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IMPROVED TIME-BOUNDS FOR THE MAXIMUM FLOW PROBLEM: 收藏
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引用; SIAM JOURNAL ON COMPUTING 1989年第5期18卷 939-954页; 作者： AHUJA, RK ORLIN, JB TARJAN, RE PRINCETON UNIV DEPT COMP SCIPRINCETONNJ 08544 AT&T BELL LABS MURRAY HILLNJ 07974; Recently, Goldberg proposed a new approach to the maximum network flow problem. The approach yields a very simple algorithm running in O(n3)<span style="display: inline-bloc; Recently, Goldberg proposed a new approach to the maximum network flow problem. The approach yields a very simple algorithm running in $O (n^{3})$; 来源：评论; 学校读者我要写书评

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An efficient algorithm for the exact test on unordered 2 x J contingency tables with equal column sums

COMPUTATIONAL STATISTICS & DATA ANALYSIS 1997年第3期25卷 273-285页

作者： Shao, XM UNIV CALIF LOS ANGELES DEPT PHYSIOL SCI SYST NEUROBIOL LAB LOS ANGELES CA 90095 USA

An efficient algorithm for Fisher's exact test on unordered 2 x J contingency tables is proposed based on the network algorithm described by Mehta and Patel (1980, 1983). When either all or some of the column sums are equal, this method substantially reduces the computational effort needed to obtain the exact p-value. The principal computational efficiency is gained from the idea that the network size could be reduced by multiplying the probabilities of equivalent tables in which the first row entries are permutation of each other rather than creating them repeatedly and summing up their probabilities. The ranges of the nodes in the network and the ranges of the arcs emanating from each node to the nodes at the succeeding stages are redefined, so that the algorithm creates only the representatives of equivalent tables which are permutationally distinct without missing any possible table. An equation to calculate the numbers of equivalent tables is given. This method is also applicable to exact Pearson chi-squared and exact likelihood ratio tests. Some numerical examples are presented to compare the computational time of the improved algorithm with the original network algorithm. (C) 1997 Elsevier Science B.V.

关键词： Fisher's exact test 2 x J contingency table network algorithm

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The arctic mouse-ear in Scotland - and why it is not arctic

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PLANT ECOLOGY & DIVERSITY 2008年第2期1卷 321-327页

作者： Brysting, Anne K. Univ Oslo Dept Biol Ctr Ecol & Evolutionary Synth Oslo Norway

Background: The arctic mouse-ear (Cerastium nigrescens, Caryophyllaceae) growing in the Scottish Highlands has a turbulent taxonomic (and nomenclatural) history, probably reflecting the complex allopolyploid origin of this high-polyploid species. It belongs to an intricate arctic-alpine species group (the C. alpinum complex) which has a reticulate evolutionary history formed through repeated hybridisation and polyploidisation events. Aims: In this paper, the position of the Scottish plant is discussed in the light of recently published sequence data from the whole complex. Methods: Sequences of a low-copy number nuclear gene (RPB2) of a few Scottish plants were obtained and compared to previously obtained sequences of C. nigrescens from other geographical areas, other closely related high-polyploid species as well as possible tetraploid progenitor taxa. Main findings: A network produced from the RPB2 sequences clearly showed that the dodecaploid plant growing in the Scottish Highlands has a common origin with C. nigrescens from Scandinavia and Shetland. By using the same approach, it was also possible to identify hybrids among Scottish plants resulting from interploidal crosses between C. alpinum (8x) and C. nigrescens (12x). Such hybrids possessed a combination of RPB2 sequences from these two parental species. Conclusions: The Scottish C. nigrescens shares its evolutionary history with C. nigrescens from Shetland and mainland Norway, and this non-arctic taxon is clearly separated from the artic taxon, C. arcticum, with which it has previously been considered conspecific.

关键词： allopolyploidy interploidal gene flow low-copy nuclear region network algorithm

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The automated malnutrition assessment

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NUTRITION 2013年第1期29卷 113-121页

作者： David, Gil Bernstein, Larry Howard Coifman, Ronald R. Yale Univ Dept Math Program Appl Math New Haven CT 06520 USA New York Methodist Hosp Cornell Weill New York NY USA

Objective: We propose an automated nutritional assessment algorithm that provides a method for malnutrition risk prediction with high accuracy and reliability. Methods: The database used for this study was a file of 432 patients, where each patient was described by 4 laboratory parameters and 11 clinical parameters. A malnutrition risk assessment of low (1), moderate (2), or high (3) was assigned by a dietitian for each patient. An algorithm for data organization and classification using characteristic metrics for each patient was developed. For each patient, the algorithm characterized the patients' unique profile and built a characteristic metric to identify similar patients who were mapped into a classification. For each patient, the algorithm characterized the patients' classification. Results: The algorithm assigned a malnutrition risk level for different training sizes that were taken from the data. Our method resulted in average errors (distance between the automated score and the real score) of 0.386, 0.3507, 0.3454, 0.34, and 0.2907 for the 10%, 30%, 50%, 70%, and 90% training sizes, respectively. Our method outperformed the compared method even when our method used a smaller training set than the compared method. In addition, we showed that the laboratory parameters themselves were sufficient for the automated risk prediction and organized the patients into clusters that corresponded to low-, low-moderate-, moderate-, moderate-high-, and high-risk areas. The organization and visualization methods provided a tool for the exploration and navigation of the data points. Conclusion: The problem of rapidly identifying risk and severity of malnutrition is crucial for minimizing medical and surgical complications. These are not easily performed or adequately expedited. We characterized for each patient a unique profile and mapped similar patients into a classification. We also found that the laboratory parameters were sufficient for the automated risk prediction.

关键词： network algorithm Unsupervised classification Malnutrition screening Protein-energy malnutrition Malnutrition risk Characteristic metric Characteristic profile Data characterization Non-linear differential diagnosis

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Railway timetabling: a maximum bottleneck path algorithm for finding an additional train path

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PUBLIC TRANSPORT 2021年第3期13卷 597-623页

作者： Ljunggren, Fredrik Persson, Kristian Peterson, Anders Schmidt, Christiane Linkoping Univ Commun & Transport Syst ITN Norrkoping Sweden Trafikverket Stockholm Sweden Sweco Stockholm Sweden

We present an algorithm to insert a train path in an existing railway timetable close to operation, when we want to affect the existing (passenger) traffic as little as possible. Thus, we consider all other trains as fixed, and aim for a resulting train path that maximizes the bottleneck robustness, that is, a train path that maximizes the temporal distance to neighboring trains in the timetable. Our algorithm is based on a graph formulation of the problem and uses a variant of Dijkstra's algorithm. We present an extensive experimental evaluation of our algorithm for the Swedish railway stretch from Malmo to Hallsberg. Moreover, we analyze the size of our constructed graph.

关键词： Railway timetabling Robust train path Bottleneck train path network algorithm Freight transportation

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GENERATING STRUCTURE SPECIFIC networkS

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ADVANCES IN COMPLEX SYSTEMS 2010年第2期13卷 239-250页

作者： Hakansson, N. Jonsson, A. Lennartsson, J. Lindstrom, T. Wennergren, U. Skovde Univ Syst Biol Res Ctr S-54128 Skovde Sweden Linkoping Univ IFM Therory & Modeling S-58183 Linkoping Sweden

Theoretical exploration of network structure significance requires a range of different networks for comparison. Here, we present a new method to construct networks in a spatial setting that uses spectral methods in combination with a probability distribution function. Nearly all previous algorithms for network construction have assumed randomized distribution of links or a distribution dependent on the degree of the nodes. We relax those assumptions. Our algorithm is capable of creating spectral networks along a gradient from random to highly clustered or diverse networks. Number of nodes and link density are specified from start and the structure is tuned by three parameters (gamma, sigma, kappa). The structure is measured by fragmentation, degree assortativity, clustering and group betweenness of the networks. The parameter gamma regulates the aggregation in the spatial node pattern and sigma and kappa regulates the probability of link forming.

关键词： network spectral assortativity fragmentation clustering betweenness centralization spatial network network algorithm

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Exact family-based association tests for biallelic data

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GENETIC EPIDEMIOLOGY 2005年第3期29卷 185-194页

作者： Schneiter, K Laird, N Corcoran, C Harvard Univ Sch Publ Hlth Dept Biostat Boston MA 02115 USA Utah State Univ Dept Math & Stat Logan UT 84322 USA

Family-based study designs have an important role in the search for association between disease phenotypes and genetic markers. Unlike traditional case-control methods, family-based tests use within-family data to avoid identification of spurious associations that may result from population admixture. Many family-based association tests have been proposed to accommodate a variety of ascertainment schemes and patterns of missing data. In this report, we describe exact family-based association tests for biallelic data. Specifically, we discuss test of the null hypotheses "no linkage and no association" and "linkage, but no association". These tests, which are valid under various models for inheritance and patterns of missingness, utilize the procedure proposed by Rabinowitz and Laird [2000: Hum Hered 50:211-223] that provides a unified framework for family based association testing (FBAT). The conditioning approach implemented in FBAT makes an exact test conceptually straightforward, but computationally difficult since the minimum sufficient statistics upon which we condition do not have a conventional form. An exact test may be especially critical when accurate computation of the extreme area of the FBAT statistic is needed, such as when the study design necessitates multiple comparisons adjustments. We describe the exact approach as a useful alternative to the aymptotic test and show that the exact tests for biallelic data may be most useful for the recessive disease model.

关键词： linkage genetic association network algorithm

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An investigation on environmental pollution due to essential heavy metals: a prediction model through multilayer perceptrons

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INTERNATIONAL JOURNAL OF PHYTOREMEDIATION 2023年第1期25卷 89-97页

作者： Sari, Murat Yalcin, Ibrahim Ertugrul Taner, Mahmut Cosgun, Tahir Ozyigit, Ibrahim Ilker Yildiz Tech Univ Fac Arts & Sci Dept Math Istanbul Turkey Bahcesehir Univ Fac Engn & Nat Sci Dept Civil Engn Istanbul Turkey Bahcesehir Univ Fac Engn & Nat Sci Dept Math Istanbul Turkey Amasya Univ Fac Arts & Sci Dept Math Amasya Turkey Marmara Univ Fac Arts & Sci Dept Biol Istanbul Turkey Kyrgyz Turkish Manas Univ Fac Sci Dept Biol Bishkek Kyrgyzstan

This research is to predict heavy metal levels in plants, particularly in Robinia pseudoacacia L., and soils using an effective artificial intelligence approach with some ecological parameters, thereby significantly eliminating common defects such as high cost and seriously tedious and time-consuming laboratory procedures. In this respect, the artificial neural network (ANN) is employed to estimate the concentrations of essential heavy metals such as Fe, Mn and Ni, depending on the Cu and Zn concentrations of plant and soil samples collected from five different locations. The derived relative errors for the constructed ANN model have been computed within the ranges 0.041-0.051, 0.017-0.025, and 0.026-0.029 for the training, testing and holdout data regarding Fe, Mn, and Ni, respectively. In addition, it has been realized that the relative errors could be diminished up to 0.007 for Fe, 0.014 for Mn and 0.022 for Ni by considering the Cu, Zn, location and plant parts as independent variables during the analysis. The results produced seem instructive and pioneering for environmentalists and scientists to design optimal study programs to leave a livable ecosystem. Novelty statement The levels of essential heavy metals, Fe, Mn, Ni, based on Zn and Cu in plant and soil samples have been predicted through an AI-based prediction model, a class of feedforward artificial neural networks (ANNs) with a multilayer perceptron (MLP). Thereby common drawbacks such as high cost and severely time-consuming laboratory procedures have been significantly eradicated. In the evaluation of different pollution levels at locations, it has been shown that the ANN method can overcome several disadvantages of analytical element analyzers to monitor the amounts of heavy metals such as Fe, Mn, and Ni in soil and plants.

关键词： Artificial neural network essential heavy metal network algorithm plant location plant part prediction model

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Cost-Efficient Resource Allocation Method for Heterogeneous Cloud Environments

INFOCOMMUNICATIONS JOURNAL

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INFOCOMMUNICATIONS JOURNAL 2018年第1期10卷 15-21页

作者： Szabo, Marton Hajay, David Szalayz, Mark Budapest Univ Technol & Econ Dept Telecommun & Media Informat Magyar Tudosok Krt 2 H-1117 Budapest Hungary

In this paper we present a novel on-line NFV (network Function Virtualization) orchestration algorithm for edge computing infrastructure providers that operate in a heterogeneous cloud environment. The goal of our algorithm is to minimize the usage of computing resources which are offered by a public cloud provider (e.g., Amazon Web Services), while fulfilling the required networking related constraints (latency, bandwidth) of the services to be deployed. We propose a reference network architecture which acts as a test environment for the evaluation of our algorithm. During the measurements, we compare our results to the optimal solution provided by an ILP-based solver.

关键词： orchestration network algorithm heterogeneous cloud fog computing cloud computing

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Synthesizing Signaling Pathways from Temporal Phosphoproteomic Data

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CELL REPORTS 2018年第13期24卷 3607-3618页

作者： Koksal, Ali Sinan Beck, Kirsten Cronin, Dylan R. McKenna, Aaron Camp, Nathan D. Srivastava, Saurabh MacGilvray, Matthew E. Bodik, Rastislav Wolf-Yadlin, Alejandro Fraenkel, Ernest Fisher, Jasmin Gitter, Anthony Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA 94720 USA Univ Washington Dept Genome Sci Seattle WA 98195 USA Univ Wisconsin Dept Biostat & Med Informat Madison WI USA Bowling Green State Univ Dept Biol Sci Bowling Green OH 43403 USA Univ Wisconsin Genet Lab Madison WI 53706 USA Univ Washington Paul G Allen Ctr Comp Sci & Engn Seattle WA 98195 USA MIT Dept Biol Engn 77 Massachusetts Ave Cambridge MA 02139 USA Microsoft Res Cambridge England Univ Cambridge Dept Biochem Cambridge England Morgridge Inst Res Madison WI USA Seattle Genet Seattle WA USA

We present a method for automatically discovering signaling pathways from time-resolved phosphoproteomic data. The Temporal Pathway Synthesizer (TPS) algorithm uses constraint-solving techniques first developed in the context of formal verification to explore paths in an interaction network. It systematically eliminates all candidate structures for a signaling pathway where a protein is activated or inactivated before its upstream regulators. The algorithm can model more than one hundred thousand dynamic phosphosites and can discover pathway members that are not differentially phosphorylated. By analyzing temporal data, TPS defines signaling cascades without needing to experimentally perturb individual proteins. It recovers known pathways and proposes pathway connections when applied to the human epidermal growth factor and yeast osmotic stress responses. Independent kinase mutant studies validate predicted substrates in the TPS osmotic stress pathway.

关键词： protein-protein interactions time series phosphorylation network algorithm program synthesis mass spectrometry

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