ghanaopendata/ghanaian-research-english huggingface dataset:
Modeling domestic violence and predicting its growth using differential equations: a case study of women and children in Tamale

The research work focused on analytic and numerical modeling of Domestic Violence. In the case of the analytic modeling, this thesis discusses a simple continuous model for the spread of Domestic Violence, using Ordinary Differential Equations. A mathematical model is inspired from the spread of Domestic Violence in Tamale Metropolitan in which the interaction of the widespread is likely to be minimized. A modeling technique ASV, similar to the SIR model in Epidemics, is used for formulating the spread of Domestic Violence as a system of Differential Equations. Hence the population of three distinct classes- the Abusive, Susceptible/Unreported Victims, and the Reported Victims, are considered in the model. The system of Differential Equations is analyzed by linearization of nonlinear systems and nondimensionlization, and to predict the behaviour of the spread of the Domestic Violence. Finally, in the case of the numerical analysis, a general model for the population of Domestic Violence Victims is constructed. The present model shows that the given data is reasonably Logistic. Moreover, this model shows that the population of Domestic Violence Victims is limited. A projected limiting number is given by this model. Some typical mathematical models are introduced such as Exponential model and logistic model. The solutions of those models are analyzed.

Source: KNUST
Modeling health Insurance claim severity in NHIS using parametric probability distribution (A case study of Amansie East Municipal)

General insurance companies face two major problems when they want to use past or present claim amount in forecasting future claim severity. First they have to find the appropriate probability distribution for the large volumes of claim amount. Then test how best these distributions fits the claim data The purpose of this study is to fit a particular distribution suitable for the National Health Insurance Scheme in the Amansie East Municipality. Secondary data was collected from Amansie Municipal Insurance Scheme. The exploratory data analysis technique was used to assist in the identification of the family of distribution which the data might follow. Akike Information Criterion and KolmogorovSmirnov used to test the goodness of fit. The diagnostic test probability plot was to used to graphically demonstrate the goodness of fit the distribution. It was found that the Lognormal distribution was appropriate distribution for Fee For Service for all categories of service in the district. However the Burr distribution were considered to be the best distribution for G-DRG in the District level, CHPS compound, Community clinics, Health centers and CHAG hospital. Also lognormal distribution was the best for G-DRG modeling for Private, Chemical and Pharmacy shops and finally the fisk distribution for Public clinics and Maternity. Management at all municipal and district health insurance schemes should be able to apply the appropriate statistical distribution used in this research for management policy prescription to improve their performance.

Source: KNUST
Modeling health insurance claim severity in NHIS using parametric probability distribution: (A case study of Amansie East Municipal)

General insurance companies face two major problems when they want to use past or present claim amount in forecasting future claim severity. First they have to find the appropriate probability distribution for the large volumes of claim amount. Then test how best these distributions fits the claim data The purpose of this study is to fit a particular distribution suitable for the National Health Insurance Scheme in the Amansie East Municipality. Secondary data was collected from Amansie Municipal Insurance Scheme. The exploratory data analysis technique was used to assist in the identification of the family of distribution which the data might follow. Akike Information Criterion and Kolmogorov- Smirnov used to test the goodness of fit. The diagnostic test probability plot was to used to graphically demonstrate the goodness of fit the distribution. It was found that the Lognormal distribution was appropriate distribution for Fee For Service for all categories of service in the district. However the Burr distribution were considered to be the best distribution for G-DRG in the District level, CHPS compound, Community clinics, Health centers and CHAG hospital. Also lognormal distribution was the best for G-DRG modeling for Private, Chemical and Pharmacy shops and finally the fisk distribution for Public clinics and Maternity. Management at all municipal and district health insurance schemes should be able to apply the appropriate statistical distribution used in this research for management policy prescription to improve their performance.

Source: KNUST
Modeling lapse rates with economic variables: The vector autoregressive model approach

Abstract Life insurance contracts are accompanied by risks. This study focuses on the risk involving termination of life policies by the policyholders. This study seeks to identify the main determinants of lapse rates in the Ghanaian life insurance industry. The data available span from 2006 to 2014 and were recorded on monthly basis. Literature research on predictive modeling of lapse rates in the insurance industry led to the choice for predicting with a VAR Model. A total of ve (5) variables were analyzed on their relationship with the average lapse rate. Of these variables in ation, stock market return and interest rate proved valuable for modeling. The vector auto-regression (VAR) model was used to capture the evolution and the interdependencies between the variables. All the variables in the VAR were treated symmetrically by including for each variable an equation explaining its evolution based on its own lags and the lags of all the other variables in the model. The main limitation of this research was the small amount of data and their level of detail. Since the results of this research are promising it is recommended to extend the research to other parts of the country. To increase the statistical strength and accuracy of the inferences that can be made it is also recommended to examine the lapse rates at a policyholder level.

Source: KNUST
Modeling lapse rates with economic variables: The vector autoregressive model approach

Life insurance contracts are accompanied by risks. This study focuses on the risk involving termination of life policies by the policyholders. This study seeks to identify the main determinants of lapse rates in the Ghanaian life insurance industry. The data available span from 2006 to 2014 and were recorded on monthly basis. Literature research on predictive modeling of lapse rates in the insurance industry led to the choice for predicting with a VAR Model. A total of ve (5) variables were analyzed on their relationship with the average lapse rate. Of these variables in ation, stock market return and interest rate proved valuable for modeling. The vector auto-regression (VAR) model was used to capture the evolution and the interdependencies between the variables. All the variables in the VAR were treated symmetrically by including for each variable an equation explaining its evolution based on its own lags and the lags of all the other variables in the model. The main limitation of this research was the small amount of data and their level of detail. Since the results of this research are promising it is recommended to extend the research to other parts of the country. To increase the statistical strength and accuracy of the inferences that can be made it is also recommended to examine the lapse rates at a policyholder level.

Source: KNUST
Modeling lapse rates with economic variables: the vector autoregressive model approach

Life insurance contracts are accompanied by risks. This study focuses on the risk involving termination of life policies by the policyholders. This study seeks to identify the main determinants of lapse rates in the Ghanaian life insurance industry. The data available span from 2006 to 2014 and were recorded on monthly basis. Literature research on predictive modeling of lapse rates in the insurance industry led to the choice for predicting with a VAR Model. A total of five (5) variables were analyzed on their relationship with the average lapse rate. Of these variables inflation, stock market return and interest rate proved valuable for modeling. The vector auto-regression (VAR) model was used to capture the evolution and the interdependencies between the variables. All the variables in the VAR were treated symmetrically by including for each variable an equation explaining its evolution based on its own lags and the lags of all the other variables in the model. The main limitation of this research was the small amount of data and their level of detail. Since the results of this research are promising it is recommended to extend the research to other parts of the country. To increase the statistical strength and accuracy of the inferences that can be made it is also recommended to examine the lapse rates at a policyholder level.

Source: KNUST
Modeling Location of Facility as P-Median Model for Location of Senior High School at Kassena-Nankana West District

Education is the process of learning geared or directed towards assisting the individual to acquire knowledge, skills and to improve his or her life. The main purpose of this research is solving the problem of locating a Senior High School in the Kassena Nankana district. Ten (10) towns in the district were considered, which are; Nakong, Katiu, Chiana, Kajelo, Kayilo, Paga, Nakolo, Sirigu, Manyoro and Binania. Since the problem is a desirable one, we formulated the problem using the p-median model developed by Hakimi (1964; 1965). Reduction heuristic (RH1, RH2 and RRH) was used to solve the p-median problem. According to the model, the Senior High school should be sited at Chiana with objective value of 56234.

Source: KNUST
Modeling microwave protein-glycoconjugates formulations from protein-starch composites

Glycation of food proteins has the great potential of improving the functionality of food systems which can lead to increased utilization of food and ultimately contribute to the reduction of food insecurity. The aim of this project was to produce a glycated protein as food ingredient to effect food functional properties of food model systems. The glycation of two types of composites; Bambara protein-rice starch and Bambara protein-cassava starch was achieved by microwave heat treatment at varying composite ratios and microwave times. Conditions for glycation were optimized using the mixture composite design of response surface methodology. Composites of Bambara protein-cassava starch gave higher glycation values as compared to composites of Bambara protein-rice starch. The maximum glycation for Bambara protein-cassava starch composite was 51.9 (μg/10mg) whiles that for Bambara protein-rice starch composite was 10 (μg/10mg). The optimum conditions were found to be 0.7 g protein, 0.3 g cassava starch and 2.0 min microwave time for Bambara protein-cassava starch composites and 0.6 g protein, 0.4 g rice starch and 6.0 min microwave time for Bambara protein-rice starch composites. It was generally observed that for both types of composites, glycation generally increased with increasing protein content whiles a decrease in both protein content and microwave time led to a reduction in glycated protein content. Bambara proteins can be used in food industries especially in the formation of glycated food proteins to improve the functionalities of locally manufactured food systems with unique food functionalities.

Source: KNUST
Modeling motor insurance claim reserves in Ghana using Bornhuetter Ferguson and Ination adjusted chain ladder.

Claims reserving for general insurance business especially motor (auto or car) insurance is critically important. The in ux and proliferation of insurance com- panies have made claim reserving more intricate coupled with the risk underwrit- ing processes. This research aims at modeling motor claim reserves in Ghana using in ation adjusted chain ladder and Bornhuetter Ferguson method. Motor insurance data used for our analysis ranges from January 2009 to December 2014. The analysis highlighted on estimating the next year (2015) outstanding liabil- ity and the total future outstanding liabilities. In this study, we found out that Bornhuetter Ferguson had a better reserve estimate than that of the in ation Adjusted Chain Ladder due to its expected loss ratio and chi test value.

Source: KNUST
Modeling optimal farm plan for cashew farming households in Northern Ghana

The choice of the farming household at every season on what to grow is driven by profit maximization. Cashew farming households with an established cashew farm cultivate other food crops for home consumption and also for sale in order to generate income during periods when fruiting of the crop have not started. Notwithstanding the benefits derived from this approach, farmers are faced with a decision on what and how much should be added that maximize their socio-economic benefits in line with the resource restrictions. This study therefore has developed a farm optimization model for cashew farming households in Bole district that cultivate other food crops alongside cashew. The study employed a multi-stage sampling technique to select 150 cashew farming households. A structured questionnaire was used to collect the data which was analyzed with General Algebraic Modeling System (GAMS) software to perform the optimization. The goal of the study was to identify the best mix of crops that maximizes gross farm income for both actual and best farm practices under different farm sizes. The optimal cropping plan under actual practices suggest that in order for cashew farming households with 5.25ha of land to maximize gross farm income, maize, cassava, yam and groundnut should be cultivated. Also, as production tends to be commercialized, maize, cassava, groundnut and millet should be cultivated to maximize gross farm income. The optimal cropping plan under best farm practices suggest that shea, sorghum, groundnut and cassava should be cultivated by farming households with 5.25ha of farm land and as production tends to be commercialized the acreages cultivated of these crops increase with shea gaining more focus. A significant difference exists between the optimal cropping plan for the baseline scenario and other alternate scenarios. If farm households were to allocate all their resources to the production of cashew under both farm practices, they would be able to gain enough income to cater for the crop consumption requirement of the household by purchasing from the external market. In periods of displacement of labor where there is less supply of family labor, the acreages of cultivation of the optimal crops should be reduced and sorghum featuring into the optimal plan under actual practices and the acreages of cultivation of the best mix of crops should be reduced and focused on the cultivation of shea under best farm practices. It is therefore recommended based on the optimization results that farming households cultivates these crops alongside their wild shea kernel gathering activities.

Source: KNUST
Modeling Site Development for Garbage Disposal as a 0-1 Knapsack Problem: a Case Study of the Sekondi-Takoradi Metropolis

Integer programming is an important class of mathematical programming problems which is a useful tool for modelling and optimizing real-life problems. The knapsack problem is a form of integer programming problem that has only one constraint and can be used to strengthen cutting planes for general integer programs. These facts make the studies of the knapsack problems and their variants extremely important area of research in the field of operations research. This thesis seeks to apply the branch-and-bound algorithm to model site development for solid waste disposal in Sekondi-Takoradi metropolis as a 0-1 knapsack problem. The model developed could be adopted for any land site management problem that can be modelled as a single 0-1 knapsack problem. Seven sites were proposed for development and the study reveals that sites A, B, F and G should be selected to obtain an optimum output and recommend that Knapsack problem model should be adopted by the district assembly for refuse disposal management.

Source: KNUST
Modeling of production plan and scheduling of manufacturing process for a beverage company in Ghana

Production scheduling is a decision-making process that is used in manufacturing and service industries to achieve effciency and minimize production cost. The goal with this research is to optimize the production and Scheduling of products of a beverage company by developing a model that displays the optimal production plan for a given planning horizon. The model is designed in a way that it can be implemented on any kind of Beverage Company: The model can also be implemented on different kind of production to make a production plan. A Mixed Linear Programming Model to support decision making is presented, in order to nd the optimal production plan, by maximizing the production and reducing cost. Data from Promasidor Ghana Limited was applied to the model. Results from the model were analyzed and sensitivity analysis was carried out. I found out that the mixed linear programming model is an e cient approach to solve a production planning and Scheduling problems.

Source: KNUST
Modeling of revenue mobilization of District Assemblies: a case study

The Act 462 of the Parliament of the Republic of Ghana, the Local Government Act empowers the District, Municipal and Metropolitan Assemblies to mobilize revenues within their boundaries, and to receive assistance from the Central Government and Donor Agencies for development. The bulk of revenues to the Assemblies are from the Central Government and Donor Agencies. If the gap between the internally generated revenue and the external source of funding is not bridged, the development of most districts in the country would be dictated from outside. This work was carried out in the Afigya-Sekyere District Assembly to investigate the trends of inflow of revenue into the District and to develop mathematical models which can be used to predict the inflow of revenues into the district in the years ahead. Regression analysis and differential equations were used to model the trend of inflow of revenue, both locally and external. The trends of Ghana's GDP, both nominal and real were also modeled. Nominal GDP gave rise to logistic growth whilst the real GDP gave rise to almost exponential growth. The data on the real GDP of Ghana from 1993 to 2004 were analyzed using a model developed by Chukwu (1993). The model developed by Chukwu (1993), is used to determine whether or not there are oscillations or fluctuations in a country's GDP or GNP using available data. Chukwu's model can be extended to investigate the behaviour of the economy of any district in Ghana provided there are data available. It was realized that there were no oscillations or fluctuations in the trend of the real GDP of Ghana from 1993 to 2004. Two time dependent models for the inflow of revenue into the Assembly were identified: the exponential and the logistic models. The exponential model is expected to work when there is inflation in the country or more sources of revenue are being identified. Logistic model is expected to work for a longer period of time when the economy is be coming stable and almost all the potential sources of internally generated revenues have been identified.

Source: KNUST
Modeling occurrence of death in Ghanaian female pensioners

The study considered count data with excess zeros and over-dispersion. The models used for this situation of the study data are the zero-inflated negative binomial (ZINB) and the negative binomial (NB) regression model. This was to establish whether the parameter age is a function of mortality for the various cohort groups. Also the Akaike Information Criteria (AIC) goodness of fit testing was used to determine a best fit for the cohort groups with the various model. The ZINB regression model best fitted the female pensioners‟ data for the 2005 cohort group while the NB regression model best fitted the 1990 cohort group. Other parameters like causes of death and standard of living after retirement must be considered in future model.

Source: KNUST
Modeling the bond strength of reinforced concrete with oil polluted rebars

The serviceability and ultimate strength of reinforced concrete structures is greatly influenced by the strength of the bond mechanism between steel and concrete. The bond ensures that the structure maintains its state of equilibrium under any giving load. This study examined the basic influence of used engine oil on bond strength at the steel–concrete interface and subsequently develops models for predicting it. Ninety (90) concrete specimen of dimension 150 x 150 x 150mm with rebar inserts were used. Three (3) grades of concrete (C15, C20, C25) were designed. The loss adhesion and the decrease in the frictional resistance was evaluated using pullout test specimens with different levels of rebar oil pollution. The results revealed that used engine oil coating has adverse (negative) effect on the bonding action between concrete and steel reinforcement. It forms a layer on the concrete-steel interface which impairs the gripping of the steel bar within the concrete-steel interface and consequently gives rise to a weakened bond. The loss in bond strength was higher for mild steel than for high tensile steel. Finally, using the regression analysis tool pack in Microsoft excel (2010 version) the relationship between the dependent variable (bond strength) and the independent variables (degree of oil pollution and concrete compressive strength) was established for two grades of steel (Mild steel and high tensile) as follows: τ_Msteel = 0.2699f_cu – 1.8451 X_P and τ_Hsteel = 0.3105f_cu – 1.5939 X_P. From the findings it was concluded that the use of oil as formwork releasing agent on construction site should be carefully carried out to ensure that the bars are free from oil. Moreover, designers should factor the effect of oil in the design of the ultimate bond strength of reinforced concrete structures in situation where oil is used on the construction site.

Source: KNUST
Modeling the contribution of high risk imports to National Revenue – A case study of the Tema Harbor

Effective Revenue Mobilization has been the bedrock of many countries including Ghana and over the years the importations of High Risk Goods have featured prominently in the revenue mobilization process. Recently, there have been indications by Governments past and present to place a ban on the importation of the High Risk Goods. This research was aimed at assessing the contribution of the High Risk Goods to National Revenue and their effect on Revenue Mobilization if a ban is placed on their importation into the country. For the sake of this research work, secondary data was obtained from the Policy Department of the Customs Division of the Ghana Revenue Authority (GRA) on the High Risk Goods which include Used Clothing, Used Fridges, Used Microwaves and Used Auto parts. The others are Rice Products and Used Computers and Accessories. Regression Analysis, Time Series and ANOVA were used to analyse the data and to formulate a model for forecasting the National Revenue for the next ten (10) years. The results showed that the High Risk Goods contributes significantly to National Revenue and a ban on them will affect National Revenue Mobilization. The proposed model for forecasting the National Revenue is Total Duty = 327624.460 - 0.278*TNW + 0.342*TPkg + 0.943*CIF + error, where Total Duty is synonymous with National Revenue for the sake of this research work. It is highly recommended that an extensive assessment should be conducted on the intangible gains that will be made in terms of health and environmental safety if the ban is placed on the said products.

Source: KNUST