Digital Commons Network^™

An Optimized Feature Selection Method For Breast Cancer Diagnosis In Digital Mammogram Using Multiresolution Representation, Mohamed Meselhy Eltoukhy, Ibrahima Faye

Applied Mathematics & Information Sciences

This paper introduces a method for feature extraction from multiresolution representations (wavelet,curvelet) for classification of digital mammograms. The proposed method selects the features according to its capability to distinguish between different classes. The method starts with both performing wavelet and curvelet transform over mammogram images. The resulting coefficients of each image are used to construct a matrix. Each row in the matrix corresponds to an image.The most significant features, in terms of capabilities of differentiating classes,are selected. The method uses threshold values to select the columns that will maximize the difference between the different classes’representatives. The proposed method is applied …

A New Image Watermarking Scheme Using Multi- Objective Bees Algorithm, Jiann-Shu Lee, Jing-Wein Wang, Kung-Yo Giang

Applied Mathematics & Information Sciences

The optimization of watermarked image fidelity and watermark robustness is an attractive research topic in image watermarking. In this paper, we propose a new image watermarking scheme based on multi-objective bees algorithm to promote watermarking robustness as well as fidelity. In contrast with the existing genetic algorithms (GAs) based approaches utilizing single objective optimization, we treat the image watermarking as a multi-objective optimization problem. Based on this new perspective, the inherent conflict existing in image fidelity and watermark robustness for image watermarking can be objectively handled. The experimental study shows that our method indeed outperform the conventional GA-based approaches in …

Two Self-Dual Lattices Of Signed Integer Partitions, Giampiero Chiaselotti, William Keith, Paolo A. Oliverio

Applied Mathematics & Information Sciences

In this paper we study two self-dual lattices of signed integer partitions, D(m,n) and E(m,n), which can be considered also sub-lattices of the lattice L(m,2n), where L(m,n) is the lattice of all the usual integer partitions with at most m parts and maximum part not exceeding n. We also introduce the concepts of k-covering poset for the signed partitions and we show that D(m,n) is 1-covering and E(m,n) is 2-covering.We study D(m,n) and E(m,n) as two discrete dynamical models with some evolution rules. In particular, the 1-covering lattices are exactly the lattices definable with one outside addition rule and one …

The Research Of Multi-Point Function Opaque Predicates Obfuscation Algorithm, Yang Yubo, Fan Wenqing, Huang Wei, Xu Guoai, Yang Yixian

Applied Mathematics & Information Sciences

On the algorithm of code obfuscation, opaque predicate is used to confuse the judgment of the program branches to achieve complex control flow statement. Currently, there are problems of obfuscation on the opaque predicate. The first problem is the isolation. the relation between opaque predicate is relatively isolated, once an opaque predicates Boolean value is obtained, the branch flow will always be identified; Second is the reversible, an attacker can determine the opaque predicate the Boolean value by analyzing reversible slicing attacks. In this paper, we proposed multi-point function opaque predicate obfuscation algorithm, using multi-function features makes opaque predicates interdependent …

Cloud Model And Tolerance Granular Space-Based Image Retrieval Methods, Jiucheng Xu, Jinyu Ren, Lin Sun, Tianhe Xu

Applied Mathematics & Information Sciences

In the existing tolerance granular space models, grid points in each layer are established only taking space position into account, which ignore uncertainties of image texture, such as randomness, fuzziness and relevance. As a matter of fact, it is very important to extract grid points for constructing tolerance granular space, which are tolerance granules’ position or center. Therefore, it is very meaningful for the accurate texture feature-description of images to extract grid points well. To address this issue, we firstly apply cloud model to extracting grid points, and establish two new tolerance granular space models. Then, similarity measures based on …

An Exponential Entropy-Based Hybrid Ant Colony Algorithm For Vehicle Routing Optimization, Chengming Qi, Ping Li

Applied Mathematics & Information Sciences

Vehicle routing problem(VRP) is important combinatorial optimization problems which have received considerable attention in the last decades. The optimization of vehicle routing problem is a well-known research problem in the logistics distribution. In order to overcome the prematurity of Ant Colony Algorithm (ACA) for logistics distribution routing optimization, a hybrid algorithm combining improved ACA with Iterated Local Search (ILS) is proposed. The proposed algorithm adjusts the pheromone trail to balance the convergence rate and diversification of solutions self-adaptively. The exponential entropy is used to control the path selection and pheromone updating strategy. Combining with ILS is to avoid local best …

Attribute-Based Server-Aided Verification Signature, Zhiwei Wang, Ruirui Xie, Shaohui Wang

Applied Mathematics & Information Sciences

Attribute based signature (ABS) is a novel cryptographic primitive, which enables a party to sign messages for any predicate satisfied by their attributes. However, heavy computational cost is required during the verification procedure in most existing ABS schemes, which may need many pairing operations. Pairings are costly operation when compared to exponentiation in the base group. As a result, this presents a greatly challenge for resource-limited users, such as smart cards and wireless sensor. In other words, verification can hardly be done in these devices if attribute based signature is employed. We solve this problem by proposing a new notion …

Exploring Differences And Finding Connections In Archaeology And History Practice And Teaching In The Livingstone Museum And The University Of Zambia, 1973 To 2016, Francis B. Musonda

Zambia Social Science Journal

This article looks at the way archaeology and history have been practised and taught at the Livingstone Museum, Zambia and the University of Zambia in relation to each other as closely allied disciplines between 1973 and 2016. It identifies some of the areas in which they have either collaborated well, or need to do so, and those that set them apart in their common aim to study the past. The paper has identified a number of grey areas that have tended to be inimical to the advancement of the two institutions in their quest to advance the study of Zambia’s …

Place Events Fall 2014, Place

PLACE Historical Documents

This document describes PLACE events at Linfield College for fall 2014.

Sfa Weather Station-November 2014, Arthur Temple College Of Forestry And Agriculture, Stephen F. Austin State University

Weather Station Data

No abstract provided.

Scholarworks Statistics - November 2014, Scholarworks

ScholarWorks Reports

For the month of November 2014, ScholarWorks recorded a total of 30,878 full-text downloads and 13,404 page views.

Bitcoins, Block Chains, And Mining Pools, Singapore Management University

Perspectives@SMU

Bitcoins can help facilitate online commerce, but investors – and speculators – should understand how the cryptocurrency works

Research Digest Number 10: Parents And Teachers: Working Together To Foster Children’S Learning, Kate Perkins, Pat Knight, Marion Meiers

Research Digest

This edition of the Research Digest focuses primarily on parent-teacher collaboration, considering what research can tell us about:

• why parental engagement is important
• key features of effective collaborations
• critical challenges and issues that teachers and parents may face
• strategies that have helped teachers and parents build effective relationships

Some examples of activities undertaken as part of whole-school programs are also included. These illustrate the kind of scaffolding that helps teachers, parents and children establish the foundations for effective interactions.

The Digest draws on searches of data bases and bibliographic resources including the Australian Education Index, Education Resources Information Center (ERIC), …

Does The Worsening Galactic Cosmic Radiation Environment Observed By Crater Preclude Future Manned Deep Space Exploration?, Nathan A. Schwadron, J. B. Blake, Anthony Case, Colin J. Joyce, Justin Kasper, J. E. Mazur, N. Petro, M. Quinn, Jamie A. Porter, Charles W. Smith, Sonya S. Smith, Harlan E. Spence, Lawrence W. Townsend, R. Turner, Jody K. Wilson, Cary Zeitlin

Physics & Astronomy

Abstract

The Sun and its solar wind are currently exhibiting extremely low densities and magnetic field strengths, representing states that have never been observed during the space age. The highly abnormal solar activity between cycles 23 and 24 has caused the longest solar minimum in over 80 years and continues into the unusually small solar maximum of cycle 24. As a result of the remarkably weak solar activity, we have also observed the highest fluxes of galactic cosmic rays in the space age and relatively small solar energetic particle events. We use observations from the Cosmic Ray Telescope for the …

Excitation Of Nightside Magnetosonic Waves Observedby Van Allen Probes, Qinghua Zhou, Fuliang Xiao, Chang Yang, Si Liu, C A. Kletzing, W. S. Kurth, G. B. Hospodarsky, Harlan E. Spence, Geoffrey Reeves, H. O. Funsten, J. B. Blake, D. N. Baker, J. R. Wygant

Physics & Astronomy

Abstract

During the recovery phase of the geomagnetic storm on 30-31 March 2013, Van Allen Probe A detected enhanced magnetosonic (MS) waves in a broad range of L = 1.8-4.7 and magnetic local time (MLT) = 17-22 h, with a frequency range ∼10-100 Hz. In the meanwhile, distinct proton ring distributions with peaks at energies of ∼10 keV, were also observed in L = 3.2-4.6 and L = 5.0-5.6. Using a subtracted bi-Maxwellian distribution to model the observed proton ring distribution, we perform three-dimensional ray tracing to investigate the instability, propagation, and spatial distribution of MS waves. Numerical results show …

On Volume-Preserving Vector Fields And Finite-Type Invariants Of Knots, R. Komendarczyk, Ismar Volić

Faculty Research and Scholarship

We consider the general non-vanishing, divergence-free vector fields defined on a domain in 3-space and tangent to its boundary. Based on the theory of finite-type invariants, we define a family of invariants for such fields, in the style of Arnold’s asymptotic linking number. Our approach is based on the configuration space integrals due to Bott and Taubes.

X-Ray Emission From Magnetic Massive Stars, Y. Nazé, V. Petit, M. Rinbrand, David H. Cohen, S. Owocki, A. Ud-Doula, G. A. Wade

Physics & Astronomy Faculty Works

Magnetically confined winds of early-type stars are expected to be sources of bright and hard X-rays. To clarify the systematics of the observed X-ray properties, we have analyzed a large series of Chandra and XMM-Newton observations, corresponding to all available exposures of known massive magnetic stars (over 100 exposures covering ~60% of stars compiled in the catalog of Petit et al.). We show that the X-ray luminosity is strongly correlated with the stellar wind mass-loss rate, with a power-law form that is slightly steeper than linear for the majority of the less luminous, lower-${\dot{M}}$ B stars and flattens for the …

Discovery Of Thienoquinolone Derivatives As Selective And Atp Non-Competitive Cdk5/P25 Inhibitors By Structure-Based Virtual Screening, Arindam Chatterjee, Stephen J. Cutler, Robert J. Doerksen, Ikhlas A. Khan, John S. Williamson

Office for Research Publications and Presentations

Calpain mediated cleavage of CDK5 natural precursor p35 causes a stable complex formation of CDK5/p25, which leads to hyperphosphorylation of tau. Thus inhibition of this complex is a viable target for numerous acute and chronic neurodegenerative diseases involving tau protein, including Alzheimer’s disease. Since CDK5 has the highest sequence homology with its mitotic counterpart CDK2, our primary goal was to design selective CDK5/p25 inhibitors targeting neurodegeneration. A novel structure-based virtual screening protocol comprised of e-pharmacophore models and virtual screening workflow was used to identify nine compounds from a commercial database containing 2.84 million compounds. An ATP non-competitive and selective thieno[3,2- …

Retained-Components Factor Transformation: Factor Loadings And Factor Score Predictors In The Column Space Of Retained Components, André Beauducel, Frank Spohn

Journal of Modern Applied Statistical Methods

Factor loadings optimally account for the non-diagonal elements of the covariance matrix of observed variables. Principal component analysis leads to components accounting for a maximum of the variance of the observed variables. Retained-components factor transformation is proposed in order to combine the advantages of factor analysis and principal component analysis.

Pairwise Comparison In Repeated Measures, I.C.A. Oyeka, C. C. Nnanatu

Journal of Modern Applied Statistical Methods

Sometimes a random sample of subjects or patients may be exposed to a battery of diagnostic tests or medication over time and interest is on determining whether there is progressive remission of condition, disease or symptom. Also perhaps early in a program or experiment, subjects or candidates may be required to significantly improve in their performance rates at the current trial relative to an immediately preceding trial, otherwise they may have to withdraw from or drop out. The research interest would then be to determine some critical minimum marginal success rate to guide the management in decision making as well …

A Comparison Of Methods For Group Prediction With High Dimensional Data, Holmes Finch

Journal of Modern Applied Statistical Methods

High dimensional data is the situation in which the number of variables included in an analysis approaches or exceeds the sample size. In the context of group classification, researchers are typically interested in finding a model that can be used to correctly place an individual into their appropriate group; e.g. correctly diagnose individuals with depression. However, when the size of the training sample is small and the number of predictors used to differentiate the groups is larger, standard approaches such as discriminant analysis may not work well. In order to address this issue, statisticians have developed a number of tools …

Objective Priors For Estimation Of Extended Exponential Geometric Distribution, Pedro L. Ramos, Fernando A. Moala, Jorge A. Achcar

Journal of Modern Applied Statistical Methods

A Bayesian analysis was developed with different noninformative prior distributions such as Jeffreys, Maximal Data Information, and Reference. The aim was to investigate the effects of each prior distribution on the posterior estimates of the parameters of the extended exponential geometric distribution, based on simulated data and a real application.

Some General Guidelines For Choosing Missing Data Handling Methods In Educational Research, Jehanzeb R. Cheema

Journal of Modern Applied Statistical Methods

The effect of a number of factors, such as the choice of analytical method, the handling method for missing data, sample size, and proportion of missing data, were examined to evaluate the effect of missing data treatment on accuracy of estimation. A methodological approach involving simulated data was adopted. One outcome of the statistical analyses undertaken in this study is the formulation of easy-to-implement guidelines for educational researchers that allows one to choose one of the following factors when all others are given: sample size, proportion of missing data in the sample, method of analysis, and missing data handling method.

Bayesian Inference For Volatility Of Stock Prices, Juliet G. D'Cunha, K. A. Rao

Journal of Modern Applied Statistical Methods

Lognormal distribution is widely used in the analysis of failure time data and stock prices. Maximum likelihood and Bayes estimator of the coefficient of variation of lognormal distribution along with confidence/credible intervals are developed. The utility of Bayes procedure is illustrated by analyzing prices of selected stocks.

Local Bandwidths For Improving Performance Statistics Of Model-Robust Regression 2, Efosa Edionwe, Julian L. Mbegbu

Journal of Modern Applied Statistical Methods

Model-Robust Regression 2 (MRR2) method is a semi-parametric regression approach that combines parametric and nonparametric fits. The bandwidth controls the smoothness of the nonparametric portion. We present a methodology for deriving data-driven local bandwidth that enhances the performance of MRR2 method for fitting curves to data generated from designed experiments.

Contrast Of Bayesian And Classical Sample Size Determination, Farhana Sadia, Syed S. Hossain

Journal of Modern Applied Statistical Methods

Sample size determination is a prerequisite for statistical surveys. A comprehensive overview of the Bayesian approach for computation of the sample size, and a comparison with classical approaches, is presented. Two surveys are taken as example to illustrate the accuracy and efficiency of each approach, and to make recommendations about which method is preferred. The Bayesian approach of sample size determination may require fewer subjects if proper prior information is available.

The Information Criterion, Masume Ghahramani

Journal of Modern Applied Statistical Methods

The Akaike information criterion, AIC, is widely used for model selection. Using the AIC as the estimator of asymptotic unbias for the second term Kullbake-Leibler risk considers the divergence between the true model and offered models. However, it is an inconsistent estimator. A proposed approach the problem is the use of A'IC, a consistently offered information criterion. Model selection of classic and linear models are considered by a Monte Carlo simulation.

Gumbel-Weibull Distribution: Properties And Applications, Raid Al-Aqtash, Carl Lee, Felix Famoye

Journal of Modern Applied Statistical Methods

Some properties of the Gumbel-Weibull distribution including the mean deviations and modes are studied. A detailed discussion of regions of unimodality and bimodality is given. The method of maximum likelihood is proposed for estimating the distribution parameters and a simulation is conducted to study the performance of the method. Three tests are given for testing the significance of a distribution parameter. The applications of Gumbel-Weibull distribution are emphasized. Five data sets are used to illustrate the flexibility of the distribution in fitting unimodal and bimodal data sets.

Fitting Stereotype Logistic Regression Models For Ordinal Response Variables In Educational Research (Stata), Xing Liu

Journal of Modern Applied Statistical Methods

The stereotype logistic (SL) model is an alternative to the proportional odds (PO) model for ordinal response variables when the proportional odds assumption is violated. This model seems to be underutilized. One major reason is the constraint of current statistical software packages. Statistical Package for the Social Sciences (SPSS) cannot perform the SL regression analysis, and SAS does not have the procedure developed to directly estimate the model. The purpose of this article was to illustrate the stereotype logistic (SL) regression model, and apply it to estimate mathematics proficiency level of high school students using Stata. In addition, it compared …

Optimal Location Design For Prediction Of Spatial Correlated Environmental Functional Data, Mahdi Rasekhi, B. Jamshidi, F. Rivaz

Journal of Modern Applied Statistical Methods

The optimal choice of sites to make spatial prediction is critical for a better understanding of really spatio-temporal data. It is important to obtain the essential spatio-temporal variability of the process in determining optimal design, because these data tend to exhibit both spatial and temporal variability. Two new methods of prediction for spatially correlated functional data are considered. The first method models spatial dependency by fitting variogram to empirical variogram, similar to ordinary kriging (univariate approach). The second method models spatial dependency by linear model co-regionalization (multivariate approach). The variance of prediction method was chosen as the optimization design criterion. …