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                <text>Understanding water quality dynamics in aquaculture ponds in Sunyani, Ghana: Insights from Partial Least Squares (PLS)-Path Modeling</text>
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                <text>Oreochromis niloticus, and African catfish Clarias gariepinus, were selected for the study. Eleven fish ponds with stock ranging between 7-21 days were randomly selected and sampled at monthly intervals for five months, with the aim of capturing water quality patterns through a full production cycle. Seventeen parameters were measured and analyzed using Partial Least Squares (PLS)-Path Modeling. Most ponds had unusually shallow depths, characterized by excessive stocking densities of 200% on average above recommended rates. This necessitates high feeding rates, thereby reducing the assimilative capacity of ponds. The effect of feeding intensity on water quality increased with stock age. Persistent algal blooms, low DO, high temperatures and elevated levels of ammonia, nitrite, phosphate, TDS and conductivity were indicative of generally poor water quality. The model showed that 82% variability in water quality was due to production inputs. Standard stocking rates, feeding rates and construction of deeper ponds are recommended.</text>
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                <text>Iddrisu Wahab Abdul, Nokoe Kaku Sagary, Akoto Isaac</text>
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                <text>Wahab A Iddrisu, Inusah Iddrisu, Abdul-Karim Iddrisu</text>
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                <text>In this study, we extend Codeço’s classical SI‐B epidemic and endemic model from a deterministic framework into a stochastic framework. Then, we formulated it as a stochastic differential equation for the number of infectious individuals I(t) under the role of the aquatic environment. We also proved that this stochastic differential equation (SDE) exists and is unique. The reproduction number, R0, was derived for the deterministic model, and qualitative features such as the positivity and invariant region of the solution, the two equilibrium points (disease‐free and endemic equilibrium), and stabilities were studied to ensure the biological meaningfulness of the model. Numerical simulations were also carried out for the stochastic differential equation (SDE) model by utilizing the Euler‐Maruyama numerical method. The method was used to simulate the sample path of the SI‐B stochastic differential equation for the …</text>
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                <text>Hindawi</text>
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                <text>Success factors of pre-construction stages of Ghanaian public road construction project life cycle</text>
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                <text>Chelteau Barajei, Emmanuel Appiah-Kubi, Nongiba A Kheni, Peter PK Yalley, Wahab Iddrisu</text>
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                <text>The research article aims to determine the critical success factors (CSFs) of the pre-construction stages of the public road construction project life cycle in Ghana. Data on 26 CSFs and 16 success criteria were collected from key stakeholders across Ghana through a questionnaire survey. The data was then analyzed using structural equation modelling (SEM). The study showed that external environmental factors and project management factors directly influence success across the pre-construction phases of the Ghanaian public road construction project life cycle whereas procurement-related factors only influence the success of the works procurement phase. The research outcome would inspire construction industry stakeholders to be dynamic and pay utmost attention to the application of the CSFs identified across the pre-construction phases of the Ghanaian public road construction project life cycle. This is the …</text>
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                <text>Modeling and Forecasting of Ghana’s Inflation Volatility</text>
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                <text>In this paper, we assessed volatility of Ghana’s inflation rates for 2000 to 2018 using the auto-regressive conditionally heteroskedasticity (ARCH), generalized ARCH (GARCH), and the exponential GARCH (EGARCH) models. The inflation data were obtained from the Ghana Statistical Service (GSS). The proposed model should be able to provide projections of inflation volatility from 2019 and beyond. The results showed that higher order models are required to properly explain Ghana’s inflation volatility and the EGARCH(12, 1) is the best fitting model for the data. The EGARCH(12, 1) model is robust to model and forecast volatility of inflation rates. Also, the results suggest that we are forecasting increasing volatility and there is increasing trend in general prices of goods and services for 2018 and beyond. The forecasts figures revealed that Ghana’s economy is likely to be unstable in 2018 and 2019. This study therefore recommends that policy makers and industry players need to put in place stringent monetary and fiscal policies that would put the anticipated increase in inflation under control. The models were implemented using R software.</text>
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                <text>Chelteau Barajei, Nongiba A Kheni, Emmanuel Appiah-Kubi, Humphrey Danso, Abdul Wahab Iddrisu</text>
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                <text>The objective of this research paper is to determine the critical success factors (CSFs) influencing the success of public road construction projects from the perspective of a developing nation. A self-administered questionnaire was used to gather data on the extent to which critical success factors gathered from literature impact the success of public road construction projects from sector practitioners’ perspectives in Ghana. The data was then analysed using factor analysis. The study revealed that external environmental factors have the highest influence (46.23%) on public road construction project success, followed by project management factors (12.25%) while procurement-related factors have the least impact (6.97%). Public construction project management organisations and the government will now have a deeper understanding of CSFs that influence the success of public construction projects and use them as …</text>
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                <text>Discriminant analysis of demand-side roadblocks to financial inclusion in Northern Ghana</text>
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                <text>Issahaku Yakubu, Romanus Dinye, Daniel Buor, Wahab A Iddrisu</text>
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                <text>Northern Ghana has been described as the most poverty-stricken spot in Ghana. Given the link between financial inclusion and poverty reduction, this paper aims at estimating a discriminant function model to analyse demand-side roadblocks to financial inclusion in Northern Ghana. The study is mainly based on primary data elicited through survey questionnaires. Even though the minimum sample size was determined to be 385 households, a total of 400 households were selected systematically, out of which 395 households returned their questionnaires for analysis. The estimated discriminant function model was found to be significant at the 1% level of significance. It was also found that, the demand-side roadblocks that are very crucial to financial inclusion in Northern Ghana (in order of importance) are “Culture”, “Cost”, “Capability”, and “Trust”. Overall, 77.2% of the cases were correctly classified by the estimated model. This paper therefore concludes that most vulnerable groups in Northern Ghana still find it difficult to access formal financial services due to barriers such as culture, cost, capability and trust. Government policies should therefore be directed at addressing these barriers so as to enhance financial inclusion in the area which eventually will lead to poverty reduction.</text>
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                  <text>Faculty of Computing and Information Systems</text>
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                <text>Background&#13;
Global fight against tuberculosis (TB) has received increasing attention over the years. However, the disease remains one of the top-most global health problems, especially in Sub-Saharan Africa and Ghana.&#13;
Aims&#13;
This paper examined geographical (regional) and seasonal distribution of TB cases providing relative risk of TB exposure in Ghana and step by step procedure to perform the analysis.&#13;
Methods and material&#13;
We modelled reported TB cases between 2015 and 2018 using wavelet analysis and applied maximum covariance analysis (MCA) to determine regional and seasonal patterns and the risk of TB exposure in Ghana. This study is based on the old administrative regions of Ghana.</text>
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                <text>Comparing bayesian and maximum likelihood methods in structural equation modelling of university student satisfaction: an empirical analysis</text>
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                <text>Killian Asampana Asosega, Wahab Abdul Iddrisu, Kassim Tawiah, Alex Akwasi Opoku, Eric Okyere</text>
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                <text>Students’ satisfaction in the university environment is essential to both the student (customer) and management of the university. Satisfied students are determined to succeed in their academics, and this sustains their loyalty and trust, which results in an improved image and esteem of the university. This study examined the level of students’ satisfaction with campus facilities and infrastructure, campus social life, student support services, and the quality of academics in the University of Energy and Natural Resources (UENR) in Ghana and further investigated how students’ satisfaction with the above four areas of the university environment affect each other. A questionnaire was administered to continuous students in UENR, and the collected data were analysed using structural equation modelling within the maximum likelihood and Bayesian frameworks whose results and performance were compared. Results …</text>
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                <text>Determining and forecasting financial inclusion in Northern Ghana using discriminant analysis</text>
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                <text>Issahaku Yakubu, Romanus Dinye, Daniel Buor, Wahab A Iddrisu</text>
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            <description>An account of the resource</description>
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                <text>Poverty and income inequality remain a serious challenge in Northern Ghana. Given the causal link between financial inclusion and poverty reduction, this paper aims at estimating a discriminant function model to analyze the determinants of financial inclusion in Northern Ghana. The study is mainly based on primary data elicited through survey questionnaires. Even though the minimum sample size was determined to be 385 households, a total of 400 households were selected systematically, out of which 395 households returned their questionnaires for analysis. The estimated discriminant function model was found to be significant at the 1% level of significance. It was also found that, the most significant determinants of financial inclusion in Northern Ghana (in order of importance) are “Age”,“Cost”,“Capability”,“Literacy”,“Distance”, and “Employment”. Overall, 72.4% of the cases were correctly classified by the estimated model. This paper therefore concludes that there is the need for Government and donors to make coordinated efforts towards addressing these determinants so as to broaden financial inclusion, thereby contributing to poverty reduction and lower income inequalities in the area.</text>
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