ghanaopendata/ghanaian-research-english huggingface dataset:
Mathematical formulation of new IBFS technique in comparison with VAM for solving a transportation problem

This study is an extension of the research initiated by Somani (2015), to improve the Initial Basic Feasible Solution (IBFS) of a transportation problem (TP). The results of this new IBFS technique were compared to the Somani Approximation Method (SAM) and the well-known Vogel’s Approximation Method (VAM), using two literature values adopted in the study. From the analysis of the basic feasible solutions from the three methods in relation to the first literature data: the IBFS values of the given problem obtained from SAM, VAM and the new IBFS method were 555, 303 and 267 respectively. The corresponding results from the Modified Distribution (MODI) method on the IBFS of SAM, VAM and the new IBFS method also yielded an optimal solution value of 267. The total iterations involved in computing IBFS through to the optimal solution for SAM, VAM and the new IBFS method were 8, 6 and 4 respectively. In the second literature data, the IBFS values of the given transportation problem obtained from SAM, VAM and the new IBFS method were also 640, 625 and 625 respectively. Applying the MODI method on the IBFS of SAM, VAM and the new IBFS method provided an optimal solution value of 625. The total iterations involved in computing IBFS through to the optimal solution for SAM, VAM and the new IBFS method were 6, 4 and 4 respectively. Comparatively, the results from the study, aside from optimal solution obtained from fewer iterations, showed that the new IBFS Technique produces an IBFS value that is better than the one produced by either the SAM or the VAM. It is recommended that the new IBFS technique will be adopted by companies and businesses to solve their transportation problems.

Source: UCC
Mathematical Mindset of Students: A Case of Some Selected Junior High Schools in the Bongo District

This study focused on the mathematical mindsets of students in some selected Junior High Schools in the Bongo District of the Upper East Region, Ghana. Specifically, three research objectives were investigated; to assess the types of mathematical mindset students at the selected Junior High Schools in Bongo District possess; to examine assessment practices likely to influence students’ mathematical mindset at the selected Junior High Schools in Bongo District, and to analyze the effect of mathematical mindsets on the achievement of students in mathematics. The study used the mixed method concurrent design with a sample size of 458 students. A structured questionnaire and interview were used to gather data from respondents of the study. Both descriptive (mean and standard deviation) and inferential statistics (simple regression) were used to address the objectives in the quantitative aspect while thematic analysis was used for qualitative part of the study. The results showed that the students exhibited more of a fixed mindset than a growth mindset about mathematics. Again, the study found that the mathematics teachers use effective questioning, feedback approach and pre-solution procedures as some assessment practices in the schools and finally, it was found that mathematical mindset has a significant positive effect on participating students’ mathematical achievements. The study concluded that approaches aimed at promoting growth mindset of students should be included in every aspect of classroom practice, calling for a change in many mathematics norms at the basic level.

Source: UCC
A mathematical model for effective control and possible eradication of malaria

In this study, a novel deterministic mathematical model for the transmission and control of malaria is formulated. The main innovation in the model is that, in addition to the natural death rate of the vector (mosquito) population, a proportion of the prevention effort also contributes to a reduction of the vector population. The model assumed that a proportion ca; 0 c 1 of the prevention effort a contributes to the death rate of the vector population. The study showed that there exists a domain where the model is epidemiologically and mathematically well-posed. The study showed that the model has a unique disease free and an endemic equilibrium points. It was established that the disease free equilibrium is locally and globally asymptotically stable when R0 < 1 and the endemic equilibrium is locally and globally asymptotically stable when R0 > 1: Parameters of the model were estimated from monthly confirmed malaria cases obtained from the Central Region of Ghana. A sensitivity analysis was carried out to determine the effects of each parameter on the basic reproduction number, R0: The result from the sensitivity analysis showed that the two most sensitive parameters in the reduction of R0 are prevention and treatment. Based on the result from the sensitivity analysis, numerical simulations were performed using various combinations of treatment and prevention to determine an optimal combination that reduces the incidence rate fastest. The result of the simulations showed that, with about 40% of effective prevention coupled with about 40% of treatment, will considerably reduce both the infected human and vector populations. The higher the prevention effort, the higher the reduction in the infected vector population. If the prevention efforts are implemented by all contiguous communities in the region, acting in concert, then a marked reduction should be seen in the infected vector population leading to a complete eradication of malaria in the region, by implication, through out Ghana.

Source: UCC
A mathematical model for lending in microfinance and applications

Loan default is one of the major problems facing most financial institutions. The solution to this problem has been the use of a mathematical model to determine the probability of default of clients of these financial institutions. This study proposes a mathematical model for predicting the probability of default of clients from a microfinance institution. The logistic and survival analysis methods were used in building the model. The results from the logistic regression model showed that the variables Rate, Number of Repayment, Branch Name, Average Inflation Rate and Average Foreign Exchange Rate are significant in predicting the probability of default. The linearity test showed that Number of Repayment was nonlinear and was transformed using restricted cubic splines. The survival analysis model showed that the variables Rate, Product, Branch Name, Easter, New Year, Ramadan, Average Inflation Rate, Average Unemployment Rate, and Average Foreign Exchange Rate were significant in predicting the probability of default of clients. The variables Average Inflation Rate and Average Unemployment Rate were transformed using restricted cubic splines. There also existed interactions between Rate and Product, New Year and Ramadan, and Easter and Average Inflation Rate. The fitted models were evaluated and validated.

Source: UCC
A mathematical model for the control of malaria

Many infectious diseases including malaria are preventable, yet they remain endemic in many communities due to lack of proper, adequate and timely control policies. Strategies for controlling the spread of any infectious disease include a rapid reduction in both the infected and susceptible populations. (if a cure is available) as well as a rapid reduction in the susceptible class if a vaccine is available. For diseases like malaria where there is no vaccine, it is still possible to reduce the susceptible class through a variety of control measures. In this dissertation, we have developed a mathematical model for the transmission of malaria. We have shown that the model has a unique disease-free and endemic equilibria. The disease-free equilibrium Is locally and globally asymptotically stable, if R <_ 1, and that the endemic equilibrium exist provided Ro > 1. Simulation of the model clearly shows that, with a proper combination of treatment and a concerted effort aimed at prevention, malaria can be eliminated from our community. It is not necessary (or impossible) to kill all mosquitoes in order to eliminate malaria. In fact, effective treatment offered to about 50% of the infected population, together with about 50% prevention rate is all that is required to eliminate the disease.

Source: UCC
Mathematical Model of Immune Response to Hepatitis B Virus and Liver Cancer Co-Existence Dynamics in the Presence of Treatment

The principal method for modeling the spread of infectious diseases generally involves the application of ordinary differential equations. Studies have demonstrated that an effective strategy for refining certain mathematical models is the integration of fractional-order differential equations. To gain a more profound understanding of the interactions between the hepatitis B virus (HBV), liver cancer, and immune system cells, a mathematical model that combined both ordinary and fractional differential equations was investigated. This model was closely aligned with experimental data on viral DNA load. The work concentrated on four qualitative scenarios: the innate immune response, adaptive immune response, cytokine response, and the coexistence of infection dynamics. Unlike earlier models, liver cells were classified into distinct stages of infection. For populations of non-pathogenic macrophages in the presence and absence of malignant cells, the study calculated the invasion probability for transmission dynamics, represented by the control reproduction number, Rc. The iterated two-step Adams-Bashforth method was employed for numerical simulations using the ABC fractional derivative in the Caputo sense, while the Latin Hypercube Sampling (LHS) and Partial Rank Correlation Coefficients (PRCC) techniques were utilized for parameter sensitivity analysis. The work identified the key transmission mechanism of viral load and proposed an optimal therapeutic method for viral treatment. Model parameters were estimated using nonlinear least squares fitting of longitudinal data (serum HBV DNA viral load) from existing literature. Finally, the study compared the classical-order model system with the ABC fractional differential equations model system to determine which offered superior performance. Both methods were evaluated using simulation results of the state variables, revealing that the fractional model provides more detailed results than the classical model.

Source: UCC
Mathematical modeling and numerical simulation of a multiscale cancer invasion of host tissue

In this study, we develop an advection-reaction-difusion system of partial diferential equations (PDEs) to describe interactions between tumor cells and extracellular matrix (ECM) at the macroscopic level. At the subcellular level, we model the interaction of proteolytic enzymes and the ECM with a set of ordinary diferential equations (ODEs). A contractivity function is used to couple the macroscopic and microscopic events. The model is supplemented with nutrients supply from the underlying tissue. These PDE-ODE systems of equations model the on-set of tumor cell invasion of the host extracellular matrix. The model accounts for diferent time and spatial scales at the macroscopic and microscopic levels. Contact inhibition between the tumor cells and the tumor micro-environment are also accounted for through a nonlinear density-dependent difusion and haptotaxis coefcients. In the numerical simulations, we use a nonstandard fnite diference method to illustrate the model predictions. Qualitatively, our results confrm the three distinct layers of proliferating, quiescent and necrotic cells as observed in multicellular spheroids experiments

Source: UCC
Mathematical Modelling of Typhoid Fever Disease Incorporating Delay Caused by False Negative Diagnosis

ABSTRACT We developed a mathematical model based on a system of ordinary differential equations to explore the dynamics of typhoid fever sickness, taking into account the delay caused by false negative diagnosis. Typhoid fever continues to be a significant public health problem in a number of countries, particularly devel- oping countries. Typhoid fever, for example, has been classified among the top twenty illnesses in Ghana, accounting for approximately 0.92 percent of hospital admissions. An epidemiological model was developed to determine the impact of delay caused by false negative diagnosis in the spread and treatment dynam- ics of the disease. Protected (P), Susceptible (S), Infected (I), Delayed (D), and Treated (T) classes were established. The next generation technique was used to calculate the basic reproduction number R0. Additionally, it was demonstrated that for R0 < 1, the disease-free equilibrium points were both locally and glob- ally asymptotically stable, whereas the endemic equilibrium points were locally asymptotically stable. Having done numerical simulations, it was found that the delay caused by false negative diagnosis significantly contributes to the spread dynamics and also has an effect on treatment. As a result, we determined that delays caused by false negative diagnoses should be kept to a minimum in order to minimize disease spread.

Source: UCC
Mathematical Models of Breast and Ovarian Cancers

Women constitute the majority of the aging United States (US) population, and this has substantial implications on cancer population patterns and management practices. Breast cancer is the most common women's malignancy, while ovarian cancer is the most fatal gynecological malignancy in the US. In this review we focus on these subsets of women's cancers, seen more commonly in postmenopausal and elderly women. In order to systematically investigate the complexity of cancer progression and response to treatment in breast and ovarian malignancies, we assert that integrated mathematical modeling frameworks viewed from a systems biology perspective are needed. Such integrated frameworks could offer innovative contributions to the clinical women's cancers community, since answers to clinical questions cannot always be reached with contemporary clinical and experimental tools. Here, we recapitulate clinically known data regarding the progression and treatment of the breast and ovarian cancers. We compare and contrast the two malignancies whenever possible, in order to emphasize areas where substantial contributions could be made by clinically inspired and validated mathematical modeling. We show how current paradigms in the mathematical oncology community focusing on the two malignancies do not make comprehensive use of, nor substantially reflect existing clinical data, and we highlight the modeling areas in most critical need of clinical data integration. We emphasize that the primary goal of any mathematical study of women's cancers should be to address clinically relevant questions

Source: UCC
Mathematical Models of Breast and Ovarian Cancers

Women constitute the majority of the aging United States (US) population, and this has substantial implications on cancer population patterns and management practices. Breast cancer is the most common women's malignancy, while ovarian cancer is the most fatal gynecological malignancy in the US. In this review we focus on these subsets of women's cancers, seen more commonly in postmenopausal and elderly women. In order to systematically investigate the complexity of cancer progression and response to treatment in breast and ovarian malignancies, we assert that integrated mathematical modeling frameworks viewed from a systems biology perspective are needed. Such integrated frameworks could offer innovative contributions to the clinical women's cancers community, since answers to clinical questions cannot always be reached with contemporary clinical and experimental tools. Here, we recapitulate clinically known data regarding the progression and treatment of the breast and ovarian cancers. We compare and contrast the two malignancies whenever possible, in order to emphasize areas where substantial contributions could be made by clinically inspired and validated mathematical modeling. We show how current paradigms in the mathematical oncology community focusing on the two malignancies do not make comprehensive use of, nor substantially reflect existing clinical data, and we highlight the modeling areas in most critical need of clinical data integration. We emphasize that the primary goal of any mathematical study of women's cancers should be to address clinically relevant questions.

Source: UCC
Mathematics Classroom Discourse in typical Ghanaian Public School: How does it look like?

This paper reports on a study which investigated the nature of classroom interaction and how that affects the way pupils learn mathematical concepts meaningfully. Observation of mathematics lessons of three primary six teachers from one District in Southern Ghana were recorded. This was followed by analysis of the rationale, general aims and objectives of teaching mathematics and the general teaching approach suggested in the preamble of the mathematics curriculum. The data collected were analysed qualitatively and presented as narrative description with illustrative examples. The results from the study revealed amongst others that the traditional school mathematics microculture constituted the dominant public discourse in the three lessons observed. Discussion of the findings and implication for mathematics curriculum development and delivery, and future research are provided.

Source: UCC
Mathematics Learning through Classroom Assessment: Evaluating the Value of Weekly Class Tests

This study adopted a descriptive case study to explore the impact of weekly class test alongside two other modes of assessment strategies: use of project work and class presentation on learning outcomes in mathematics among 145 year-one high school students in the Central Region of Ghana. Subject evaluation questionnaire and scores obtained in weekly class test, end of term examination, class presentation and project work were the main sources of data collected for the study. The results indicated that scores obtained from all the modes of assessment (class test, class presentation and project work) used in the study correlated with end of term examination; however, the best predictor of end of term examination was class test. Thus, the study revealed that employing class test as an approach in the classroom drives students to deepen their understanding of concepts taught, encourage students to review their notes ahead of each new class session and consequently enhance their learning outcomes. Furthermore, the results demonstrated that students who were most committed in the subject, as evidenced by participation in all class tests, fared significantly better in the end of term examination than those who failed to participate in most of the class tests and those who participated mid-way. Consequently, the study reiterates that increased frequency of class test has the potential to impart student learning outcomes.

Source: UCC
Mature Women Students’ Experiences of Social and Academic Support in Higher Education: A Systematic Review

In the Widening Participation in Higher Education agenda, students' retention and success should be a matter of concem, since high students' attrition can negatively affect the reputation of institutions. Mature women students' juggling roles and academic study place them at a high risk of dropping out or successful completion. Using the guidelines for systematic reviews formulated by the Evidence for Policy and Practice Information and Co-ordinating Centre (EPPI-Centre), this review set out to examine institution-based support systems that are available to mature women students and their experiences of the support systems. It found that very few studies focus on women only. In the studies that included mature women or focused on them, support from friends, tutors and administrators emerged crucial in their stories of progression and successful completion, though this was not systematically administered. Overall, institution-based support was not an important source of support, as in most cases, students had no knowledge about it. The paper recommends the provision and systematic administration of institution-based support for mature women students and regular evaluation of such a system

Source: UCC
A maturity estimation of bell pepper (capsicum annuum l.) by artifcial vision system for quality control

Sweet bell peppers are a Solanaceous fruit belonging to the Capsicum annuumL. species whose consumption is popular in world gastronomy due to its wide variety of colors (ranging green, yellow orange, red, and purple), shapes, and sizes and the absence of spicy favor. In addition, these fruits have a characteristic favor and nutritional attributes that include ascorbic acid, polyphenols, and carotenoids. A quality criterion for the harvest of this fruit is maturity; this attribute is visually determined by the consumer when verifying the color of the fruit’s pericarp. The present work proposes an artificial vision system that automatically describes ripeness levels of the bell pepper and compares the Fuzzy logic (FL) and Neuronal Networks for the classification stage. In this investigation, maturity stages of bell peppers were referenced y measuring total soluble solids (TSS), ◦ Brix, and using refractometry. The proposed method was integrated in four stages. The first one consists in the image acquisition of five views using the Raspberry Pi 5 Megapixel camera. The second one is the segmentation of acquired image samples, where background and noise are removed from each image. The third phase is the segmentation of the regions of interest (green, yellow, orange and red) using the connect components algorithm to select areas. The last phase is the classification, which outputs the maturity stage. The classificatory was designed using Matlab’s Fuzzy Logic Toolbox and Deep Learning Toolbox. Its implementation was carried out onto Raspberry Pi platform. It tested the maturity classifier models using neural networks (RBF-ANN) and fuzzy logic models (ANFIS) with an accuracy of 100% and 88%, respectively. Finally, it was constructed with a content of ◦ Brix prediction model with small improvements regarding the state of art

Source: UCC
Maximum and minimum lumbar interpedicular distances in normal adult Nigerians

The pioneering work of Elsberg & Dyke (1934) and later reports by Landmesser & Heublein (1953), Verbiest (1954, 1955), Simril & Thurston (1955), Schwarz (1956), Hinck, Clark & Hopkins (1966) have established the clinical value of measurements of interpedicular distances in the diagnosis of narrowing of the spinal canal. Verbiest (1954) pointed out that the bony canal could be developmentally narrow, whilst Scheslinger & Taveras (1953) and Verbiest (1954, 1955) described some of the effects of the narrow canal. Since then, the size of the spinal canal has attracted increasing interest. Various techniques, including plain radiographs, myelography, epidural venography, computed tomography and diagnostic ultrasound, have been used to measure the size of the lumbar spinal canal (Hinck et al. 1966; Kirkaldy- Willis, Paine, Cauchoix & Mclvor, 1974; Gargano, Jacobson & Rosomoff, 1974; Eisenstein, 1977; Sheldon, Sersland & Leborgne, 1977; Chynn, Altman, Shaw & Finby, 1978; Porter, Wicks & Ottewell, 1978; Bestawros, Vreeland & Goldman, 1979). Although each technique has its own limitations, Chynn et al. (1978) observed that plain radiographs are of great value in the diagnosis of lumbar spinal canal stenosis.

Source: UCC