Master of Computer Science

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https://testir.kiu.ac.ug/handle/20.500.12306/3607

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Query Optimization and Database Tuning In Free and Open Source Software Databases and Proprietary Databases
(Kampala International University, school of computer science, 2006-10) Suleiman Kedir, Nebi
There are many factors that affect the performance of databases and database throughput. However, more often than not, these factors are not critically analyzed and assessed by the Database Administrator or by any person charged with the responsibility ot overseeing the day-to-day running of the database. Critical and complex Queries are needed frequently to be executed. Most of the times these queries are not tuned effectively to get maximum out put, so it Is needed to tune them according to the environment in which they are used. There is therefore a need to determine the performance indicators for the database when it comes to query optimization and database tuning. These indicators are also influenced by the platform on which the database is to be run- proprietary or open source. This research therefore tries to carry out a comparative study and analysis of the query optimization and database tuning on the two platforms windows and Linux. The major findings of this research Is that MySQL Unux database runs faster than MySQL windows and Oracle windows when creating tables whereas the execution time is faster in oracle on windows when a query contains a join. This is found to be based on the Cost-base Optimization (CBO) execution plan and path taken by the query optimizer which is found to be more complex in Oracle than in other databases.
Analysis, design and implementation of a computer-based information system for Dairo air services handling limited
(Kampala International University, School of Computing and Information Technology, 2009-07) Nakigozi, Linda
Standard of flight handling depends a lot on flight information management. However, DAS Handling’s current system is not efficient (manual data entry is slow and prone to errors) and is unreliable. DAS Handling Ltd needs a fast and reliable means of flights’ data circulation. Information on flight handling should be easily accessible by all parties involved in order to have quick turnaround of flights. this study therefore aims at identifying means that can minimize additional costs that may arise due to delay of flights on ground, and provide complete and consistent information about activities taking place in all departments at all times based on a variety of concurrent data sources. The study is a non-experimental research and followed a case study design (in-depth information about a limited number of subjects, and may produce new insights that generate additional studies, according to yin (1994); specifically an exploratory case study (fieldwork, and data collection may be undertaken prior to definition of the research questions and hypotheses).
Developing framework for adopting e-learning pedagogical approach in Higher Education : a case for Makerere University, Kampala, Uganda.
(Kampala International University, School of Computing and Information Technology, 2012-10) Humphrey, Mukooyo Geoffrey
The overall objective of this study is to investigate the challenges of adopting e-learning pedagogical approach in higher education in higher education institutions in Uganda. The descriptive research design method was employed in this study. It involved using the questionnaires in collecting data from the respondents. The quantitative research design was used in gathering data on cases of efficiency in accessing, retrieving, securing, storing, registering and disseminating information the departments. Furthermore, this research collection technique was used because it was flexible and reliable method of data collection. The sample size 171 respondents from Makerere University, Kampala, Uganda. The researcher used simple random sampling which was a type of sampling technique that allowed researchers to collect data in which each element in the population has a known and equal probability of selection. This technique was convenient in order to achieve the research objectives because the respondents would have the same chance to be in sample. The research findings were that the students and lecturers could use the e-learning platform without any hindrance and online learning required Internet access and transmission of multimedia materials required high bandwidth. Universities could tackle some issues themselves. They could come together in order to buy bandwidth in bulk so as to reduce costs. To gain this kind of negotiating power, institutional leaders and IT departments must cooperate. Institutional managers would also have policies for using bandwidth sensibly by defining acceptable use. The recommendations are that use of new collaborative technologies required team work more than we were used to, in order for eLearning courses to produce an outcome that was competitive in the global employment market; universities need to invest carefully in online courses and before commencing an eLearning program, capacity analysis needs to be done first
Polyethylene terephthalate aggregates in structural lightweight concrete
(Springer, 2023-08-30) Chikadibia Kalu Awa Uche; Sani Aliyu Abubakar; Stephen Ndubuisi Nnamchi; Kelechi John Ukagwu
There is growing interest in the use of recycled materials in the building sector as a way to reduce waste and improve environmental sustainability. Polyethylene terephthalate (PET) is a thermoplastic polymer that has attracted the attention of researchers due to its application in the building industry. In the recent past, many studies have reported on the application of PET aggregates in structural lightweight concrete. This paper presents a review of the fndings of 20 studies conducted between 2010 and 2022 randomly. The preliminary fndings highlighted include the method of production of PET aggregates and their physical/thermal properties. The review extended further to focus on the extent of incorporation, physical properties, strength properties, and durability of concrete with PET aggregates. The substitution of PET aggregates up to 20% refected positively on the compressive strength, while tensile and fexural strength had positive responses up to 10%. Water absorption as a measure of concrete durability increased with the addition of PET aggregates. A meta-analysis of these fndings was performed using hypothesis testing (t-test and f-test) to identify signifcant diferences between the experimental outcomes of PET incorporation in concrete. Experimental procedures with greater tolerance for PET inclusion and satisfactory concrete properties were highlighted. The paper recommends the formulation of hybrid mix proportions, developed from experimental designs with noteworthy inclusion of PET aggregates and those that attained high values of desired concrete properties. Furthermore, optimization should be performed to provide robust mix designs for high-strength or lightweight concrete with PET aggregates.
Predicting the Growth Rate of Uganda Economy Using Foreign Trade Flow on Grains and Beverages
(2024) Ibrahim Mumin Mohamud
This study explores the impact of foreign trade flows on Uganda's economic growth from 1990 to 2023, focusing on key export commodities, including grains (wheat, rice, maize) and beverages (coffee, cocoa, tea). A stationarity assessment using unit root tests showed that cocoa, rice, coffee, and economic growth data were stationary at level, while wheat, tea, and maize required differencing to achieve stationarity. Multicollinearity analysis confirmed the absence of significant multicollinearity among the variables, allowing for reliable regression modeling. Regression models were fitted to quantify the relationship between these export flows and economic growth. The results revealed that the overall models demonstrated weak statistical significance, though individual components like rice, maize, and tea-cocoa showed notable effects. Among the models, the ARDL Grains, Beverages Interactions, and Economic Growth model was identified as the best predictor, with an AIC of 3.202 and a moderate RMSE of 0.560, suggesting a reasonable balance between model accuracy and complexity. The study concludes that; while grains and beverage exports have a moderate positive impact on Uganda's economic growth, the interactions between these exports require further model refinement for improved predictive performance
Structural Equation Model Analysis of Sex Education, Hiv/Aids Knowledge and Attitude, among University Students at Kampala International University, Kampala, Uganda
(2024) Womunga Emmanuel
This study explores the impact of sex education on HIV/AIDS knowledge and attitudes among students at Kampala International University, addressing ongoing challenges in effectively curbing HIV/AIDS through education. The primary objectives were to examine the relationship between sex education and HIV/AIDS knowledge, assess the correlation between knowledge and attitudes, and construct a structural equation model (SEM) illustrating these interactions. A cross-sectional design was employed, collecting data from 425 students through a stratified sampling technique. Data analysis was conducted using SPSS, Python, and Smart PLS, utilizing logistic regression and SEM for model construction. The results revealed that sex education accounts for 13.6% of the variability in HIV/AIDS knowledge, indicating a moderate influence. Furthermore, 34.9% of the knowledge gained influences students' attitudes toward HIV/AIDS, suggesting a significant correlation. The SEM analysis demonstrated positive and significant relationships between sex education, HIV knowledge, and attitudes. The study concludes that comprehensive sex education significantly enhances students' understanding of HIV/AIDS, which in turn positively influences their attitudes toward the disease. Recommendations include integrating sex education into the university curriculum to bolster HIV/AIDS prevention efforts.
A Framework Design for Handling Technical Factors Affecting Deployment of Mobile Networks in Uganda
(2024) Tuhame William
Telecommunications service quality and coverage are major concerns globally, especially in the mobile communications sector. In Uganda, the deployment of mobile networks faces various technical, operational, and business challenges (UCC report, 2022). This study aimed to design a mobile network framework that addresses these technological issues to ensure widespread coverage and high-quality services (QoS) nationwide. Using a mixed-methods approach, the research gathered quantitative data from 109 stakeholders, including mobile telecom companies, infrastructure providers, and the Uganda Communications Commission (UCC), alongside qualitative insights. Findings revealed that mobile network deployment in Uganda is moderately high, with emerging technologies impacting deployment at a moderate level. Key factors facilitating deployment included spectrum availability and regulatory support. To enhance network coverage and reliability, the study recommended increasing the number of deployed endpoints, utilizing unlicensed spectrum, and establishing more ad hoc networks in remote areas. It proposed using the Communication and Computing Energy Cost model for rural regions and wireless mesh networks for broader coverage. The designed framework simulated using Packet Tracer, effectively addressed key technical factors, enhancing security, optimizing spectrum usage, and improving infrastructure performance. Recommendations for improving deployment quality and coverage included increasing mobile tower numbers, reducing costs through innovative backhaul technologies and low-cost base stations, and ensuring affordable power supplies. The study also emphasized the need for revised spectrum management policies, collaborative strategies among stakeholders, and increased investment in ICT infrastructure.
Modeling the Associated Factors with Early Sexual Initiation among Female Youth in Uganda
(2024) Isabirye Julius
The aim of the study was to find out the associated factors with early sexual initiation among female youth in Uganda. This research utilized secondary data from the Uganda Demographic and Health Survey (UDHS, 2016), administered by the Uganda Bureau of Statistics (UBOS).The study considered 8,406 female youth who participated in the UDHS 2016survey, aged between 18 and 30 years, and engaged in sexual intercourse between 8 and 30 years. The study was analyzed at three stages namely univariate, stepwise variables selection, and multivariate analysis. The study used stepwise backward selection method in the process of selecting predictor variables for multivariate analysis. After the variable selection and multicollinearity test, the selected independent variables were used to run the multiple logistic regression against the outcome variable. Concerning the socio-demographic factors, the study found that age of the respondent, education level, and sub regions were significantly associated with early sexual initiation among female youth in Uganda at 5% significance level. For economic factors, it was found that occupation of the female youth had a significant association with early sexual initiation at 5% significance level. Regarding the environmental factors, the study found that alcohol abuse had a significant association with early sexual initiation among the female youth in Uganda at 5% significance level.In conclusion, the lesson learnt from the study is that socio-demographic, economic, and environmental factors play a significant role towards early sexual initiation among female youth in Uganda.The study recommends that more sexuality lessons that address the dangers of early sexual initiation should be introduced in lower schools like primary and lower secondary schools in Uganda since they are most at risk.
A Statistical Evaluation of The Effect Of Public Debt On Gross Domestic Product Growth Rate in Uganda (1988- 2022)
(2024) Hassan Sheikh Ali Hilowle
The purpose of this studywas to assess the impact of public debt on the GDP growth rate of Uganda from 1988 to 2022. It aimed at investigating the short-term and long-term correlations between public debt and economic growth, focusing on understanding how varying levels of public debt influence GDP growth over time. The study utilized a 34-year time-series dataset and incorporated macroeconomic factors such as inflation, exchange rates, and government expenditure that ensured a comprehensive analysis. The methodology involved descriptive analysis, trend assessment, and regression analysis, utilizing Ordinary Least Squares (OLS) regression that gauged the association between public debt and GDP growth rate, while controlling relevant variables like inflation, exchange rates, and government spending. The data's stationary was confirmed using the Augmented Dickey-Fuller (ADF) test, and the ARDL bounds testing approach was employed to identify long-term relationships between the variables. The findings indicated that public debt has a negative impact on Uganda's GDP growth rate in the long run, with external debt posing a more significant threat to economic growth compared to domestic debt. In the short term, the influence of public debt on GDP growth was more moderate but still noteworthy. The analysis suggested that surpassing specific thresholds of public debt can result in slower economic growth. Furthermore, inflation and exchange rates were identified as notable influencers of GDP growth during the study period. The study concludes that while public debt is essential for funding development projects, excessive accumulation can impede Uganda's long-term economic growth. To ensure sustainable growth, the results emphasized the need for prudent debt management and a balance between borrowing for development and maintaining debt sustainability. Policymakers are encouraged to implement strategies that prevent adverse long-term impacts on the economy.
A Machine Learning-Based Model for Predicting Credit Facility Defaulters in Uganda
(2024) Muddu George
Predicting credit facility defaulters in Uganda poses a significant challenge, particularly for individuals lacking formal banking histories. This study aims to address this gap by leveraging machine learning techniques on a diverse set of financial data, including mobile money transactions, FinTech services, and traditional banking records. By developing a more inclusive creditworthiness assessment tool, we seek to enhance financial inclusion for underserved populations. Several machine learning algorithms to predict loan defaults were evaluated, including Logistic Regression, Support Vector Machines (SVM), and Extreme Gradient Boosting (XGBoost). The XGBoost model emerged as the most effective, achieving an accuracy of 95.23%, a recall of 73.32%, a precision of 94.11%, and an AUC of 0.8119. In contrast, the Logistic Regression model attained an accuracy of 89.53%, with a significantly lower recall of 43.24% and precision of 66.59%. The SVM model performed moderately, with an accuracy of 93.21% and a recall of 62.80%, but it still fell short compared to XGBoost. The findings highlight the potential of advanced machine learning models like XGBoost to significantly improve credit scoring systems. By providing a more accurate and inclusive tool for credit evaluation, financial institutions and policymakers can better identify potential defaulters, mitigate loan defaults, and foster economic growth among underserved communities
Statistical Modelling of the Determinants of Fertility among Women of 15 – 49 Years of Age in Uganda
(2024) Miriam Basigirenda
The purpose of this study was to identify the factors associated with fertility among women of reproductive age in Uganda. The study aimed to determine the prevalence of the total fertility rate in Uganda, establish the sociodemographic and economic factors associated with fertility, identify reproductive factors associated with fertility, and fit a predictive model for the TFR.. Descriptive statistics were employed to ascertain fertility prevalence, while a multivariate analysis using negative binomial regression was used to identify associated factors. The study used STATA version 17 to conduct analysis at different levels. The study found that the average total fertility rate in Uganda is approximately 4 children per woman. Key sociodemographic and economic factors associated with fertility include a woman's age, education level, marital status, wealth index, and region of residence. The reproductive factors such as age at first sexual intercourse, age at first marriage, and the duration of breastfeeding were significantly associated with fertility rate in Uganda. The study concludes that social demographic, economic, and reproductive factors play a significant role towards fertility rates in Uganda. The study recommends implementing targeted family planning programs for women aged 20 to 49 years. It also suggests strengthening initiatives to increase access to education for girls, particularly in rural areas and expanding access to family planning services for married women, women in partnerships, widows, and those who are divorced or separated
Statistical Modelling of Factors Affecting the Length of Time for Water Collection among Rural Women in Northern Uganda
(2024) Kisubi Nelson
Background: The study aimed to model the factors affecting the length of time for water collection among rural women in Northern Uganda. The study utilized secondary data from the Uganda Demographic and Health Survey (UDHS) 2016, conducted by the Uganda Bureau of Statistics (UBOS). Methodology: The analysis utilized data from 3,483 rural women aged 15 to 49 from Northern Uganda who participated in the 2016 UDHS survey. The analysis was conducted at three levels: univariate, bivariate, and multivariate. Results: The study found that socio-demographic factors such as women’s age, sub-regions, and household size, as well as the economic factor of wealth quintile, were associated with the length of time for water collection among rural women in Northern Uganda. However, no community-level factors studied were associated with the time of water collection. Conclusion: The study concluded that the risk of prolonged water collection time (exceeding 30 minutes) increased for older women compared to younger ones, women in the Karamoja sub-region compared to those in Lango, Acholi, and West Nile sub-regions, larger households, and women from poorer backgrounds compared to wealthier ones. It recommended targeted interventions to help older women, particularly those in Karamoja and from larger households, reduce the time spent collecting water.
Statistical Analysis of Agricultural Production and Income Per Capita Growth Rate in Uganda 1988-2022
(2024) Sakariye Abdullahi Abdi
The relationship between Uganda's agricultural output and income per capita growth rate between 1988 and 2022 is examined using Statistical analysis. Multiple linear regression is used in the study to examine the data gathered during the designated time frame. The results show that agricultural output has been trending downward over time, but per capita income has been steadily rising. Table 4.2 in the analysis shows that agricultural production has a moderate impact on Uganda's income per capita growth rate, despite the country's diminishing agricultural output. These results are consistent with earlier studies, demonstrating the critical role that agriculture plays in the economic growth of countries, especially those with lower per capita incomes. Furthermore, the study shows a causal relationship—albeit one with a limited effect on total economic growth—between agricultural productivity and income per capita growth rate. These variables have statistically significant short- and long-term correlations, highlighting the long-lasting impact of agricultural activities on income levels throughout time. The study concludes by highlighting the significance of policies targeted at improving agricultural production, assisting the agricultural industry, and controlling variables like labor availability and interest rates to guarantee sustained income development and the decrease of poverty in Uganda. These findings offer insightful information for stakeholders, researchers, and politicians looking to advance the well-being and economic growth of agricultural economies
A Logistic Regression Analysis for the Risk Factors Associated with Malnutrition among Children Under 5 Years in Uganda
(2024) Iradukunda Orly Davis
This study investigated the risk factors associated with malnutrition among children under 5 years in Uganda between 2006-2016. The study was guided by the following research objectives: i) to identify the demographic factors associated with malnutrition in children under 5 years in Uganda between 2006-2016; ii) to find out the socio-economic factors by fitting it into regression models, associated with malnutrition in children under 5 years in Uganda between 2006-2016; and iii) to establish the feeding practices associated with malnutrition in children under 5 years in Uganda between 2006-2016. The study adopted cross-sectional studies based on data from the Uganda Demographic and Health Surveys (UDHS) from 2006, 2011, and 2016. The study population was 10,152 participants. The study used multistage sampling technique. Data analysis was performed using binary and multivariate logistic regression. The demographic factors associated with malnutrition in children under five in UDHS 2016, 2011, and 2006 included, age, sex, birth interval, size at birth, and residence. In addition, the study found that breastfeeding practices associated with malnutrition in children under five in UDHS 2016, 2011, and 2006 is ‘not breastfeeding’. The study concluded that the factors associated with malnutrition are: age, sex, birth interval, size at birth, residence, mother’s nutritional status, mother’s education, wealth quintile, and not exclusively breastfeeding a child. The study recommended among others that interventions should be focused on child health promotion and prevention, improvement of household wealth index and food security, including mother’s awareness regarding health nutritional care of children <5 years in Uganda. New policies in nutritional intervention, particularly for mothers with low BMI and children who have smaller size at birth should be implemented by the government to improve health and nutritional status of children <5 years in Uganda
Statistical Modelling of the Effect of Government Investments on Poverty Alleviation in Mogadishu, Somalia
(2024) Sakerie Saed Mouse
This study examines the effect of government investments on poverty alleviation in Mogadishu, Somalia, focusing on key sectors such as agriculture, manufacturing, and small and medium enterprises (SMEs). Data were collected through surveys and official government reports. By employing advanced statistical methods, including Granger-causality tests, Johansen co-integration tests, Lasso regression, and Ridge regression, the research analyzes both short-term and long-term impacts on poverty reduction indicators like household income, access to clean water, food, and shelter. The findings reveal that investments in SMEs have the most significant positive effect, driving improvements in living standards and contributing to sustainable economic growth. In contrast, investments in agriculture show a less consistent impact, suggesting the need for more targeted strategies to enhance their effectiveness. The manufacturing sector also contributes to poverty alleviation, though its effects are less pronounced compared to SMEs. This study underscores the importance of sector-specific investment strategies, particularly focusing on SMEs, to achieve meaningful poverty reduction in conflict-affected regions. Additionally, it is recommended that policy makers prioritize resource allocation towards sectors demonstrating the highest returns on investment for poverty alleviation. The findings contribute to the broader discourse on development economics, highlighting key areas for continued research and policy refinement.

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