Kabale University Digital Repository (KAB-DR)
KAB-DR preserves research output from the Kabale University community
Communities in KAB-DR
Select a community to browse its collections.
- The collections in this Community are comprised of Indigenous Knowledge emanating from communities in the neighborhoods of Kabale University. These are communities in the great Kigezi Region.
- This community holds students (Graduates) dissertation and Thesis, Staff field reports, Students (undergraduate) study reports
- The community includes research article publications in journals both local and international, conference papers in proceedings and reports, abstracts and reviews by Kabale University Staff and Students
- This community archives publications by individual University Staff and Students, Faculty and Departmental Publications (i.e. University Journal, Newsletters, University official publications etc.), groups and Association operating in the University (i.e. Convocation and Staff and Students Association}
Recent Submissions
Analyses of Bioretention Systems for Removal of Stormwater Pollutants
(Journal of Ecological Engineering, 2024) Sholagberu, Abdulkadir T.; Nuwagaba, Emmanuel; Tibenderana, Philip; Terseer, Ako; Bainomugisha, Jonan; Twesigye-omwe, Moses N.; Agwe, M. Tobby; Oluwatosin, Olofintoye O.
Stormwater transports directly into rivers eroded soil, animal wastes, pesticides, fertilizers and other potential pollutants. Bioretention is often designed to capture and treat it using the natural properties of soil and plants. However, selection of appropriate media structure and plants need to be adequately studied. This study investigated the performance of bioretention system in removing stormwater pollutants using Dracaena, a local plant, also called Song of India Plants. Physical model of three Columns A, B and C were developed having five layered filter media of different configurations whose materials were analyzed to meet the design standards. The plants were introduced into Columns A and C leaving out B as control experiment. The quality parameters were determined before and after treatments at ages 10, 20, 30and 40 days when Dracaena plants were introduced into bioretention models. The results showed that the bioretention model drastically improved stormwater quality by reducing values of electrical conductivity, total coliforms (TC), fecal coliforms (FC), total suspended solids (TSS) and biochemical oxygen demand (BOD) as compared to the tested raw stormwater samples. The filter media in both Columns A and C substantially reduced the pollutant levels to standard discharge limits for all parameters tested such as TSS, TC, FC, BOD and nitrates. BOD fell within the recommended standard after 20 days of treatment in Column C with considerable reduction in TC and FC by 68.9% and 75.4% respectively when compared to raw stormwater sample. However, Column C completely removed TC and FC at 40 days which are pathogen indicators in wastewater. This study would be useful to the stakeholders for sustainable stormwater treatment and management.
Performance evaluation of lime improved lateritic soil with the addition of pulverised snail shell and sawdust ash for sustainable highway infrastructure
(Discover Civil Engineering, 2024-02-03) Fadugba, Olaolu George; Ojo, Adeyemi Amos; Oluyemi Ayibiowu, Bamitale Dorcas; Omomomi, Oladapo Jayejeje; Bodunrin, Michael
This research investigated the effects of lime, Pulverized snail shell (PSS), and sawdust ash on the mechanical proper ties of lateritic soil for soil stabilization in construction. The use of this waste materials aligns with the United Nations’ Sustainable Development Goals (SDGs), particularly Goal 12 on responsible consumption and production and Goal 9 on sustainable infrastructure development. Reusing waste materials for soil stabilization supports a circular economy approach, diverting these materials from landfills and promoting their sustainable use as valuable resources. Various tests, including maximum dry density, moisture content, unconfined compressive strength (UCS), triaxial, permeability, compressibility, and California Bearing Ratio (CBR) tests, were conducted on soil samples with different proportions of additives. The results show that the addition of additives reduced maximum dry density and increased moisture content. The sample with 6% lime and 7.5% PSS exhibited the highest UCS of 302 kPa after 28 days of curing, while the untreated sample had a UCS of 121 kPa. Triaxial tests revealed reduced cohesion and increased angle of internal friction with higher additive content. The 6% lime and 7.5% PSS sample displayed the highest shear strength of 60.6 kPa and elastic modulus of 181.8 MPa. Permeability tests demonstrated that the 6% lime and 6% sawdust ash sample had the lowest permeability (6.67 × 10–7 m/s) among the stabilized samples. The untreated soil exhibited high compressibility, whereas the 6% lime and 7.5% PSS sample exhibited the highest resistance to compression and deformation. The untreated soil had a soaked CBR value of 8%, while the 6% lime and 7.5% PSS sample achieved the highest soaked CBR value of 38%, making it suitable as a sub-base material. These findings highlight the effectiveness of lime, PSS, and sawdust ash in enhancing the mechanical properties of lateritic soil and offer valuable insights for soil stabilization in construction of Sustainable Highway Infrastructure.
Industrial Monitoring System with Real-time Alerts and Automated Protection Mechanisms
(Modern Education and Computer Science Press., 2025-04-08) Nabusha, Alice; Asiimwe, Julius; Bature, U. I.; Mugisha, Simon; Tusiime, Meron
This work presents the design and prototyping of an Industrial Monitoring and Protection System aimed at enhancing safety and operational efficiency in industrial environments. The system integrates multiple sensors with a GSM module to monitor and respond to critical environmental parameters, such as ambient light levels, temperature, and smoke detection. A Light Dependent Resistor (LDR) is configured to detect excessive lighting levels, interfacing with a microcontroller to activate the GSM module and send alert messages when thresholds are exceeded. The temperature sensor continuously monitors ambient temperature, and upon detecting overheating, the microcontroller triggers the GSM module to notify operators. Similarly, a smoke sensor detects the presence of harmful smoke and initiates an alert through the GSM module for early fire hazard detection. These sensors are connected to the microcontroller via analog and digital input pins, with their outputs processed to enable condition-based responses. A relay switch, controlled by the microcontroller, automatically disconnects connected loads when safety thresholds are breached, preventing equipment damage and ensuring personnel safety. Real-time sensor readings and system status are displayed on an OLED screen, providing operators with comprehensive, up-to-date information on the monitored environment. The system dynamically responds to environmental conditions by triggering alerts and actions based on customizable safety thresholds for light intensity, temperature, and smoke levels. This integrated architecture ensures seamless communication between sensors, the microcontroller, and the GSM module, delivering real-time monitoring, automated protective mechanisms, and early warning capabilities. The proposed system demonstrates the feasibility of affordable and scalable solutions for industrial safety, offering immediate responses to hazardous conditions while minimizing downtime. Furthermore, its adaptable design allows for customization across different industrial environments, making it suitable for a wide range of applications.
A Regression Model to Enhance the Profitability of Local Construction Contractors in Uganda
(Journal of Construction in Developing Countries, 2021-08-23) Buhamizo, Isaac; Muhwezi, Lawrence; Sengonzi, Ruth
Doubtlessly, the primary goal of every construction company is to maximise profitability. Without this, construction companies cannot survive. Incidentally, Ugandan local construction contractors (LCCs) continue to collapse in a short period, despite enormous public and private investments in the construction sector. This study investigates the profitability of LCCs in Uganda. An investigation was conducted to develop a regression model that would enable LCCs to enhance their profitability and minimise business failure. A questionnaire survey was conducted to collect primary data from 47 local construction companies registered with the Uganda National Association of Building and Civil Engineering Contractors (UNABCEC) and secondary data were collected from audited books of accounts covering from year 2016 to 2018. Thirty-five valid responses were received, representing a response rate of 74%. Data were coded into SPSS version 25, analysed and displayed using the relative importance index (RII), statistical correlation and regression analysis. The findings indicated that the profitability of LCCs was unsatisfactory when compared to the profitability ratios recommended for the construction industry and those of contractors in other countries. The results also indicate that the profitability of LCCs is significantly affected by the timeliness of payments, cost of f inance, competitive bidding environment, project delays, price fluctuations and corruption tendencies, in that order. The findings of this study will benefit construction industry players by providing awareness about the factors affecting the profitability of LCCs. A regression model to enhance profitability was developed using regression analysis. This will help LCCs enhance their profitability by developing mitigation strategies that prevent low profitability; consequently, business failure will be minimised.
Mathematical Modeling of Traffic Flow in Kampala City Using the Moving Observer Method
(East African Journal of Interdisciplinary Studies, 2024-08-25) Okiza,Humphrey; Muhwezi, Lawrence; Omwonylee, Okello Joseph; Awichi, Richard Opaka; Nuwagaba, Savannah
The purpose of the study was to investigate the variables affecting traffic flow in Kampala Central Business District (CBD), employing a quantitative approach. The rapid urbanization has led to a huge increase in the number of vehicles, resulting in traffic congestions, delays, and financial losses especially in the Kampala CBD area. Data on traffic density, speeds, and driver behaviors were collected for a period of 20 days from five selected road sections leading into and out of the city which included traffic on Entebbe Road, Jinja road, Sir Apollo Kaggwa Road, Yusuf Lule and Wandegeya roads using the moving observer method. Regression analysis was done to identify the relationships between the variables, leading to the development of a predictive model for traffic flow. The study found out that the flow tends to increase as the day progresses and as well flow rate increases with increase in density. As the week progressed, the flow rate decreased as number of people coming to town on weekends is low since there is no work. A mathematical model was generated which could be used to predict the traffic intensity on the road at a given day and time. The model shows that changing from weekdays to weekend, the flow decreases by about 29%, and as density increases by 1%, the flow also increases by 1.5% over time. The study recommends prioritizing public transportation improvement, establishment of out of city parking yards, utilizing the other various means of transport other than road and promoting non-motorized modes of transportation in order to reduce traffic density on the road and subsequently manage congestion.