Light scattering, as well as light absorption in the water, often cause underwater images to be h... more Light scattering, as well as light absorption in the water, often cause underwater images to be hazy, poorly contrasted, and dominated by either green or blue colour cast. In this paper, we review some of the state-of-the-art approaches in which specifically designed to enhance the quality of the acquired images. These approaches are able to eliminate the color cast and haziness on the images as well as to improve the image colourfulness and contrast. The characteristics of each of the developed approaches are highlighted, and their performances are evaluated both subjectively and objectively by the quality assessment methods.
Time series of counts are observed widely in actuarial science, finance, epidemiology and biology... more Time series of counts are observed widely in actuarial science, finance, epidemiology and biology. These time series may exhibit over-, equi- and under-dispersion. The Poisson distribution is commonly used in count time series models, but it is restricted by the equality of mean and variance. Other distributions such as the generalized Poisson, double Poisson, hyper-Poisson, and COM-Poisson distributions have been proposed to replace the Poisson distribution to model the different levels of dispersion in time series of counts. These models have certain limitations such as complex expressions for the mean and variance which complicate the formulation as GARCH models. In this study, we propose an alternative hyper-Poisson (AHP) distribution, with simple forms of conditional mean and variance, for an integer-valued GARCH (INGARCH) model for time series of counts that also exhibit the different levels of dispersion. We demonstrate that the AHP-INGARCH model is comparable to some existin...
A new parameter is introduced to extend the geometric distribution using Azzalini's method. S... more A new parameter is introduced to extend the geometric distribution using Azzalini's method. Several important structural properties of the proposed two-parameter extended geometric distribution are investigated. Characterizations including for the geometric distribution, in terms of the proposed model, are established. Maximum likelihood estimation, method of moment estimation and relative frequency based estimation of the parameters are discussed in detail. The likelihood ratio test regarding relevance of the additional parameter is presented. Bayesian estimation of the parameters using STAN is also discussed. The proposed model is compared with some recently introduced two-parameter count models by analyzing two real-life datasets. The findings clearly indicate superiority of the proposed model over the rest.
Background: Alzheimer’s disease (AD) is a neurodegenerative disorder where patients suffer from m... more Background: Alzheimer’s disease (AD) is a neurodegenerative disorder where patients suffer from memory loss, cognitive impairment and progressive disability. Individual blood biomarkers have not been successful in defining the disease pathology, progression and diagnosis of AD. There is a need to identify multiplex panels of blood biomarkers for early diagnosis of AD with high sensitivity and specificity. This study focused on identification of cytokine biomarkers. The maximum likelihood estimates of the ordinary logistic regression model cannot be obtained when there is complete separation and the alternative is Firth logistic regression which uses a penalised Maximum Likelihood in parameter estimation. Methods: This paper reports a Firth logistic regression application in finding potential blood-based cytokine biomarkers for Alzheimer’s disease in a matched case control study. We used a principle component analysis to discriminate the correlated, completely separated covariates. ...
The number of non-payments is an indicator of delinquent behaviour in credit scoring, hence its e... more The number of non-payments is an indicator of delinquent behaviour in credit scoring, hence its estimation and prediction are of interest. The modelling of the number of non-payments, as count data, can be examined as a renewal process. In a renewal process, the number of events (such as non-payments) which has occurred up to a fixed time t is intimately connected with the inter-arrival times between the events. In the context of non-payments, the inter-arrival times correspond to the time between two subsequent non-payments. The probability mass function and the renewal function of the count distribution are often complicated, with terms involving factorial and gamma functions, and thus their computation may encounter numerical difficulties. In this paper, with the motivation of modelling the number of non-payments through a renewal process, a general method for computing the probabilities and the renewal function based on numerical Laplace transform inversion is discussed. This me...
Communications in Statistics - Simulation and Computation
The convolution of two binomial random variables has appeared in various settings such as a model... more The convolution of two binomial random variables has appeared in various settings such as a model in machine maintenance and as a Markov chain model. This article presents a bivariate distribution with this convolution of binomials as marginal distributions. This bivariate distribution arises from sampling with partial classification, and this has potentially useful applications in diverse areas. The distribution generalizes the bivariate binomial distribution and its variants. Some properties of the bivariate distribution have been obtained. A mixture formulation of the distribution has been derived which facilitates computation of probabilities and computer sampling. An application to a real data set is presented to illustrate its usefulness in empirical modeling.
In commerce, economics, engineering and the sciences, quantitative methods based on statistical m... more In commerce, economics, engineering and the sciences, quantitative methods based on statistical models for forecasting are very useful tools for prediction and decision. There is an abundance of papers on forecasting for continuous-time series but relatively fewer papers for time series of counts which require special consideration due to the integer nature of the data. A popular method for modelling is the method of mixtures which is known for its flexibility and thus improved prediction capability. This paper studies the coherent forecasting for a flexible stationary mixture of Pegram and thinning (MPT) process, and develops the likelihood-based asymptotic distribution. Score functions and the Fisher information matrix are presented. Numerical studies are used to assess the performance of the forecasting methods. Also, a comparison is made with existing discrete-valued time series models. Finally, the practical application is illustrated with two sets of real data. It is shown tha...
Logistic regression is often used for the classification of a binary categorical dependent variab... more Logistic regression is often used for the classification of a binary categorical dependent variable using various types of covariates (continuous or categorical). Imbalanced data will lead to biased parameter estimates and classification performance of the logistic regression model. Imbalanced data occurs when the number of cases in one category of the binary dependent variable is very much smaller than the other category. This simulation study investigates the effect of imbalanced data measured by imbalanced ratio on the parameter estimate of the binary logistic regression with a categorical covariate. Datasets were simulated with controlled different percentages of imbalance ratio (IR), from 1% to 50%, and for various sample sizes. The simulated datasets were then modeled using binary logistic regression. The bias in the estimates was measured using MSE (Mean Square Error). The simulation results provided evidence that the effect of imbalance ratio on the parameter estimate of the...
The Private Higher Education Paradoxes: Reality or Myth?
International Journal of Asian Social Science, 2014
Higher educational landscape in Malaysia experienced drastic changes as a result of liberalisatio... more Higher educational landscape in Malaysia experienced drastic changes as a result of liberalisation measures undertaken by the governments. Private Higher Educational Institutions (PHEI) are normally not directly funded by the government. Not surprisingly, PHEI are driven by financial motives to ensure continued business success. Moreover, higher education is a highly contested field. In recent years, stakeholders such as parents, businesses, government regulators and accreditation bodies are beginning to exert influence on PHEI in areas like programme development and delivery. It has always been the aim of PHEI to satisfy powerful stakeholders. However, this is not an easy task as their expectations can be contradictory. This development has created strategy tensions for PHEI to juggle. This paper argues that higher education issues have to be treated as paradoxes where there is no real solution. It goes on to argue that higher education paradoxes are the manifestation of stakeholder influence. The paper first highlights the interplay of stakeholders? expectations which has been a catalyst for the creation of paradoxes followed by the discussion of the six paradoxes.
African Journal of Business Management, Jul 31, 2011
This paper attempts to confirm the adequacy of the strategic management model using the structura... more This paper attempts to confirm the adequacy of the strategic management model using the structural equation modeling (SEM) method. The model adopted the resource-based view (RBV) approach to identify competitive strength. The RBV method states that organizations with the right resources coupled with the appropriate management skills and capabilities will develop competitive strength and organizational performance. Results generated by AMOS graphics v. 18, an SEM statistical software, confirm the adequacy of the model for companies engaged in the industrial products sector. Financial strength was found to be a better predictor of competitive advantage than management strength. The results also confirm that competitive advantage has a positive impact on the profitability and performance of organizations.
A new distribution on (0, 1), generalized Log-Lindley distribution, is proposed by extending the ... more A new distribution on (0, 1), generalized Log-Lindley distribution, is proposed by extending the Log-Lindley distribution. This new distribution is shown to be a weighted Log-Lindley distribution. Important probabilistic and statistical properties have been derived. An interesting characterization of the weighted distribution in terms of Kullback-Liebler distance and weighted entropy has also been obtained. A useful result in insurance for the distorted premium principal is presented and verified with numerical calculations. New regression models for bounded responses based on this distribution and their application is illustrated by considering modeling a real life data on risk management and another data set on outpatient health expenditure in comparison with beta regression and Log-Lindley regression models. Much better fits for both data sets justify the relevance of the new distribution in statistical modeling and analysis. Furthermore this generalization, apart from adding flexibility for modelling, retains the compactness and tractability of statistical quantities required for statistical analysis, which is a feature of the Log-Lindley distribution. Thus, the generalized Log-Lindley distribution should be a useful addition to statistical models for practitioners.
Mixed Poisson distributions are a class of distributions arising from the Poisson mean fluctuatin... more Mixed Poisson distributions are a class of distributions arising from the Poisson mean fluctuating as a random variable. Mixed Poisson distributions have been applied in diverse disciplines for modelling non-homogeneity in populations. This paper brings together recent work on this class of distributions with focus on specific models, computation and simulation, applications to stochastic and data modelling.
Communications in Statistics - Theory and Methods, 2017
This paper proposes a generalized binomial distribution with four parameters, which is derived fr... more This paper proposes a generalized binomial distribution with four parameters, which is derived from the finite capacity queueing system with state-dependent service and arrival rates. This distribution is also generated from the conditional Conway-Maxwell-Poisson distribution given a sum of two Conway-Maxwell-Poisson variables. In this paper, we consider the properties about the probability mass function, index of dispersion, skewness and kurtosis and give applications of the proposed distribution from its geneses. The estimation method and simulation study are also considered.
Cryptanalysis of various images based on neural networks with leakage and time varying delays
International Journal of Nonlinear Sciences and Numerical Simulation
The main objective of this paper is to provide an efficient image encryption for each and every s... more The main objective of this paper is to provide an efficient image encryption for each and every single person in order to secure their own records while saving them in social networks. We have formulated the delayed fuzzy cellular neural networks (FCNNs) with suitable keys that are the values of the parameters of FCNNs and obtain the irregular dynamical signal (solution) which encrypts the images. We have utilized entirely 42 parameters as a key sensitivity in the order of 10−15 among them three elements of initial condition parameters are sensitive to the order of 10−14. Lastly, comparison results are provided with the existing literature. The measurements show that the proposed algorithm is a novel overall solution for image encryption.
Mathematical Modelling and Prediction Tools for the COVID-19 Pandemic: A Review (Preprint)
UNSTRUCTURED The latest threat to global health is the ongoing outbreak of the Coronavirus Diseas... more UNSTRUCTURED The latest threat to global health is the ongoing outbreak of the Coronavirus Disease 2019 (COVID-19). There are three main areas of modeling research, namely epidemiology, drug repurposing and vaccine design. The most important purpose of the models is to inform institutional and nationwide efforts to ensure patient safety. This study aimed to review COVID-19 modelling and prediction tools. Understanding these methods streamlines the strengths and limitations of each method. We researched the traditional model and the more current models that flourish during the pandemic. This understanding is the key to the proper use of specific models to achieve certain goals. Modeling approaches for COVID-19 can be very broadly categorized into phenomenological models and mechanistic models. Phenomenological approaches treat the modeling problem purely from an empirical perspective. From our survey, there are three major types of approaches under the phenomenological models: time-s...
Analysis of tumor cells in the absence and presence of chemotherapeutic treatment: The case of Caputo-Fabrizio time fractional derivative
Mathematics and Computers in Simulation, 2021
Abstract In this work, a study of the mathematical model of uncontrolled growth of tumor cells in... more Abstract In this work, a study of the mathematical model of uncontrolled growth of tumor cells in the presence of chemotherapy is proposed. The fractional form of the model with the non-singular exponential kernel is considered. This model consists of four coupled partial differential equations (PDEs) which depict the relationship among the normal, tumor, immune cells, and the chemotherapy parameter. The purpose is to investigate the behavior of all types of cells with a change in the fractional order parameter and to show the effect of chemotherapeutic treatment on tumor cells with different levels of immune system. Before applying the proposed numerical method, an approximate expression for the fractional-order Caputo-Fabrizio (C-F) derivative of polynomial function x k is derived. A shifted Chebyshev operational matrix of fractional order derivative is deduced by using an approximation of the C-F fractional derivative of the function and some properties of the orthogonal polynomials. The system of four coupled fractional order PDEs is studied by using the operational matrix method. The dynamics of all the aforementioned cells with respect to different fractional order derivatives are derived and computed numerically for the prescribed values of parameters. These are depicted through graphs to study the diffusive nature of cells and the effect of chemotherapy on all types of cells, before and after applying the therapy. This study shows that tumor cell growth decreases with time when chemotherapy treatment is started. The concentration of tumor cells is more in the invasive fronts of the tumor site as compared to the center of the tumor. It is concluded that the growth of tumor cells is less due to chemotherapy treatment for a person with a strong immune system.
Journal of Computational and Applied Mathematics, 2019
This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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