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Relevant bibliographies by topics / Class skew

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Academic literature on the topic 'Class skew'

Author: Grafiati

Published: 4 June 2021

Last updated: 17 February 2022

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Journal articles on the topic "Class skew"

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Ma, Yanyuan, and Marc G. Genton. "Flexible Class of Skew-Symmetric Distributions." Scandinavian Journal of Statistics 31, no. 3 (September 2004): 459–68. http://dx.doi.org/10.1111/j.1467-9469.2004.03_007.x.

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Ma, Jianmin, and Kaishun Wang. "Four-class skew-symmetric association schemes." Journal of Combinatorial Theory, Series A 118, no. 4 (May 2011): 1381–91. http://dx.doi.org/10.1016/j.jcta.2010.12.002.

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Sidorenko, Vladimir, Wenhui Li, Onur Günlü, and Gerhard Kramer. "Skew Convolutional Codes." Entropy 22, no. 12 (December 2, 2020): 1364. http://dx.doi.org/10.3390/e22121364.

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A new class of convolutional codes, called skew convolutional codes, that extends the class of classical fixed convolutional codes, is proposed. Skew convolutional codes can be represented as periodic time-varying convolutional codes but have a description as compact as fixed convolutional codes. Designs of generator and parity check matrices, encoders, and code trellises for skew convolutional codes and their duals are shown. For memoryless channels, one can apply Viterbi or BCJR decoding algorithms, or a dualized BCJR algorithm, to decode skew convolutional codes.

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Mirzadeh, Saeed, and Anis Iranmanesh. "A new class of skew-logistic distribution." Mathematical Sciences 13, no. 4 (October 5, 2019): 375–85. http://dx.doi.org/10.1007/s40096-019-00306-8.

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Abstract In this study, the researchers introduce a new class of the logistic distribution which can be used to model the unimodal data with some skewness present. The new generalization is carried out using the basic idea of Nadarajah (Statistics 48(4):872–895, 2014), called truncated-exponential skew-logistic (TESL) distribution. The TESL distribution is a member of the exponential family; therefore, the skewness parameter can be derived easier. Meanwhile, some important statistical characteristics are presented; the real data set and simulation studies are applied to evaluate the results. Also, the TESL distribution is compared to at least five other skew-logistic distributions.

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Dinh, Hai Q., Bac T. Nguyen, and Songsak Sriboonchitta. "A Note on Skew Cyclic Codes over a Class of Rings." Algebra Colloquium 27, no. 04 (November 5, 2020): 703–12. http://dx.doi.org/10.1142/s1005386720000589.

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We study skew cyclic codes over a class of rings [Formula: see text], where each [Formula: see text] [Formula: see text] is a finite field. We prove that a skew cyclic code of arbitrary length over R is equivalent to either a usual cyclic code or a quasi-cyclic code over R. Moreover, we discuss possible extension of our results in the more general setting of [Formula: see text]-dual skew constacyclic codes over R, where δR is an automorphism of R.

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Li, Chun Guang, and Ting Ting Zhou. "Skew symmetry of a class of operators." Banach Journal of Mathematical Analysis 8, no. 1 (2014): 279–94. http://dx.doi.org/10.15352/bjma/1381782100.

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Behboodian, J., A. Jamalizadeh, and N. Balakrishnan. "A new class of skew-Cauchy distributions." Statistics & Probability Letters 76, no. 14 (August 2006): 1488–93. http://dx.doi.org/10.1016/j.spl.2006.03.008.

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Arellano-Valle, Reinaldo B., Héctor W. Gómez, and Fernando A. Quintana. "A New Class of Skew-Normal Distributions." Communications in Statistics - Theory and Methods 33, no. 7 (December 31, 2004): 1465–80. http://dx.doi.org/10.1081/sta-120037254.

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Gupta, Arjun K., and John T. Chen. "A class of multivariate skew-normal models." Annals of the Institute of Statistical Mathematics 56, no. 2 (June 2004): 305–15. http://dx.doi.org/10.1007/bf02530547.

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Chen, Xuedong, Qianying Zeng, and Qiankun Song. "Likelihood Inference of Nonlinear Models Based on a Class of Flexible Skewed Distributions." Abstract and Applied Analysis 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/542985.

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This paper deals with the issue of the likelihood inference for nonlinear models with a flexible skew-t-normal (FSTN) distribution, which is proposed within a general framework of flexible skew-symmetric (FSS) distributions by combining with skew-t-normal (STN) distribution. In comparison with the common skewed distributions such as skew normal (SN), and skew-t (ST) as well as scale mixtures of skew normal (SMSN), the FSTN distribution can accommodate more flexibility and robustness in the presence of skewed, heavy-tailed, especially multimodal outcomes. However, for this distribution, a usual approach of maximum likelihood estimates based on EM algorithm becomes unavailable and an alternative way is to return to the original Newton-Raphson type method. In order to improve the estimation as well as the way for confidence estimation and hypothesis test for the parameters of interest, a modified Newton-Raphson iterative algorithm is presented in this paper, based on profile likelihood for nonlinear regression models with FSTN distribution, and, then, the confidence interval and hypothesis test are also developed. Furthermore, a real example and simulation are conducted to demonstrate the usefulness and the superiority of our approach.

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Dissertations / Theses on the topic "Class skew"

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Akdemir, Deniz. "A Class of Multivariate Skew Distributions: Properties and Inferential Issues." Bowling Green, Ohio : Bowling Green State University, 2009. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=bgsu1237574643.

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Basalamah, Doaa. "Statistical Inference for a New Class of Skew t Distribution and Its Related Properties." Bowling Green State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1496762068499547.

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Smith, Michael Reed. "An Empirical Study of Instance Hardness." BYU ScholarsArchive, 2009. https://scholarsarchive.byu.edu/etd/2012.

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Most widely accepted measures of performance for learning algorithms, such as accuracy and area under the ROC curve, provide information about behavior at the data set level. They say nothing about which instances are misclassified, whether two learning algorithms with the same classification accuracy on a data set misclassify the same instances, or whether there are instances misclassified by all learning algorithms. These questions about behavior at the instance level motivate our empirical analysis of instance hardness, a measure of expected classification accuracy for an instance. We analyze the classification of 57 data sets using 9 learning algorithms. Of the over 175000 instances investigated, 5% are misclassified by all 9 of the considered learning algorithms, and 15% are misclassified by at least half. We find that the major cause of misclassification for hard instances is class overlap, manifested as outliers and border points which can be exacerbated by class skew. We analyze these causes and show to what extent each leads to misclassifications, both in isolation and jointly. 19.8% of all misclassified instances are outliers; 71.3% are border points; 21% belong to a minority class. We also find that 91.6% of all outliers and 38.3% of all border points are misclassified whereas only 3.5% of instances without class overlap are misclassified. We propose a set of heuristics to predict when an instance will be hard to correctly classify. Additionally, we analyze how different learning algorithms perform on tasks with varying degrees of outliers, border points and class skew.

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Frühwirth-Schnatter, Sylvia, and Gertraud Malsiner-Walli. "From here to infinity: sparse finite versus Dirichlet process mixtures in model-based clustering." Springer Berlin Heidelberg, 2019. http://dx.doi.org/10.1007/s11634-018-0329-y.

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In model-based clustering mixture models are used to group data points into clusters. A useful concept introduced for Gaussian mixtures by Malsiner Walli et al. (Stat Comput 26:303-324, 2016) are sparse finite mixtures, where the prior distribution on the weight distribution of a mixture with K components is chosen in such a way that a priori the number of clusters in the data is random and is allowed to be smaller than K with high probability. The number of clusters is then inferred a posteriori from the data. The present paper makes the following contributions in the context of sparse finite mixture modelling. First, it is illustrated that the concept of sparse finite mixture is very generic and easily extended to cluster various types of non-Gaussian data, in particular discrete data and continuous multivariate data arising from non-Gaussian clusters. Second, sparse finite mixtures are compared to Dirichlet process mixtures with respect to their ability to identify the number of clusters. For both model classes, a random hyper prior is considered for the parameters determining the weight distribution. By suitable matching of these priors, it is shown that the choice of this hyper prior is far more influential on the cluster solution than whether a sparse finite mixture or a Dirichlet process mixture is taken into consideration.

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Medina, Garay Aldo William. "Modelos não lineares sob a classe de distribuições misturas da escala skew-normal." [s.n.], 2010. http://repositorio.unicamp.br/jspui/handle/REPOSIP/306690.

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Orientadores: Victor Hugo Lachos Dávila, Filidor Edilfonso Vilca Labra
Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica
Made available in DSpace on 2018-08-16T04:06:26Z (GMT). No. of bitstreams: 1 MedinaGaray_AldoWilliam_M.pdf: 1389516 bytes, checksum: 2763869ea52e11ede3c860714ea0e75e (MD5) Previous issue date: 2010
Resumo: Neste trabalho estudamos alguns aspectos de estimação e diagnóstico de influência global e local de modelos não lineares sob a classe de distribuição misturas da escala skew-normal, baseado na metodologia proposta por Cook (1986) e Poon & Poon (1999). Os modelos não lineares heteroscedásticos também são discutidos. Esta nova classe de modelos constitui uma generalização robusta dos modelos de regressão não linear simétricos, que têm como membros particulares distribuições com caudas pesadas, tais como skew-t, skew-slash, skew-normal contaminada, entre outras. A estimação dos parâmetros será obtida via o algoritmo EM proposto por Dempster et al. (1977). Estudos de testes de hipóteses são considerados utilizando as estatísticas de escore e da razão de verossimilhança, para testar a homogeneidade do parâmetro de escala. Propriedades das estatísticas do teste são investigadas através de simulações de Monte Carlo. Exemplos numéricos considerando dados reais e simulados são apresentados para ilustrar a metodologia desenvolvida
Abstrac: In this work, we studied some aspects of estimation and diagnostics on the global and local influence in nonlinear models under the class of scale mixtures of the skewnormal (SMSN) distribution, based on the methodology proposed by Cook (1986) e Poon & Poon (1999). Heteroscedastic nonlinear models are also discussed. This new class of models are a robust generalization of non-linear regression symmetrical models, which have as members individual distributions with heavy tails, such as skew-t, skew-slash, and skew-contaminated normal, among others. The parameter estimation will be obtained with the EM algorithm proposed by Dempster et al. (1977). Studies testing hypotheses are considered using the score statistics and the likelihood ratio test to test the homogeneity of scale parameter. Properties of test statistics are investigated through Monte Carlo simulations. Numerical examples considering real and simulated data are presented to illustrate the methodology
Mestrado
Métodos Estatísticos
Mestre em Estatística

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Massuia, Monique Bettio 1989. "Modelos para dados censurados sob a classe de distribuições misturas de escala skew-normal." [s.n.], 2015. http://repositorio.unicamp.br/jspui/handle/REPOSIP/306680.

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Orientador: Víctor Hugo Lachos Dávila
Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática Estatística e Computação Científica
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Resumo: Este trabalho tem como objetivo principal apresentar os modelos de regressão lineares com respostas censuradas sob a classe de distribuições de mistura de escala skew-normal (SMSN), visando generalizar o clássico modelo Tobit ao oferecer alternativas mais robustas à distribuição Normal. Um estudo de inferência clássico é desenvolvido para os modelos em questão sob dois casos especiais desta família de distribuições, a Normal e a t de Student, utilizando o algoritmo EM para obter as estimativas de máxima verossimilhança dos parâmetros dos modelos e desenvolvendo métodos de diagnóstico de influência global e local com base na metodologia proposta por Cook (1986) e Poom & Poon (1999). Sob o enfoque Bayesiano, o modelo de regressão para respostas censuradas é estudado sob alguns casos especiais da classe SMSN, como a Normal, a t de Student, a skew-Normal, a skew-t e a skew-Slash. Neste caso, o amostrador de Gibbs é a principal ferramenta utilizada para a inferência sobre os parâmetros do modelo. Apresentamos também alguns estudos de simulação para avaliar a metodologia desenvolvida que, por fim, é aplicada em dois conjuntos de dados reais. Os pacotes SMNCensReg, CensRegMod e BayesCR para o software R dão suporte computacional aos desenvolvimentos deste trabalho
Abstract: This work aims to present the linear regression model with censored response variable under the class of scale mixture of skew-normal distributions (SMSN), generalizing the well known Tobit model as providing a more robust alternative to the normal distribution. A study based on classic inference is developed to investigate these censored models under two special cases of this family of distributions, Normal and t-Student, using the EM algorithm for obtaining maximum likelihood estimates and developing methods of diagnostic based on global and local influence as suggested by Cook (1986) and Poom & Poon (1999). Under a Bayesian approach, the censored regression model was studied under some special cases of SMSN class, such as Normal, t-Student, skew-Normal, skew-t and skew-Slash. In these cases, the Gibbs sampler was the main tool used to make inference about the model parameters. We also present some simulation studies for evaluating the developed methodologies that, finally, are applied on two real data sets. The packages SMNCensReg, CensRegMod and BayesCR implemented for the software R give computational support to this work
Mestrado
Estatistica
Mestra em Estatística

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Falon, Roger Jesus Tovar. "Modelos de regressão lineares mistos sob a classe de distribuições normal-potência." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-15032018-132547/.

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Neste trabalho são apresentadas algumas extensões dos modelos potência-alfa assumindo o contexto em que as observações estão censuradas ou limitadas. Inicialmente propomos um novo modelo assimétrico que estende os modelos t-assimétrico (Azzalini e Capitanio, 2003) e t-potência (Zhao e Kim, 2016) e inclui a distribuição t de Student como caso particular. Este novo modelo é capaz de ajustar dados com alto grau de assimetria e curtose, ainda maior do que os modelos t-assimétrico e t-potência. Em seguida estendemos o modelo t-potência às situações em que os dados apresentam censura, com alto grau de assimetria e caudas pesadas. Este modelo generaliza o modelo de regressão linear t de Student para dados censurados por Arellano-Valle et al. (2012). O trabalho também introduz o modelo linear misto normal-potência para dados assimétricos. Aqui a inferência estatística é realizada desde uma perspectiva clássica usando o método de máxima verossimilhança junto com o método de integração numérica de Gauss-Hermite para aproximar as integrais envolvidas na função de verossimilhança. Mais tarde, o modelo linear com interceptos aleatórios para dados duplamente censurados é estudado. Este modelo é desenvolvido sob a suposição de que os erros e os efeitos aleatórios seguem distribuições normal-potência e normal- assimétrica. Para todos os modelos estudados foram realizados estudos de simulação a fim de estudar as suas bondades de ajuste e limitações. Finalmente, ilustram-se todos os métodos propostos com dados reais.
In this work some extensions of the alpha-power models are presented, assuming the context in which the observations are censored or limited. Initially we propose a new asymmetric model that extends the skew-t (Azzalini e Capitanio, 2003) and power-t (Zhao e Kim, 2016) models and includes the Students t-distribution as a particular case. This new model is able to adjust data with a high degree of asymmetry and cursose, even higher than the skew-t and power-t models. Then we extend the power-t model to situations in which the data present censorship, with a high degree of asymmetry and heavy tails. This model generalizes the Students t linear censored regression model t by Arellano-Valle et al. (2012) The work also introduces the power-normal linear mixed model for asymmetric data. Here statistical inference is performed from a classical perspective using the maximum likelihood method together with the Gauss-Hermite numerical integration method to approximate the integrals involved in the likelihood function. Later, the linear model with random intercepts for doubly censored data is studied. This model is developed under the assumption that errors and random effects follow power-normal and skew-normal distributions. For all the models studied, simulation studies were carried out to study their benefits and limitations. Finally, all proposed methods with real data are illustrated.

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Book chapters on the topic "Class skew"

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Percannella, Gennaro, Paolo Soda, and Mario Vento. "Mitotic HEp-2 Cells Recognition under Class Skew." In Image Analysis and Processing – ICIAP 2011, 353–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24088-1_37.

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Sadeghkhani, Abdolnasser, and Syed Ejaz Ahmed. "Bayesian Predictive Densities as an Interpretation of a Class of Skew–Student t Distributions with Application to Medical Data." In Advances in Intelligent Systems and Computing, 416–28. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21248-3_31.

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Prati, Ronaldo C., Gustavo E. A. P. A. Batista, and Maria Carolina Monard. "Learning with Class Skews and Small Disjuncts." In Advances in Artificial Intelligence – SBIA 2004, 296–306. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-28645-5_30.

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Conference papers on the topic "Class skew"

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Stager, M., P. Lukowicz, and G. Troster. "Dealing with Class Skew in Context Recognition." In 26th IEEE International Conference on Distributed Computing Systems Workshops (ICDCSW'06). IEEE, 2006. http://dx.doi.org/10.1109/icdcsw.2006.36.

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Bergamin, Luzi. "Doubly skew: A new class of non-birefringent media." In 2010 URSI International Symposium on Electromagnetic Theory (EMTS 2010). IEEE, 2010. http://dx.doi.org/10.1109/ursi-emts.2010.5637095.

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Shieh, W. B., L. W. Tsai, S. Azarm, and A. L. Tits. "A New Class of Six-Bar Mechanisms With Symmetrical Coupler Curves." In ASME 1996 Design Engineering Technical Conferences and Computers in Engineering Conference. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/96-detc/dac-1491.

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Abstract A new class of six-bar mechanisms with symmetrical coupler-point curves is presented. This class of mechanisms is made up of a four-bar linkage with an additional dyad to form an embedded regular or skew pantograph. Because the coupler curve generated at an output point is amplified from that of a four-bar, a compact mechanism with a relatively large coupler curve can be obtained. In addition, due to their structure arrangement, the analysis and synthesis of such mechanisms can be easily achieved. It is shown that the admissible range of transmission angle for such mechanisms is smaller than that of a four-bar mechanism. It is also shown that mechanisms with an embedded skew pantograph exhibit better design flexibility than those with an embedded regular pantograph. Finally, an example mechanism from this class is illustrated and compared with a four-bar linkage with the same coupler curve.

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Sicilia, Rosa, Ermanno Cordelli, and Paolo Soda. "On Using Meta-Features to Learn Under Class Skew in Biomedical Domains." In 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS). IEEE, 2020. http://dx.doi.org/10.1109/cbms49503.2020.00054.

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Ouwayed, N., A. Belaïd, and F. Auger. "Cohen's class distributions for skew angle estimation in noisy ancient Arabic documents." In The Third Workshop. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1568296.1568305.

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Gupta, Tanmay, and Manoj Kumar. "Structural Response of Skew-Curved Concrete Box-Girder Bridges under Eccentric Vehicular Loading." In IABSE Conference, Kuala Lumpur 2018: Engineering the Developing World. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2018. http://dx.doi.org/10.2749/kualalumpur.2018.1021.

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<p>Concrete box-girders are widely used for modern highway bridges and large urban interchanges. Bridges with ends skewed or horizontally curved girders are becoming more popular now-a-days to incorporate heavy traffic within a very limited space available. Certain geographical situation even demand skew supports in addition to the curved layout of the bridge and results in complex skew-curve geometry of the deck. All the more complexity of such cases increases under eccentric traffic load due to which additional torsion and warping is induced in the bridge. Present study focuses on predicting the bending moment and deflection response of a single cell box-girder bridge for each unique skew/curve/skew-curve combination via 3D finite element analysis using CsiBridge. For the curved and skew-curved bridges the central curvature angle has been varied from 0° to 48° at an interval of 12° while for the skewed and skew-curved bridges the skew angle is swept from 0° to 50° at an interval of 10° in order to investigate the effect of curvature, skewness and skew-curve on flexural and deflection response of box-girder bridge. For these unique simply supported concrete box girder bridges, bending moment and vertical deflection of bridge girder for dead load as well as for IRC Class 70R Tracked wheel load cases are monitored via large parametric study. Results indicate that with increasing skew angle, magnitude of girder deflection and bending moment in general decreases for outer web and inner web. While for heavily curved bridges outer girder response becomes severe, combining the effect of skewness and curvature, it is observed that for highly curved bridges it is better to have skewed abutment to significantly reduce the overall deflection and bending moment response.</p>

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Lin, Hong-Chin, Tsung-Chieh Lin, and KwangHae H. Yae. "The Skew-Symmetric Property of the Newton-Euler Formulation for Constrained Multibody Systems." In ASME 1996 Design Engineering Technical Conferences and Computers in Engineering Conference. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/96-detc/dac-1476.

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Abstract This paper proposes a special form of the recursive Newton-Euler formulation that satisfies the skew-symmetric property, which is a necessary condition to ensure global convergence in a class of regressor-based identification and adaptive control (Slotine, 1987a & 1987b; Craig, 1987). For general multibody systems, such a special form has been developed in a reduced Euler-Lagrange formulation, but not in the Newton-Euler formulation, which has been very popular in the computational analysis of large scale systems. The paper successfully constructs a pair of inertia and Coriolis-centrifugal matrices for a “skew-symmetric” recursive Newton-Euler formulation, which can be used in both dynamics simulations and control applications.

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Bernard, J. M. L. "Properties of the solution and reciprocity theorem for a class of wedge problem at skew incidence." In International Symposium on Antennas and Propagation Society, Merging Technologies for the 90's. IEEE, 1990. http://dx.doi.org/10.1109/aps.1990.115300.

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Akash, Pritom Saha, Md Eusha Kadir, Amin Ahsan Ali, and Mohammad Shoyaib. "Inter-node Hellinger Distance based Decision Tree." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/272.

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This paper introduces a new splitting criterion called Inter-node Hellinger Distance (iHD) and a weighted version of it (iHDw) for constructing decision trees. iHD measures the distance between the parent and each of the child nodes in a split using Hellinger distance. We prove that this ensures the mutual exclusiveness between the child nodes. The weight term in iHDw is concerned with the purity of individual child node considering the class imbalance problem. The combination of the distance and weight term in iHDw thus favors a partition where child nodes are purer and mutually exclusive, and skew insensitive. We perform an experiment over twenty balanced and twenty imbalanced datasets. The results show that decision trees based on iHD win against six other state-of-the-art methods on at least 14 balanced and 10 imbalanced datasets. We also observe that adding the weight to iHD improves the performance of decision trees on imbalanced datasets. Moreover, according to the result of the Friedman test, this improvement is statistically significant compared to other methods.

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Savander, Brant R., Malcolm E. Willis, Karl A. Stambaugh, and Kelley A. Cox. "USCG Patrol Craft Hydrodynamic Fuel Efficiency Improvements." In SNAME 13th International Conference on Fast Sea Transportation. SNAME, 2015. http://dx.doi.org/10.5957/fast-2015-035.

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A computational analysis program, conducted at full scale, has been completed on the USCG Fast Response Cutter (FRC) to evaluate how appendage and propeller redesign affects calm water powering performance and erosive cavitation onset. Aft working forward, the geometric variations considered included: addition of a stern flap, wake adapted rudder redesign, propeller design refinement, wake adapted skeg redesign, and redesign of the spray rail system. The first activity was to use a wake alignment procedure to redesign the current rudder in an effort to improve the rudder drag characteristics and minimize or eliminate rudder cavitation. The wake aligned redesign eliminated rudder cavitation over the entire speed range, and decreased total drag by 6% at flank speed. Replacement of only the current rudders with the wake aligned redesign is predicted to increase flank speed from 28.9 knots to 29.4 knots. The stern flap and spray rail efforts followed the historical guidance of similar work performed on the USCG Island Class patrol boats, as documented in Cusanelli and Barry (2002). Following the geometric guidance of the Island Class stern flaps the final recommended stern flap for the FRC results in a brake power demand reduction of 15%. The Island Class achieved a 12% reduction in required brake power at similar speeds. The combination of the new stern flap, wake adapted rudders, current propeller, current skegs, and new spray rail yielded an increase in flank speed from 28.9 to 31.4 knots. Skeg redesign resulted in a 30% decrease in the magnitude of the radiated pressure pulse amplitudes experienced in the propeller tunnel above the propeller. The redesign of the skeg did not affect the propeller behind efficiency. Modification of the current propeller geometry was the final redesign task. The final system, which included the new stern flap, wake aligned rudders, redesigned propeller, wake aligned skegs, and new spray rail system decreased power by 18.6% at the prior 28.9 knot flank speed of FRC. The new flank speed, with the final system, has increased to 32.9 knots in the full load, end of service life condition. The combined effect of all redesign activities reveals an annual fuel consumption savings of 24,000 gallons per vessel per year, which corresponds to a 13.6% savings when compared to the original as-built system. Assuming a fuel cost of $4 per gallon, the annual cost savings per vessel per year equals $96,000. This savings extrapolated over a 58 ship fleet equates to $5.5 million in savings per year for the class. This saving per year yields a savings of $110 million for the 20-year operating life of the 58-ship class.

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