Sumaya Univ Technol Dept Sci & Humanities Amman 11941 Jordan

The multistep differential transform method is first employed to solve a time-fractional enzyme kinetics. This enzyme-substrate reaction is formed by a system of nonlinear ordinary differential equations of fractional order. The fractional derivatives are described in the Caputo sense. A comparative study between the new algorithm and the classical Runge-Kutta method is presented in the case of integer-order derivatives. The results demonstrate reliability and efficiency of the algorithm developed.

关键词： Application multustep generalized Generalise Solve Runge-Kutta methods Enzyme kinetics Ordinary differential equation Transform Differential algorithm efficiency

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Estimation of temporal scales of variation in long-term scalp electroencephalograms from epilepsy patients

Estimation of temporal scales of variation in long-term scal...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Catherine Stamoulis Bernard S. Chang Departments of Radiology and Neurology Boston Children's Hospital and Harvard Medical School

ISBN: (纸本)9781457702150

Long-term neurophysiological recordings, such as scalp encephalograms (EEG), have been routinely used in studies that aim to characterize dynamic changes in brain activity associated with normal biological processes, such as sleep, but are also becoming increasingly common for clinical evaluation of patients with neurological disorders, such as epilepsy. Analysis of non-stationary recordings from multiple days poses new signal processing challenges, in regard to algorithm efficiency and computational cost, as well as adequate dimensionality data reduction. We compared four approaches for estimating the underlying temporal dynamics of long-term recordings from patients with medically refractory epilepsy: (i) model order selection using the minimum description length principle, (ii) approximate entropy, (iii) mutual information, and (iv) Detrended Fluctuation Analysis (DFA). Individual approaches were found to be sensitive only to specific scales of variation. Approximate entropy and mutual information were sensitive to local dynamics, whereas dynamic model order estimation captured only slowly varying dynamics. DFA was sensitive to multiple temporal scales.

关键词： Scalp brain activity clinical investigation algorithm efficiency temporal variations Recordings Epilepsy Neurologic Disorders Biological Process

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A Reconstruction algorithm for Point-wise Sources in a Two-dimension Electroencephalography Model

A Reconstruction Algorithm for Point-wise Sources in a Two-d...

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International Conference on Fuzzy Systems and Knowledge Discovery

作者： Hongyan Wang Jiayin Sun Yuan Li Zejing Xing Lixin Feng School of Mathematical Sciences Heilongjiang University School of Humanities and Social Sciences Harbin Institute of Technology

ISBN: (纸本)9781467352512

This paper proposes a computing algorithm for reconstructing point-wise sources in an inverse electroencephalog-raphy problem, where only a two-dimension model for boundary problem of Poisson equation is considered. Based on the variational form of this boundary value problem, we select a special form of complex polynomial as the test function, and then derive an algebraic relationship among the source parameters. Then the point-wise sources can be reconstructed by using an algebraic direct method. We present that this algebraic direct algorithm is suitable for both monopole sources and dipole sources. Finally, a few numerical examples are demonstrated to verify the efficiency of this algorithm.

关键词： Reconstruction algorithm Boundary value problems Poisson equation Algebra Electroencephalography algorithm efficiency dimensional modules

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Designing multi-objective multi-armed bandits algorithms: a study

Designing multi-objective multi-armed bandits algorithms: a ...

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International Joint Conference on Neural Networks

作者： Madalina M. Drugan Ann Nowe Computational Modeling lab Artificial Intelligence group of Computer Science Department Vrije Universiteit Brussels Pleinlaan 2 B-1050 Brussels Belgium

ISBN: (纸本)9781467361279

We propose an algorithmic framework for multi-objective multi-armed bandits with multiple rewards. Different partial order relationships from multi-objective optimization can be considered for a set of reward vectors, such as scalarization functions and Pareto search. A scalarization function transforms the multi-objective environment into a single objective environment and are a popular choice in multi-objective reinforcement learning. Scalarization techniques can be straightforwardly implemented into the current multi-armed bandit framework, but the efficiency of these algorithms depends very much on their type, linear or non-linear (e.g. Chebyshev), and their parameters. Using Pareto dominance order relationship allows to explore the multi-objective environment directly, however this can result in large sets of Pareto optimal solutions. In this paper we propose and evaluate the performance of multi-objective MABs using three regret metric criteria. The standard UCB1 is extended to scalarized multi-objective UCB1 and we propose a Pareto UCB1 algorithm. Both algorithms are proven to have a logarithmic upper bound for their expected regret. We also introduce a variant of the scalarized multi-objective UCB1 that removes online inefficient scalarizations in order to improve the algorithm's efficiency. These algorithms are experimentally compared on multi-objective Bernoulli distributions, Pareto UCB1 being the algorithm with the best empirical performance.

关键词： study multiple rewards reward vectors algorithms algorithm efficiency Regret optimal solution Reward Environments

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Human Like Learning algorithm for Simultaneous Force Control and Haptic Identification

Human Like Learning Algorithm for Simultaneous Force Control...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Chenguang Yang Zhijun Li Etienne Burdet School of Computing and Mathematics University of Plymouth UK Key Laboratory of Autonomous Sysems and Netowked Control Ministry of Education Guangzhou 510640 China Department of Bioengineering Imperial College of Science Technology and Medicine London UK

ISBN: (纸本)9781467363563

This paper develops a learning control algorithm adapting the reference point and force to interact with an object of unknown geometry and elasticity. The controller is inspired by neuroscience studies that investigated the neural mechanisms when human adapt to virtual objects of different properties. The learning control algorithm estimates the shape and stiffness of the given object while maintaining a specified contact force with the environment. Simulations demonstrate the efficiency of the algorithm to identify the geometry and impedance of an unknown object without requiring force sensing. These properties are attractive for robotic haptic exploration with little demand on the sensing.

关键词： learning algorithms Force control Computer algorithms reference station Human learning control CONTACT FORCE algorithm efficiency Neurosciences Neurophysiology algorithms geometry impedance

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Application of the method of incomplete cross approximation to a nonstationary problem of vortex rings dynamics

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RUSSIAN JOURNAL OF NUMERICAL ANALYSIS AND MATHEMATICAL MODELLING 2012年第3期27卷 303-320页

作者： Stavtsev, S. L. Inst Numer Math Moscow 119333 Russia

An application of the method of incomplete cross approximation for solving a problem of vortex ring dynamics is described in the paper. A formulation of the problem and its solver based on the method of discrete vortices are presented. An adaptation of the incomplete cross approximation algorithm for the solution of nonstationary problems essentially improves computations in the problem described in this paper. A series of techniques improving the convergence is presented. The efficiency of the algorithms is confirmed by the results of numerical experiments.

关键词： Solvers dynamics Problem Formulation approximation transversality application methods vortex state (superconductivity) algorithm efficiency

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SOLVING WEIGHTED MAX-CUT PROBLEM BY GLOBAL EQUILIBRIUM SEARCH

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CYBERNETICS AND SYSTEMS ANALYSIS 2012年第4期48卷 563-567页

作者： Shylo, V. P. Shylo, O. V. Roschyn, V. A. Natl Acad Sci Ukraine VM Glushkov Inst Cybernet Kiev Ukraine Univ Pittsburgh Pittsburgh PA 15260 USA

A new algorithm based on the global equilibrium search (GES) is developed to solve the weighted max-cut problem and is compared with currently the best solution algorithms. The advantages of the GES algorithm both in ... 详细信息

关键词： maximum weighted cut of a graph global equilibrium search computing experiment algorithm efficiency

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Investigation of hidden parameters influencing the automated object detection in images from the deep seafloor of the HAUSGARTEN observatory

Investigation of hidden parameters influencing the automated...

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MTS/IEEE Oceans Conference

作者： Schoening, Timm Bergmann, Melanie Nattkemper, Tim W. Univ Bielefeld Biodata Min Grp Fac Technol D-33615 Bielefeld Germany Alfred Wegener Inst Polar & Marine Res HGF MPG Grp Deep Sea Ecol & Technol Bremerhaven Germany

ISBN: (纸本)9781467308298;9781467308304

Detecting objects in underwater image sequences and video frames automatically, requires the application of selected algorithms in consecutive steps. Most of these algorithms are controlled by a set of parameters, which need to be calibrated for an optimal detection result. Those parameters determine the effectivity and efficiency of an algorithm and their impact is usually well known. There are however further non-algorithmic impact factors (or hidden parameters), which bias the training of a machine learning system as well as the subsequent detection process and thus need to be well understood and taken into account. In the context of megafauna detection in benthic images, we investigate the effects of some of these parameters on our machine learning based detection system iSIS. The images to be analyzed were taken at the deep-sea, long-term observatory HAUSGARTEN in which five experts labeled seven distinct object classes as an annotation gold standard. We found, that the hidden parameters from imaging as well as the fusion of expert knowledge could partly be compensated and were able to achieve detection performances of 0.67 precision and 0.87 recall. Despite the efforts to compensate the hidden parameters, the detection performance was still varying across the image transect. This poses the potential occurrence of further hidden parameters not taken into account so far.

关键词： ocean floors images parameters Astronomical observatories optimum detection impact factor Object detection image sequences Expert Opinion WELLS Artificial Intelligence Machine Learning algorithms algorithm efficiency

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Echo State Network-based Credit Rating System

Echo State Network-based Credit Rating System

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4th IEEE International Symposium on Logistics and Industrial Informatics (LINDI)

作者： Bozsik, Jozsef Ilonczai, Zsolt Eotvos Lorand Univ Dept Software Technol & Methodol H-1117 Budapest Hungary

ISBN: (纸本)9781467345194

Nowadays credit rating is of paramount importance in our economic system. In this article a new approach on financial credit rating will be demonstrated. Unlike many classical credit rating methods, the power of this solution lies in the use of artificial intelligence, which is getting more and more prevalent in economics [J. Bozsik, Neural Fuzzy System for Default Forecasts, 11th International Symposium on Computational Intelligence and Informatics, 18-20 Nov. 2010, Budapest, Hungary, pp. 69-74]. The goal has been to create an echo state network-based artificial system, which can provide an effective and reliable way to solve the credit rating task. Besides describing the theoretical background of the echo state network-based solution, this article also focuses on the efficiency of the algorithm and the potential problems in different situations, revealing their solutions as well. As closure, tests will be provided to illustrate the effectiveness of the system.

关键词： Echoes resting state network US networks Computational intelligence Fuzzy systems Corona Austrina algorithm efficiency

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On Discovery of Traveling Companions from Streaming Trajectories

On Discovery of Traveling Companions from Streaming Trajecto...

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28th IEEE International Conference on Data Engineering (ICDE)

作者： Tang, Lu-An Zheng, Yu Yuan, Jing Han, Jiawei Leung, Alice Hung, Chih-Chieh Peng, Wen-Chih Univ Illinois Urbana IL 61801 USA Microsoft Res Asia Beijing Peoples R China Univ Sci & Technol Anhui Sheng Peoples R China BBN Technol Cambridge MA USA Yahoo Inc Sunnyvale CA USA Natl Chiao Tung Univ Hsinchu Taiwan

ISBN: (纸本)9781467300421

The advance of object tracking technologies leads to huge volumes of spatio-temporal data collected in the form of trajectory data stream. In this study, we investigate the problem of discovering object groups that travel together (i.e., traveling companions) from streaming trajectories. Such technique has broad applications in the areas of scientific study, transportation management and military surveillance. To discover traveling companions, the monitoring system should cluster the objects of each snapshot and intersect the clustering results to retrieve moving-together objects. Since both clustering and intersection steps involve high computational overhead, the key issue of companion discovery is to improve the efficiency of algorithms. We propose the models of closed companion candidates and smart intersection to accelerate data processing. A data structure termed traveling buddy is designed to facilitate scalable and flexible companion discovery from streaming trajectories. The traveling buddies are micro-groups of objects that are tightly bound together. By only storing the object relationships rather than their spatial coordinates, the buddies can be dynamically maintained along trajectory stream with low cost. Based on traveling buddies, the system can discover companions without accessing the object details. The proposed methods are evaluated with extensive experiments on both real and synthetic datasets. The buddy-based method is an order of magnitude faster than baselines. It also achieves higher precision and recall in companion discovery.

关键词： Companions trajectory Object Relationship algorithm efficiency trajectory data program area new data Snapshots advance streams monitoring systems

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