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Item Comparison of Least Squares Method and Bayesian with Multivariate Normal Prior in Estimating Multiple Regression Parameters(2016-02-17) Mettle, F.O.; Iddi, S.Based on an assumption of multivariate normal priors for parameters of multivariate regression model, this study outlines an algorithm for application of traditional Bayesian method to estimate regression parameters. From a given set of data, a Jackknife sample of least squares regression coefficient estimates are obtained and used to derive estimates of the mean vector and covariance matrix of the assumed multivariate normal prior distribution of the regression parameters. Driven to determine whether Bayesian methods to multivariate regression parameter estimation present a stable and consistent improvement over classical regression modeling or not, the study results indicate that the Bayesian method and Least Squares Method (LSM) produced almost the same estimates for the regression parameters and coefficient of determination with the Bayesian method having smaller standard errors.Item Modified zero-inflated negative binomial model with application to clinical trial in epileptic patients(2016-03-10) Iddi, S.Marginalized models are in great demand by many researchers in the life sciences, particularly in clinical trials studies, epidemiology, health-economics, surveys and many others, since they allow generalization of inference to the entire population under study. For count data, standard procedures such as the Poisson regression and negative binomial model provide population average inference for model parameters. However, occurrence of excess zero counts and lack of independence in empirical data have necessitated their extension to accommodate these phenomena. These extensions, though useful, complicate interpretations of fixed effects. For example, the zero-inflated Poisson model accounts for the presence of excess zeros, but the parameter estimates do not have a direct marginal inferential ability as the base model, the Poisson model. Marginalizations due to the presence of excess zeros are underdeveloped though demand for them is interestingly high. The aim of this talk, therefore, is to present a developed marginalized model for zero-inflated univariate count outcome in the presence of overdispersion. Emphasis is placed on methodological development, efficient estimation of model parameters, and application to a clinical trial dataset. Results of simulation study performed to assess the performance of the model are also discussed.Item Exact Matrix Completion via Convex Optimization(2016-03-10) Lotsi, A.; Doku-Amponsah, K.We consider a problem of considerable practical interest: the recovery of a data matrix from a sampling of its entries. Suppose that we observe m entries selected uniformly at random from a matrix M. Can we complete the matrix and recover the entries that we have not seen? We show that one can perfectly recover most low-rank matrices from what appears to be an incomplete set of entries. We prove that if the number m of sampled entries obeys for some positive numerical constant C, then with very high probability, most n*n matrices of rank r can be perfectly recovered by solving a simple convex optimization problem. This program finds the matrix with minimum nuclear norm that fits the data. The condition above assumes that the rank is not too large. However, if one replaces the 1.2 exponent with 1.25, then the result holds for all values of the rank. Our results are connected with the recent literature on compressed sensing, and show that objects other than signals and images can be perfectly reconstructed from very limited information.Item Coloured Random Graphs, Simple Random Allocation of Coloured Balls into Coloured Bins(2016-03-17) Doku-Amponsah, K.Simple coloured random allocation model is obtained when coloured balls are sequentially inserted at random into coloured bins. The empirical occupancy measure of the simple coloured random allocation model counts the number of bins of a given colour with a given number of balls of each colour. In this paper we show that, given the colours, both the empirical occupancy measure of simple coloured random allocation models and the empirical neighbourhood distribution of sparse coloured random graph models converge weakly to the product of independent Poisson distributions.Item On statistics of extremes under random censoring(2016-04-07) Minkah, R.; Asiedu, L.In the field of statistics of extremes, the most common assumption is to consider that samples are independent and identically distributed or weakly dependent and stationary from a distribution function F. However, in most real life applications such as survival analysis and reliability data, observations are usually censored. For such data sets, the classical estimators in statistics of extremes need some modification to take into account censoring. Compared to the classical statistics of extremes, the case of censoring is fairly new and in its early stages of development. In this presentation, we propose some estimators of the Extreme Value Index and extreme quantiles when data is randomly censored. We compare the proposed estimators with an exhaustive list of estimators in the literature in a large simulation study. The results show that our estimators are more robust to censoring. In addition, the estimators provide better confidence intervals when there is heavy censoring and more intermediate observations are included in the estimation.Item New Insights on Woodfuel Reliance and Human Welfare(2016-06-27) Jagger, P.; Codjoe, S.N.A.Over 3 billion people globally rely on woodfuels (fuelwood and charcoal) to meet basic energy needs for cooking and heating. Reliance on woodfuels and the emissions associated with burning them has major implications for climate, sustainable forest use, health and human well-being. We use data from approximately 7,000 households throughout the low income tropics collected by the Poverty Environment Network at the Center for International Forestry Research to provide new insights into the role of woodfuels in rural livelihoods and factors that influence their supply and demand.Item Bayesian and Multilevel Approaches to Modelling Road Traffic Fatalities in Ghana(2016-07-04) Hesse, C.A.; Iddi, S.The knowledge of accident rates in a country provides a useful tool for a comprehensive analysis of their causes as well as for their prevention. Prof. R. J. Smeed, in 1949, gave a regression model for estimating road traffic fatalities. The study gives a modified form of Smeed’s regression formula for estimating road traffic fatalities in Ghana. The modified regression model was found to be relatively more accurate form for estimating road traffic fatalities in Ghana, than Smeed’s formula. Bayesian model for predicting the annual regional distribution of the number of road traffic fatalities in Ghana is derived, using road traffic accident statistics data from the National Road Safety Commission, Ghana Statistical Service and Driver and Vehicle Licensing Authority. The data span 1991 to 2009. Since the parameters are assumed to vary across the various regions, they are considered to be random variables with probability distributions. The Markov chain Mont Carlo (MCMC) sampling techniques were used to draw samples from each of the posterior distribution, thereby determining the values of the unknown parameters for each region based on a given data. The study has shown that population and number of registered vehicles are predominant factors affecting road traffic fatalities in Ghana. The effect of other additional factors on road traffic fatality such as human (the driver, passenger and pedestrian), vehicle (its condition and maintenance), environmental/weather and nature of the road cannot be ruled out. Similar to the Bayesian model, where the regression parameters are considered as random variables, a Multilevel Random Coefficient (MRC) model for predicting road traffic fatalities in Ghana was also developed. In this model, the number of road traffic fatalities and the regional groups are conceptualized as a hierarchical system of road traffic fatalities and geographical regions of Ghana, with fatalities and regions defined at separate levels of this hierarchical system. Instead of estimating a separate regression equation for each of the 10 regions in Ghana, a multilevel regression analysis was applied to estimate the values of the regression coefficients for each region based on data given.Item Validation of Malaria Predictive Model with Missing Covariates(2016-09-29) Duah, D.This study develops a statistical methodology for validating a predictive clinical malaria model when data has missing values in predictor variables. Using the logistic regression framework, multiple imputation techniques for missing values and a penalized likelihood approach to avoid overfitting of the data were adopted. Models with different functional forms were built using known predictors (age, sickle cell, blood group, parasite density, and mosquito bed net use) and some malaria antibody specific antigens and FCGR3B polymorphism. Models were assessed through visualization and differences between the Area Under the Receiver Operating Characteristic Curve (AUROC) and Brier Score (BS) estimated by suitable internal cross-validation designs. The contributions of this research are in three folds: (i) addresses the statistical question on how to build and validate a risk prediction model in the presence of missing explanatory variables (ii) improves the general statistical approach for malaria epidemiology (iii) identifies potential malaria antibodies and FCGR3B polymorphism which should be the research focus in the search for potential malaria vaccine candidateItem On the Estimation of Conditional Tail Index and Extreme Quantiles under Random Censoring(2016-09-29) Minkah, R.In the area of Statistics of Extremes, the main assumption on any set of univariate data is to regard them as a complete sample of independent and identically distributed observations from an unknown distribution function, F. However, in many real life applications such as survival analysis, observations are usually subject to random censoring and may be influenced by an underlying covariate information. In such case, the classical extreme value theory needs some adjustment to take into account the presence of censoring and covariates. In this presentation, we propose estimators of the conditional tail index and conditional extreme quantiles for heavy-tailed distributions in the presence of random censoring and covariate information. We compare the proposed estimators with the existing estimators in the literature in a large scale simulation study. The results show improvement in bias and median absolute deviation over the existing estimators of the conditional tail index and conditional extreme quantiles.Item Combatting IUU Fishing in Ghana(2016-11-02) Wiafe, G.Globally, Illegal, Unregulated and Unreported (IUU) fishing has created large declines in commercially important fish populations and is thus recognized as a major threat, with the potential to cause an irreversible change in marine ecosystems. It has been estimated that IUU fishing accounts for about 20% of world catches, representing a global loss of between US$10 billion and US$23.5 billion annually. In West Africa alone, IUU fishing costs the region $7.15b, equivalent of 2.9m tons of illegally harvested fish. Such losses are detrimental to socio-economic development of the region, where over 3 million people, directly or indirectly are employed by the fisheries sector; per capita consumption of fish as animal protein exceeds global average; and up to 30% of GDP in some countries comes from fishery export revenues. The difficulty in combatting IUU fishing stems from inadequate human and infrastructural capacity to enforce fishery regulation, problem of internal conflict and political strife, and priorities other than fishery management requiring governmental attention. It goes without saying that dependence on foreign aid to balance national budget has also encouraged legal fishing fleets to overfish the resource in the region. Furthermore, inability to police the extent of the EEZ makes it possible for large factory ships from industrialized countries, stationed within the high seas, to carry out indiscriminate poaching. Notwithstanding these challenges, the ECOWAS Commission and its two Sub-Regional Fisheries Bodies, have put in place some measures to address IUU fishing in the region. The interventions include harmonization of fisheries legislation, setting up of national fishing registers, deployment of vessel monitoring systems (VMS), and cross-border patrols. The use of Earth Observation (EO) data coupled with technological advancement is playing a key role in maritime sensing in many developed countries. Hence, the ECOWAS Commission has set up a Regional Marine Centre in the University of Ghana as part of the Monitoring for Environment and Security in Africa initiative. The focus is to utilize EO data and innovative technologies for environment and resource management. This presentation will showcase how the Centre is helping to fight IUU fishing among others. Fourteen countries, from Mauritania to Sao Tome e Principe, receive daily intelligence on activities of all manner of vessels within their exclusive economic zones. Through a collaboration with exactEarth of Canada, a pilot programme to monitor inshore vessels in Ghana has resulted in deployment of transponders on all inshore fishing vessels in Ghana by the Ministry of Fisheries and Aquaculture Development. The results from the one-year pilot will be presented in the context of fighting IUU fishing.Item Combatting IUU Fishing in West Africa(2016-11-02) Wiafe, G.Globally, Illegal, Unregulated and Unreported (IUU) fishing has created large declines in commercially important fish populations and is thus recognized as a major threat, with the potential to cause an irreversible change in marine ecosystems. It has been estimated that IUU fishing accounts for about 20% of world catches, representing a global loss of between US$10 billion and US$23.5 billion annually. In West Africa alone, IUU fishing costs the region $7.15b, equivalent of 2.9m tons of illegally harvested fish. Such losses are detrimental to socio-economic development of the region, where over 3 million people, directly or indirectly are employed by the fisheries sector; per capita consumption of fish as animal protein exceeds global average; and up to 30% of GDP in some countries comes from fishery export revenues. The difficulty in combatting IUU fishing stems from inadequate human and infrastructural capacity to enforce fishery regulation, problem of internal conflict and political strife, and priorities other than fishery management requiring governmental attention. It goes without saying that dependence on foreign aid to balance national budget has also encouraged legal fishing fleets to overfish the resource in the region. Furthermore, inability to police the extent of the EEZ makes it possible for large factory ships from industrialized countries, stationed within the high seas, to carry out indiscriminate poaching. Notwithstanding these challenges, the ECOWAS Commission and its two Sub-Regional Fisheries Bodies, have put in place some measures to address IUU fishing in the region. The interventions include harmonization of fisheries legislation, setting up of national fishing registers, deployment of vessel monitoring systems (VMS), and cross-border patrols. The use of Earth Observation (EO) data coupled with technological advancement is playing a key role in maritime sensing in many developed countries. Hence, the ECOWAS Commission has set up a Regional Marine Centre in the University of Ghana as part of the Monitoring for Environment and Security in Africa initiative. The focus is to utilize EO data and innovative technologies for environment and resource management. This presentation will showcase how the Centre is helping to fight IUU fishing among others. Fourteen countries, from Mauritania to Sao Tome e Principe, receive daily intelligence on activities of all manner of vessels within their exclusive economic zones. Through a collaboration with exactEarth of Canada, a pilot programme to monitor inshore vessels in Ghana has resulted in deployment of transponders on all inshore fishing vessels in Ghana by the Ministry of Fisheries and Aquaculture Development. The results from the one-year pilot will be presented in the context of fighting IUU fishing.Item Implementation of Fourier Transform in Image Processing(2017-02-09) Ansah-Narh, T.For a realistic radio interferometer for flat-sky approximation, the basic observation is a set of complex visibilities, which is defined in 2D Fourier Transform (FT) as Radio Measurement Interferometer Measurement Equation (RIME). The Discrete Fourier Transform (DFT) is a specific form of Fourier analysis that is widely employed in signal processing and related fields to analyze frequencies contained in a sample signal to solve partial differential equations and to perform other operations such as convolutions. The presentation will focus on the implementation of the algorithm of Fast Fourier Transform (FFT) by converting a 2D image to the frequency domain and back to the image domain (Inverse FFT). The technique will then be related to RIME.Item “Maximum Penalized Likelihood Approach for Current Status Data with Informative Censoring Based on Frailties”(2017-02-09) Faisal, A.; Mettle, F.O.Current status data arise in many fields including epidemiological surveys and animal carcinogenicity experiments. By current status data we mean each subject in a study is observed only once at a certain time to ascertain whether or not the event of interest has occurred. This means that for current status data, the event (failure) time is not exactly observed but only known to be smaller or greater than the observation (censoring) time. The standard assumption in survival data analysis is that the observation time is non-informative, that is, the observation time is unrelated to the failure time. However, this assumption may not be valid in some circumstances, especially if the subject is lost-to-follow-up before the study ends. The examination time for such a subject can potentially be linked to the failure time and hence the examination time will be said to be informatively censored. To avoid severely misleading inferences that can result from failing to account for informative censoring, shared frailty models have been proposed in literature to account for informative censoring with current status data. The most commonly used estimation procedure is the Expectation-Maximization (EM) algorithm, but this approach yield discrete estimation of the distribution and possibly a negative hazard estimate. Thus the EM algorithm might not only be able to provide an accurate trend of how the baseline hazard estimates are changing over time, but also affect the accuracy of the estimated parameters. The goal of this thesis therefore, is to develop Maximum Penalized Likelihood (MPL) methods for current status data with informative censoring based on gamma-shared frailty assumption. We intend to show how the MPL procedure can be employed to simultaneously estimate the regression parameters and the smooth baseline continuous hazard functions for Proportional Hazards Model, Semiparametric transformation Model and Clustered data under the proportional hazards model. The variances and the asymptotic properties of these MPL estimators will be studied. Simulations studies will also be conducted to ascertain the performance of our proposed MPL methods. Comparisons will also be made with some of the existing EM methods. For illustrative purposes, we will apply our methods to the data set on rodent tumorigenicity experiment example provided by National Toxicology Program (1998)Item Thermochemical Conversion of Biomass for Fuels & Chemicals at the USDA(2017-04-05) Boateng, A.A.; Onwona-Agyeman, B.Lignocellulosic biomass is the most abundant renewable carbon resource available for the production of biofuels and bio-based chemicals. To harness this biogenic carbon biochemical or thermochemical conversion technologies are employed. Thermochemical methods for the conversion of biomass comprise i) pyrolysis, the heating in the absence of air, ii) gasification, heating under partial oxygen conditions, and iii) combustion, the heating in excess oxygen environment. Among these, pyrolysis is the only route that has the full potential to provide small design footprint that is adaptable to the farm/forest setting and with the capability to handle a wide array of agricultural residues. Done properly, thermochemical liquefaction pathways, such as pyrolysis, offer a unique potential to directly produce hydrocarbon fuel intermediates i.e., refinery fuel blendstocks that can potentially enter existing petroleum refinery flow streams without added expenses of creating a whole new refinery infrastructure. The talk will provide an overview of on-farm pyrolysis biorefining research at the USDA highlighting various scales of bio-oil production, defunctionalization of the organic oxygenates contained in the bio-oil to drop-in fuels and separation/extraction of valuable chemical coproducts with the added benefit of enhancing the economic viability of a pyrolysis based bio-refineryItem Quaternary Ostracoda as Palaeoenvironmental Proxies(2017-09-27) Frenzel, P.Ostracoda are minute crustaceans with a calcified, two-valved carapace. They are a classical group of micropalaeontology because of their long and rich record in earth history going back to Ordovician times. The presentation introduces into morphology, ecology and distribution of this group and demonstrates methods of its use in palaeoenvironmental analysis. Examples of application in coastal geology, palaeoclimatology, environmental micropalaeontology and geoarchaeology are givenItem The Problem of Environmental Estrogens from the Wastewater Perspective(2017-12-14) Novak, P.Environmental estrogens are discharged from wastewater treatment plants and can cause physiological, developmental, and behavioral changes in fish and other aquatic organisms. Sources of environmental estrogens vary, with some sources under appreciated. In addition, the fate of these compounds in treatment plants and the environment is complicated, with degradation rates varying widely and degradation products sometimes causing physiological effects as well. Given this, how should we approach the management of these compounds? Do we impose regulations on the discharge of environmental estrogens, and if so, how? Finally, how do we pay for the treatment required to protect ecosystems?Item A Watershed-wide Investigation of the Biological Effects of Contaminants of Emerging Concern: A Case Study in the North American Great Lakes(2017-12-14) Schoenfuss, H.L.Dr. Schoenfuss will explore the effects of Contaminants of Emerging Concern (CECs) on resident fish species in the North American Great Lakes watershed. CECs include common pharmaceuticals, household products and industrial and agricultural chemicals known to cause harm to aquatic life. We analyzed nearly 500 surface water samples at 54 sites in tributaries of the Great Lakes Watershed to confirm the ubiquitous presence of CECs. A subsequent cluster analyses of commonly detected CECs in this data matrix suggests that the co-occurrence of approximately half of the CECs can be attributed to dichotomous urban or agricultural upstream land use. Almost 3,000 resident and caged sunfish (Lepomis ssp.) were collected from 27 of the 54 sampling sites and analyzed for indicators of stress associated with CEC exposure. Canonical correspondence analyses revealed that concurrent with indicators of toxic stress, biomarkers of reproductive potential declined. To further examine the population level consequences, fathead minnows (Pimephales promelas) were exposed in the laboratory for three generations to the empirically derived urban CEC mixture at three environmentally relevant concentrations. Taken together, this integrated series of studies provides a case study on how to develop a comprehensive assessment of the presence and biological effects of CECs across a continental watershed. Dr. Schoenfuss will close the seminar by providing a brief introduction to the research activities, facilities and educational programs found in the Department of Biological Sciences at St. Cloud State University.Item What is killing them? The use of some selected Ghanaian plants used to control Coelaenomenodera lamensisBerti and Mariau (Coleoptera; Chrysomelidae) in Ghana.(2019-03-18) Buxton, T.The oil palm leaf miner, Coelaenomenodera lamensis Berti and Mariau (Coleoptera; Chrysomelidae) is the most important pest of oil palm endemic to West Africa. The use of synthetic insecticides has been employed in controlling the pest, although it poses a major threat to the environment and human health. Recently the use of natural products from plants as insecticides has been practiced widely in agricultural production. In a study for a more environmentally safe insecticide, we found that the parts of some Ghanaian plants are effective in controlling this pest. The methanol extracts of Zanthoxylum zanthoxyloides (Roots) and Cashew Nut Shell Liquid (CNSL) were screened against the leaf miner to determine their insecticidal activity against the pest. Bioassay guided isolation led to the isolation of (2E, 4E)-N-(2- methylpropyl)deca-2,4-dienamide (pellitorine) from the roots of Z. zanthoxyloides whiles three major cardanol derivatives, (Z)-3-(8- pentadecenyl)phenol, (8Z,11Z)-3-(8,11- pentadecadienyl)phenol and (8Z,11Z)-3-(8,11,14-pentadecatrienyl)phenol (2-3) were isolated from CNSL. Currently, these botanicals are being applied under field conditions to determine their efficacy as well.Item Climate Change Issues: where we have come from and where we are going(2020-02-18) Klutse, N.A.B.The earth is warming at a steady pace and is having a devastating impact on the earth’s climate. Climate change is mostly natural. However, clear evidence exists that the rate of the occurrence of the changes we are experiencing in the climate and the intensity of the impacts are closely related to human activity. We understand the reason for this is the increase in human-caused greenhouse gases causing more warming of the earth's climate. How much have humans contributed to the greenhouse gases and what is the contribution of humans to climate change is still a global discussion. The presentation will focus on what climate change is, where we have come from and where we are going with the level of human influence. A debate on whether climate change mitigation is a moral or political issue will also be opened.Item Intellectual Property Right and Scientific Research in Ghana(University of Ghana, 2020-03-03) Abaidoo, C.Science research and Innovation are key to national development especially in an era of expanding global market and the growth of knowledge based resources. In Africa, one of the underlying setbacks for our development is the slow pace of innovation and technology development. However, exploitation of the Intellectual Property Right (IPR) system presents one of the greatest opportunities for scientists and researchers to create wealth for themselves and contribute to the innovation eco-system. This paper, therefore, seeks to expose the participants to IPR creation and management with emphasis on patenting and utility models