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Institution

University of New Brunswick

EducationFredericton, New Brunswick, Canada
About: University of New Brunswick is a education organization based out in Fredericton, New Brunswick, Canada. It is known for research contribution in the topics: Population & Adsorption. The organization has 10498 authors who have published 20654 publications receiving 474448 citations.


Papers
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Journal ArticleDOI
TL;DR: A precise definition of the basic reproduction number, R0, is presented for a general compartmental disease transmission model based on a system of ordinary differential equations and it is shown that, if R0<1, then the disease free equilibrium is locally asymptotically stable; whereas if R 0>1,Then it is unstable.
Abstract: A precise definition of the basic reproduction number, Ro, is presented for a general compartmental disease transmission model based on a system of ordinary dierential equations. It is shown that, if Ro 1, then it is unstable. Thus,Ro is a threshold parameter for the model. An analysis of the local centre manifold yields a simple criterion for the existence and stability of super- and sub-threshold endemic equilibria for Ro near one. This criterion, together with the definition of Ro, is illustrated by treatment, multigroup, staged progression, multistrain and vectorhost models and can be applied to more complex models. The results are significant for disease control.

7,106 citations

Proceedings ArticleDOI
08 Jul 2009
TL;DR: A new data set is proposed, NSL-KDD, which consists of selected records of the complete KDD data set and does not suffer from any of mentioned shortcomings.
Abstract: During the last decade, anomaly detection has attracted the attention of many researchers to overcome the weakness of signature-based IDSs in detecting novel attacks, and KDDCUP'99 is the mostly widely used data set for the evaluation of these systems. Having conducted a statistical analysis on this data set, we found two important issues which highly affects the performance of evaluated systems, and results in a very poor evaluation of anomaly detection approaches. To solve these issues, we have proposed a new data set, NSL-KDD, which consists of selected records of the complete KDD data set and does not suffer from any of mentioned shortcomings.

3,300 citations

Journal ArticleDOI
TL;DR: In this article, the authors considered the problem of estimating latent ability using the entire response pattern of free-response items, first in the general case and then in the case where the items are scored in a graded way, especially when the thinking process required for solving each item is assumed to be homogeneous.
Abstract: Estimation of latent ability using the entire response pattern of free-response items is discussed, first in the general case and then in the case where the items are scored in a graded way, especially when the thinking process required for solving each item is assumed to be homogeneous. The maximum likelihood estimator, the Bayes modal estimator, and the Bayes estimator obtained by using the mean-square error multiplied by the density function of the latent variate as the loss function are taken as our estimators. Sufficient conditions for the existence of a unique maximum likelihood estimator and a unique Bayes modal estimator are formulated with respect to an individual item rather than with respect to a whole set of items, which are useful especially in the situation where we are free to choose optimal items for a particular examinee out of the item library in which a sufficient number of items are stored with reliable quality controls. Advantages of the present methods are investigated by comparing them with those which make use of conventional dichotomous items or test scores, theoretically as well as empirically, in terms of the amounts of information, the standard errors of estimators, and the mean-square errors of estimators. The utility of the Bayes modal estimator as a computational compromise for the Bayes estimator is also discussed and observed. The relationship between the formula for the item characteristic function and the philosophy of scoring is observed with respect to dichotomous items.

3,031 citations

Journal ArticleDOI
Sabeeha S. Merchant1, Simon E. Prochnik2, Olivier Vallon3, Elizabeth H. Harris4, Steven J. Karpowicz1, George B. Witman5, Astrid Terry2, Asaf Salamov2, Lillian K. Fritz-Laylin6, Laurence Maréchal-Drouard7, Wallace F. Marshall8, Liang-Hu Qu9, David R. Nelson10, Anton A. Sanderfoot11, Martin H. Spalding12, Vladimir V. Kapitonov13, Qinghu Ren, Patrick J. Ferris14, Erika Lindquist2, Harris Shapiro2, Susan Lucas2, Jane Grimwood15, Jeremy Schmutz15, Pierre Cardol3, Pierre Cardol16, Heriberto Cerutti17, Guillaume Chanfreau1, Chun-Long Chen9, Valérie Cognat7, Martin T. Croft18, Rachel M. Dent6, Susan K. Dutcher19, Emilio Fernández20, Hideya Fukuzawa21, David González-Ballester22, Diego González-Halphen23, Armin Hallmann, Marc Hanikenne16, Michael Hippler24, William Inwood6, Kamel Jabbari25, Ming Kalanon26, Richard Kuras3, Paul A. Lefebvre11, Stéphane D. Lemaire27, Alexey V. Lobanov17, Martin Lohr28, Andrea L Manuell29, Iris Meier30, Laurens Mets31, Maria Mittag32, Telsa M. Mittelmeier33, James V. Moroney34, Jeffrey L. Moseley22, Carolyn A. Napoli33, Aurora M. Nedelcu35, Krishna K. Niyogi6, Sergey V. Novoselov17, Ian T. Paulsen, Greg Pazour5, Saul Purton36, Jean-Philippe Ral7, Diego Mauricio Riaño-Pachón37, Wayne R. Riekhof, Linda A. Rymarquis38, Michael Schroda, David B. Stern39, James G. Umen14, Robert D. Willows40, Nedra F. Wilson41, Sara L. Zimmer39, Jens Allmer42, Janneke Balk18, Katerina Bisova43, Chong-Jian Chen9, Marek Eliáš44, Karla C Gendler33, Charles R. Hauser45, Mary Rose Lamb46, Heidi K. Ledford6, Joanne C. Long1, Jun Minagawa47, M. Dudley Page1, Junmin Pan48, Wirulda Pootakham22, Sanja Roje49, Annkatrin Rose50, Eric Stahlberg30, Aimee M. Terauchi1, Pinfen Yang51, Steven G. Ball7, Chris Bowler25, Carol L. Dieckmann33, Vadim N. Gladyshev17, Pamela J. Green38, Richard A. Jorgensen33, Stephen P. Mayfield29, Bernd Mueller-Roeber37, Sathish Rajamani30, Richard T. Sayre30, Peter Brokstein2, Inna Dubchak2, David Goodstein2, Leila Hornick2, Y. Wayne Huang2, Jinal Jhaveri2, Yigong Luo2, Diego Martinez2, Wing Chi Abby Ngau2, Bobby Otillar2, Alexander Poliakov2, Aaron Porter2, Lukasz Szajkowski2, Gregory Werner2, Kemin Zhou2, Igor V. Grigoriev2, Daniel S. Rokhsar6, Daniel S. Rokhsar2, Arthur R. Grossman22 
University of California, Los Angeles1, United States Department of Energy2, University of Paris3, Duke University4, University of Massachusetts Medical School5, University of California, Berkeley6, Centre national de la recherche scientifique7, University of California, San Francisco8, Sun Yat-sen University9, University of Tennessee Health Science Center10, University of Minnesota11, Iowa State University12, Genetic Information Research Institute13, Salk Institute for Biological Studies14, Stanford University15, University of Liège16, University of Nebraska–Lincoln17, University of Cambridge18, Washington University in St. Louis19, University of Córdoba (Spain)20, Kyoto University21, Carnegie Institution for Science22, National Autonomous University of Mexico23, University of Münster24, École Normale Supérieure25, University of Melbourne26, University of Paris-Sud27, University of Mainz28, Scripps Research Institute29, Ohio State University30, University of Chicago31, University of Jena32, University of Arizona33, Louisiana State University34, University of New Brunswick35, University College London36, University of Potsdam37, Delaware Biotechnology Institute38, Boyce Thompson Institute for Plant Research39, Macquarie University40, Oklahoma State University Center for Health Sciences41, İzmir University of Economics42, Academy of Sciences of the Czech Republic43, Charles University in Prague44, St. Edward's University45, University of Puget Sound46, Hokkaido University47, Tsinghua University48, Washington State University49, Appalachian State University50, Marquette University51
12 Oct 2007-Science
TL;DR: Analyses of the Chlamydomonas genome advance the understanding of the ancestral eukaryotic cell, reveal previously unknown genes associated with photosynthetic and flagellar functions, and establish links between ciliopathy and the composition and function of flagella.
Abstract: Chlamydomonas reinhardtii is a unicellular green alga whose lineage diverged from land plants over 1 billion years ago. It is a model system for studying chloroplast-based photosynthesis, as well as the structure, assembly, and function of eukaryotic flagella (cilia), which were inherited from the common ancestor of plants and animals, but lost in land plants. We sequenced the approximately 120-megabase nuclear genome of Chlamydomonas and performed comparative phylogenomic analyses, identifying genes encoding uncharacterized proteins that are likely associated with the function and biogenesis of chloroplasts or eukaryotic flagella. Analyses of the Chlamydomonas genome advance our understanding of the ancestral eukaryotic cell, reveal previously unknown genes associated with photosynthetic and flagellar functions, and establish links between ciliopathy and the composition and function of flagella.

2,554 citations

Proceedings ArticleDOI
01 Jan 2018
TL;DR: A reliable dataset is produced that contains benign and seven common attack network flows, which meets real world criteria and is publicly avaliable and evaluates the performance of a comprehensive set of network traffic features and machine learning algorithms to indicate the best set of features for detecting the certain attack categories.
Abstract: With exponential growth in the size of computer networks and developed applications, the significant increasing of the potential damage that can be caused by launching attacks is becoming obvious. Meanwhile, Intrusion Detection Systems (IDSs) and Intrusion Prevention Systems (IPSs) are one of the most important defense tools against the sophisticated and ever-growing network attacks. Due to the lack of adequate dataset, anomaly-based approaches in intrusion detection systems are suffering from accurate deployment, analysis and evaluation. There exist a number of such datasets such as DARPA98, KDD99, ISC2012, and ADFA13 that have been used by the researchers to evaluate the performance of their proposed intrusion detection and intrusion prevention approaches. Based on our study over eleven available datasets since 1998, many such datasets are out of date and unreliable to use. Some of these datasets suffer from lack of traffic diversity and volumes, some of them do not cover the variety of attacks, while others anonymized packet information and payload which cannot reflect the current trends, or they lack feature set and metadata. This paper produces a reliable dataset that contains benign and seven common attack network flows, which meets real world criteria and is publicly avaliable. Consequently, the paper evaluates the performance of a comprehensive set of network traffic features and machine learning algorithms to indicate the best set of features for detecting the certain attack categories.

1,931 citations


Authors

Showing all 10596 results

NameH-indexPapersCitations
David Scott124156182554
Wei Lu111197361911
Richard J. Hobbs10859268141
Wei Zhang104291164923
Chris M. Wood10279543076
Mark S. Tremblay10054143843
James Taylor95116139945
Johan Richard9549925915
Chun Li9351741645
Bin Li92175542835
Robert J. Blanchard8324122316
Robie W. Macdonald7929223460
Serge Kaliaguine7646521443
Ravin Balakrishnan7218215970
Min Wang7271619197
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20241
202341
2022145
20211,008
20201,066
2019989