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                <text>Research Article 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 showed that students’ satisfaction levels with available campus facilities, campus social life, and student support services were low but were fairly satisfied with the quality of academics. Both maximum likelihood and Bayesian techniques showed positive significant effects of students’ satisfaction with campus facilities and infrastructure on satisfaction with campus social life, students’ support services, and academics. Moreover, students’ satisfaction with social life was positively associated with their satisfaction with academics and student support services. Although both estimation methods obtained similar estimates and inferences, the Bayesian SEM outperformed the ML-SEM based on the recommended fit indices. Findings of the study …</text>
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                <text>The Road to a Greener Future: How Government Expenditure and Effectiveness Drive Renewal Energy Consumption</text>
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                <text>This study examines the impact of government expenditure and government effectiveness on renewable energy consumption in Africa from 1990 to 2021. Utilizing the fixed effects technique, the findings indicate a positive significant relationship between government expenditure and renewable energy consumption, while government effectiveness demonstrates a significant negative influence. Additionally, trade openness and urbanization exhibit a negative impact on renewable energy usage. The effect of foreign direct investment (FDI) on renewable energy consumption is found to be mixed. To facilitate the transition towards a greener energy future in Africa, the study recommends several measures including increasing government expenditure on renewable energy, enhancing government effectiveness, promoting sustainable trade practices, and prioritizing sustainable urban planning.</text>
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                <text>Research Article Modeling Cholera Epidemiology Using Stochastic Differential Equations</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 SIB stochastic differential equation for the number of infectious individuals I (t), and the findings showed that the sample path or trajectory of the stochastic differential equation for the number of infectious individuals I (t) is continuous but not differentiable and that the SI-B stochastic differential equation model for the number of infectious individuals I (t) fluctuates inside the solution of the SI-B ordinary differential equation model. Another significant feature of our proposed SDE model is its simplicity.</text>
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                <text>Content-Based Spam Classification of Academic E-mails: A Machine Learning Approach</text>
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                <text>Wahab Abdul Iddrisu, Sylvester Kwasi Adjei-Gyabaa, Isaac Akoto</text>
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                <text>In the academic environment, players have overstretched University faculty with less available time. The task of reading and deleting electronic mail (e-mail) spam tends to consume or steal the little available time they have at their disposal. Due to the spam issue, automated processes or methods for separating spam from valid emails are becoming important. Due to the unstructured nature of the material, additional features, and a vast number of documents, the process of automatically classifying spam email presents significant difficulties. Increasing usage of the e-mail spam directly affects the performance of these spam classifications with regards to the quality and speed based on the challenges stated above. Most of the recent algorithms consider only relevant features or characteristics for the classification of the e-mails as spam or legitimate. The main objective of this work was to use a machine-learning …</text>
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                <text>Springer Nature Singapore</text>
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                <text>Enhancing the success of Ghanaian public road construction projects</text>
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                <text>Humphery Danso, Chelteau Barajei, A Nongiba Kheni, Emmanuel Appiah-Kubi, A 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 …</text>
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                <text>2023</text>
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                <text>https://scholar.google.com/citations?view_op=view_citation&amp;amp;hl=en&amp;amp;user=ECTxVnYAAAAJ&amp;amp;cstart=20&amp;amp;pagesize=80&amp;amp;citation_for_view=ECTxVnYAAAAJ:qUcmZB5y_30C</text>
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                <text>Using Principal Component Analysis to Identify Latent Factors Influencing Ghanaian Irrigation Project Abandonment</text>
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                <text>Chelteau Barajei, Emmanuel Adinyira, Ebenezer Boakye, Clinton Aigbavboa, Abdul Wahab Iddrisu</text>
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                <text>Despite the investments and efforts to develop irrigation systems, many irrigation projects in Ghana are not working up to design expectations, whilst others have been abandoned altogether. To address this, factors influencing the abandonment of small-scale irrigation schemes in Ghana were interrogated. The study employed the quantitative approach to gather data from key stakeholders. Of the 170 questionnaires distributed, 125 responses were retrieved and analysed using factor analysis. The study revealed that 12 factors influence the abandonment of small-scale irrigation projects and subsequently grouped them into institutional, social, construction, and economic factors. Social factors had the most significant influence (28.68%), followed by economic factors (22.10%), and construction factors (18.88%), with institutional factors having the least impact (10.79%). This is the first study to identify factors …</text>
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                <text>Marketisation is the application of economic theory to the practice of higher education. This is&#13;
based on the fundamental notion of the primacy of the market as a tool for business and&#13;
strategic decisions. The market is the primary unit of focus as it determines supply and demand,&#13;
while the ultimate goal is the maximisation of productivity and profit margins. However, there&#13;
are persistent arguments against the marketisation of higher education. The commercialisation&#13;
or commodification of education and its transactionalisation as a good to be sold by universities&#13;
and purchased by students is probably the most prominent critics. The chapter theoretically&#13;
explored the notion of marketisation and its growth on the African continent and discussed the&#13;
six conceptual ideas had become well developed in the marketisation of higher education in&#13;
order to provide a backdrop for the work covered in the subsequent chapters of this book. The&#13;
concluding section of the chapter provides an overview of the chapters in the book.&#13;
Keywords: marketisation, marketing communication, branding, higher education,&#13;
universities, Africa, edited book, introduction.</text>
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                <text>In this study, we jointly modeled longitudinal CD4 count data and survival outcome (time-to-first occurrence of composite outcome of death, cardiac tamponade or constriction) in other to investigate the effects of Mycobacterium indicus pranii immunotherapy and the CD4 count measurements on the hazard of the composite outcome among patients with HIV and tuberculous (TB) pericarditis. In this joint modeling framework, the models for longitudinal and the survival data are linked by an association structure. The association structure represents the hazard of the event for 1-unit increase in the longitudinal measurement. Models fitting and parameter estimation were carried out using R version 4.2.3. The association structure that represents the strength of the association between the hazard for an event at time point j and the area under the longitudinal trajectory up to the same time j provides the best fit. We found …</text>
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                <text>Spatio-Temporal Modelling of COVID-19 Dynamics in Africa</text>
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                <text>Iddrisu Wahab Abdul</text>
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                <text>Since the outbreak of COVID-19 in China, in December 2019, almost no country in the world has been spared the devastation caused by the pandemic. In this paper, I model and analyze the trend of COVID-19 in Africa along space and time, in order to provide accurate and reliable predictions of the dynamics of the disease in Africa. Data on daily confirmed cases of COVID-19 for fiftytwo countries in Africa from February 14, 2020 to December 04, 2020 were obtained from “Our World in Data”(OWID). A model that captures space-time dependence was fitted to the data and used for analysis. The results indicate that the second wave of the pandemic in Africa is yet to reach its peak. The results also indicate that countries in Africa have been affected by the disease to a very heterogeneous extent during this period. It was also observed that the average reproduction of the disease within countries in Africa, which is known as the autoregressive effect was about 0.46 while the neighbourhood effect, which is the transmission of the disease from adjacent countries, was quite negligible. The seasonality-adjusted factor which indicates how the basic endemic incidence increases per day was observed to be about 1.23 while the epidemic proportion of the disease incidence in Africa was found to be 46%. These findings, indicating where and when the incidence of the disease will be high may be useful for public health decisionmaking, as they provide time to intervene on the local public health systems.</text>
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                <text>Modelling the effects of bile and nutrients on microbes and the evolution of temperature, electrical conductivity, surface tension and pH during biodegradation of used engine …</text>
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                <text>Imoro Abubakari Zarouk, Iddrisu Wahab Abdul, Abubakari Issah</text>
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                <text>At five levels of Bile (No bile, 1.2 ml, 1.4 ml, 1.6 ml and 1.8 ml) and two nutrient levels (Nutrient medium and No Nutrients) the effect of Bile and Nutrients on microbes and the evolution of temperature, electrical conductivity, surface tension and pH were studied and modeled during the bioremediation of a petroleum hydrocarbon contaminated water. Analysis of variance (ANOVA) for α= 0.05 was used to show the variations in parameter values according to the levels of Bile and Nutrients. Microbial colony numbers and pH generally did not show a uniform evolution trend as the level of Bile increased but showed an increasing trend with increment in Nutrients level. Temperature increased with increasing Bile and Nutrients levels only when either Bile or Nutrients Medium was the lone supplement in the experiment. Electrical conductivity increased with increasing levels of Bile whiles surface tension decreased with increasing levels of Bile and</text>
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                <text>J Environ Earth Sci</text>
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