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Development of computational algorithms for daily water leak detection in district metered areas based on the principal component analysis

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DESALINATION AND WATER TREATMENT 2021年 227卷 93-103页

作者： Park, Suwan Ha, Jae-Hong Pusan Natl Univ Dept Civil & Environm Engn Busan 46241 South Korea Seoyong Engn Yongin 16950 South Korea

Techniques for detecting leakage in water pipe networks have been developed worldwide in order to reduce unaccounted-for water quantity and enhance the reliability of the pipe networks. In this paper computational algorithms utilizing principal component analysis (PCA) were developed so that the algorithms can be used in a realistic water pipe network management situation in which the daily flow data of a district metered area (DMA) are needed to be verified for a possible relation with a water leak incident. For the improvement of the algorithms, it was assumed that a manager of a water pipe network uses these algorithms every day to test if yesterday's inflow data to a DMA were an outlier according to the PCA computational algorithm. The flow data used in this study were analyzed to determine the best flow data size for the field use of the developed PCA algorithm. For various flow data sets, which were defined as the smaller sizes of the flow measured in days than the whole data set available, a reference modeling for the PCA was applied to calculate the model outliers by moving the flow data sets day by day. For each DMA the effective outlier detection rates (EODRs) were calculated for the whole range of the defined time windows. The maximum effective outlier detection rate for a DMA was obtained as the maximum of the calculated EODRs. The process and results of the sensitivity analyses of the model parameters were used to suggest guidance on how to determine model parameters for a given flow data.

关键词： Principal component analysis District metered area Water pipe network Leak detection computational algorithm Flow data

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Static output feedback strategy for mean-field social control with nonlinear stochastic dynamics

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2025年

作者： Mukaidani, Hiroaki Xu, Hua Zhuang, Weihua Hiroshima Univ Grad Sch Adv Sci & Engn 1-4-1 Kagamiyama Higashihiroshima 7398527 Japan Univ Tsukuba Grad Sch Business Sci Bunkyo Ku Tokyo Japan Univ Waterloo Dept Elect & Comp Engn Waterloo ON Canada

A mean-field social control problem for uncertain nonlinear stochastic systems is investigated by using a robust static output feedback (SOF) strategy. First, the problem in the single decision maker case is investigated in terms of guaranteed cost control approaches to derive suboptimal conditions at the supremum of the cost function. The Karush-Kuhn-Tucker (KKT) condition is used to derive the necessary conditions which are expressed as a large stochastic combined matrix equation (SCME). Second, the preliminary results in the single decision maker case are used to study the Pareto optimal strategy in a cooperative game. As our main contribution, we derive the high-order centralised strategies and the low-order decentralised strategies, respectively, for the cooperative game. In order to avoid the difficulty of higher-order dimensional problem related to SCMEs, a new reduced-order decomposition numerical scheme by means of Newton's method is developed. The computation for designing the proposed strategy set can be performed in low dimension, even when the number of decision makers approachs to infinity. Moreover, the degradation of the cost function is rigorously evaluated by comparing the centralised strategy set with the proposed strategy set. Finally, several numerical experiments are conducted to demonstrate the usefulness and effectiveness of the proposed strategy set.

关键词： Mean-field social control multiple decision makers reduced-order technique computational algorithm uncertain nonlinear stochastic system

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Automated detection of spreading depolarizations in electrocorticography

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SCIENTIFIC REPORTS 2025年第1期15卷 1-15页

作者： Puchala, Sreekar Muchnik, Ethan Ralescu, Anca Hartings, Jed A. Univ Cincinnati Dept Comp Sci Cincinnati OH 45267 USA Univ Oregon Dept Electrochem Eugene OR USA Univ Cincinnati Coll Med Dept Neurosurg 231 Albert Sabin Way Cincinnati OH 45267 USA

Spreading depolarizations (SD) in the cerebral cortex are a novel mechanism of lesion development and worse outcomes after acute brain injury, but accurate diagnosis by neurophysiology is a barrier to more widespread application in neurocritical care. Here we developed an automated method for SD detection by training machine-learning models on electrocorticography data from a 14-patient cohort that included 1,548 examples of SD direct-current waveforms as identified in expert manual scoring. As determined by leave-one-patient-out cross-validation, optimal performance was achieved with a gradient-boosting model using 30 features computed from 400-s electrocorticography segments sampled at 0.1 Hz. This model was applied to continuous electrocorticography data by generating a time series of SD probability [PSD(t)], and threshold PSD(t) values to trigger SD predictions were determined empirically. The developed algorithm was then tested on a novel dataset of 10 patients, resulting in 1,252 true positive detections (/1,953;64% sensitivity) and 323 false positives (6.5/day). Secondary manual review of false positives showed that a majority (224, or 69%) were likely real SDs, highlighting the conservative nature of expert scoring and the utility of automation. SD detection using sparse sampling (0.1 Hz) is optimal for streaming and use in cloud computing applications for neurocritical care.

关键词： Spreading depolarization Spreading depression Electroencephalography Machine learning Automated detection computational algorithm Neurocritical care

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Mathematical models and computational algorithms for probit-based asymmetric stochastic user equilibrium problem with elastic demand

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TRANSPORTMETRICA 2012年第4期8卷 261-290页

作者： Meng, Qiang Liu, Zhiyuan Natl Univ Singapore Dept Civil Engn Singapore 117576 Singapore

This article addresses model development and computational algorithm design for the probit-based asymmetric stochastic user equilibrium (SUE) problem with elastic demand. Two variational inequality (VI) models are first proposed for the SUE problem and then existence and uniqueness of their solutions are examined. These two VI models are, in reality, built by means of a probit-based stochastic network loading (SNL) map. Since there is no computational procedure available for calculating the SNL map, we thus propose a two-stage Monte Carlo simulation-based method to estimate the SNL map. To compromise computational time with accuracy in the estimation, a lower bound of sample size required by the Monte Carlo simulation is also investigated. Based on these two VI models and Monte Carlo simulation-based method, we design two hybrid predictioncorrection (PC) cost averaging (CA) algorithms for solving the SUE problem. Finally, two numerical examples are carried out to assess performance of the proposed algorithms.

关键词： probit-based stochastic user equilibrium elastic demand asymmetric link travel time functions variational inequality computational algorithm

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computational methods for performance evaluation of a statistical multiplexer supporting bursty traffic

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IEEE-ACM TRANSACTIONS ON NETWORKING 1996年第3期4卷 386-397页

作者： Wu, GL Mark, JW UNIV WATERLOO DEPT ELECT & COMP ENGNWATERLOOON N2L 3G1CANADA

A statistical multiplexer supporting a number of bursty sources is modeled as a discrete time, single server queueing system with an infinite buffer. The probability generating function (PGF) method is used to analyze the queueing behavior. The PGF method requires the determination of a large number of boundary values and, hence, the roots of the characteristic equation. An iterative algorithm to evaluate the characteristic roots is proposed. When the arrival process is a superposition of independent processes, a decomposition approach is used to reduce the state space involved in the computational algorithm. Additionally, the computational algorithm is made efficient through the establishment of conditions under which all the roots are either real or nonnegative real numbers. A set of equations to recursively compute the moments of the queue length are established. Sample applications of the computational methods to evaluate the performance of a multiplexer supporting voice and video sources, modeled by two-state Markov and L-state MMPP processes, respectively, demonstrate the viability of the proposed methods.

关键词： Multiplexing Queueing Theory Discrete Time Systems Probability Iterative Methods State Space Methods Recursive Functions computational Complexity Markov Processes Stochastic Processes Visual Communication Telecommunication Traffic computational Methods Performance Evaluation Statistical Multiplexer Bursty Traffic Bursty Sources Discrete Time Single Server Queueing System Infinite Buffer Probability Generating Function Method Boundary Values Characteristic Equation Iterative algorithm Arrival Process Decomposition Approach State Space computational algorithm Queue Length Moments Recursive Method Voice Source Video Source Two State Markov Processes L State MMPP Processes Markov Modulated Poisson Process Multiplexing Iterative algorithms Aggregates Quantum Computing Probability Streaming Media Traffic Control computational Complexity Poisson Equations Queueing Analysis

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A computational model for suspended large rigid bodies in 3D unsteady viscous flows

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JOURNAL OF computational PHYSICS 1999年第2期155卷 348-379页

作者： Xiao, F RIKEN Inst Phys & Chem Res Sci Computat Lab Wako Saitama 3510198 Japan

A 3D numerical model for computing large rigid objects suspended in fluid flow has been developed. Rather than calculating the surface pressure upon the solid body, we evaluate the net force and torque based on a volume force formulation. The total effective force is obtained by summing up the forces at the Eulerian grids occupied by the rigid body. The effects of the moving bodies are coupled to the fluid flow by imposing the velocity field of the bodies to the fluid. A Poisson equation is used to compute the pressure over the whole domain. The objects are identified by color functions and calculated by the PPM scheme and a tangent function transformation which scales the transition region of the computed interface to a compact thickness. The model is then implemented on a parallel computer of distributed memory and validated with Stokes and low Reynolds number hows. (C) 1999 Academic Press.

关键词： computational algorithm fluid dynamics large suspended objects multiphase flows low Reynolds number parallel computing

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Mapping a neutralizing epitope on the SARS coronavirus spike protein: computational prediction based on affinity-selected peptides

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JOURNAL OF MOLECULAR BIOLOGY 2006年第1期359卷 190-201页

作者： Tarnovitski, Natalia Matthews, Leslie J. Sui, Jianhua Gershoni, Jonathan M. Marasco, Wayne A. Tel Aviv Univ George S Wise Fac Life Sci Dept Cell Res & Immunol IL-69978 Tel Aviv Israel Harvard Univ Sch Med Dana Farber Canc Inst Dept Canc Immunol & AIDS Boston MA 02115 USA Harvard Univ Sch Med Dept Med Boston MA 02115 USA

Rapid elucidation of neutralizing antibody epitopes on emerging viral pathogens like severe acute respiratory syndrome (SARS) coronavirus (CoV) or highly pathogenic avian influenza H5N1 virus is of great importance for rational design of vaccines against these viruses. Here we combined screening of phage display random peptide libraries with a unique computer algorithm "Mapitope" to identify the discontinuous epitope of 80R, a potent neutralizing human anti-SARS monoclonal antibody against the spike protein. Using two different types of random peptide libraries which display cysteine-constrained loops or linear 13-15-mer peptides, independent panels containing 42 and 18 peptides were isolated, respectively. These peptides, which had no apparent homologous motif within or between the peptide pools and spike protein, were deconvoluted into amino acid pairs (AAPs) by Mapitope and the statistically significant pairs (SSPs) were defined. Mapitope analysis of the peptides was first performed on a theoretical model of the spike and later on the genuine crystal structure. Three clusters (A, B and C) were predicted on both structures with remarkable overlap. Cluster A ranked the highest in the algorithm in both models and coincided well with the sites of spike protein that are in contact with the receptor, consistent with the observation that 80R functions as a potent entry inhibitor. This study demonstrates that by using this novel strategy one can rapidly predict and identify a neutralizing antibody epitope, even in the absence of the crystal structure of its target protein. (c) 2006 Elsevier Ltd. All rights reserved.

关键词： SARS antibody epitope Mapitope computational algorithm

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Derivation of computational formulas for certain class of finite sums: Approach to generating functions arising from p$$ p $$-adic integrals and special functions

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MATHEMATICAL METHODS IN THE APPLIED SCIENCES 2022年第16期45卷 9520-9544页

作者： Simsek, Yilmaz Univ Akdeniz Dept Math Fac Sci TR-07058 Antalya Turkey

The aim of this paper is to construct generating functions for certain families of special finite sums by using the Newton-Mercator series, hypergeometric functions, and p$$ p $$-adic integral. By using these generating functions with their functional and partial derivative equations, many novel computational formulas involving the special finite sums of (inverse) binomial coefficients, the Bernoulli type polynomials and numbers, Euler polynomials and numbers, the Stirling numbers, the (alternating) harmonic numbers, the Leibnitz polynomials, and others are derived. We also develop a computation algorithm for these finite sums and provide some of their special values. By using these finite sums and combinatorial numbers, we find some formulas involving multiple alternating zeta functions, the Bernoulli polynomials of higher order and the Euler polynomials of higher order. We then obtain a decomposition from these formulas, which are related to the multiple Hurwitz zeta functions.

关键词： computational algorithm finite sums generating function multiple alternating zeta functions p-adic integral special functions and special numbers

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COMPUTER-BASED TECHNIQUES FOR SOLVING PROBLEMS OF APPLIED AND computational MATHEMATICS WITH GIVEN QUALITY CHARACTERISTICS

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CYBERNETICS AND SYSTEMS ANALYSIS 2006年第5期42卷 641-648页

作者： Sergienko, I. V. Zadiraka, V. K. Babich, M. D. Berezovskii, A. I. Besarab, P. N. Lyudvichenko, V. A. Natl Acad Sci Ukraine VM Glushkov Inst Cybernet Kiev Ukraine 2Ukrainian Acad Foreign Trade Kiev Ukraine Int Acad Human Resource Management MAUP Kiev Ukraine

The paper is concerned with computer-based techniques for the choice and development of computational resources and their efficient use to find an approximate solution with a given accuracy in a limited processor time.

关键词： computer-based techniques mathematical model of applied problem computational model computational process computational algorithm estimates of quality characteristics of computational algorithm

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Bootstrapping the lexicon: A computational model of infant speech segmentation

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COGNITION 2002年第2期83卷 167-206页

作者： Batchelder, EO CUNY Grad Ctr New York NY USA

Prelinguistic infants must find a way to isolate meaningful chunks from the continuous streams of speech that they hear. BootLex, a new model which uses distributional cues to build a lexicon, demonstrates how much can be accomplished using this single source of information. This conceptually simple probabilistic algorithm achieves significant segmentation results on various kinds of language corpora - English, Japanese, and Spanish: child- and adult-directed speech, and written texts;and several variations in coding structure - and reveals which statistical characteristics of the input have an influence on segmentation performance. BootLex is then compared, quantitatively and qualitatively, with three other groups of computational models of the same infant segmentation process, paying particular attention to functional characteristics of the models and their similarity to human cognition. Commonalities and contrasts among the models are discussed, as well as their implications both for theories of the cognitive problem of segmentation itself, and for the general enterprise of computational cognitive modeling. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： speech segmentation infants computational algorithm probabilistic cues cognitive models

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