http://ir.mksu.ac.ke/handle/123456780/70 Scholarly output of the School of Engineering and Technology Sun, 17 May 2026 14:01:55 GMT 2026-05-17T14:01:55Z http://ir.mksu.ac.ke/handle/123456780/21182 Economic Load Dispatch on a 132 kV Line with Service Potential Transformer Substations: A Case Study of Juja-Rabai Line Kitheka, Joel; Moses, Peter; Nyete, Abraham; Abungu, Nicodemus Power outages have created significant challenges for power system networks, particularly in developing countries where the electricity demand continues to rise without a corresponding increase in power generation or the expansion of transmission and distribution networks. In Kenya, while there is a well-established transmission line network, the distribution infrastructure remains inadequate for supplying electricity to end consumers. This paper examines the economic load dispatch (ELD) of power system networks utilizing Service Potential Transformer (SPT) substations to provide electricity to villages located near high voltage (HV) lines. The ELD analysis was conducted to identify the optimal economic power output from the Kipevu, Rabai, and Thika thermal power plants, addressing the demand for both conventional and non-conventional substations. A gradient method was employed to calculate the ELD for these three generating units, and the results were validated using the PowerWorld simulator. Findings indicated that the three generators supplied 20 MW, 37.5 MW, and 12.5 MW, respectively. The results obtained from the gradient method are consistent with those obtained from PowerWorld software. Additionally, this study projected an annual fuel cost savings of USD 17,695.20 when ELD was implemented, compared to a scenario of equal load distribution among generating units. Over a ten-year period, these savings would be sufficient to establish a conventional distribution substation to meet the power demands of villages located further away from high voltage lines. Sun, 01 Sep 2024 00:00:00 GMT http://ir.mksu.ac.ke/handle/123456780/21182 2024-09-01T00:00:00Z http://ir.mksu.ac.ke/handle/123456780/21181 Modeling Zika Virus Disease Dynamics with Control Strategies Helikumi, Mlyashimbi; Lolika, Paride; Makau, Kimulu; Ndambuki, Muli; Mhlanga, Adquate In this research, we formulated a fractional-order model for the transmission dynamics of Zika virus, incorporating three control strategies: health education campaigns, the use of insecticides, and preventive measures. We conducted a theoretical analysis of the model, obtaining the disease-free equilibrium and the basic reproduction number, and analyzing the existence and uniqueness of the model. Additionally, we performed model parameter estimation using real data on Zika virus cases reported in Colombia. We found that the fractional-order model provided a better fit to the real data compared to the classical integer-order model. A sensitivity analysis of the basic reproduction number was conducted using computed partial rank correlation coefficients to assess the impact of each parameter on Zika virus transmission. Furthermore, we performed numerical simulations to determine the effect of memory on the spread of Zika virus. The simulation results showed that the order of derivatives significantly impacts the dynamics of the disease. We also assessed the effect of the control strategies through simulations, concluding that the proposed interventions have the potential to significantly reduce the spread of Zika virus in the population. Fri, 01 Nov 2024 00:00:00 GMT http://ir.mksu.ac.ke/handle/123456780/21181 2024-11-01T00:00:00Z http://ir.mksu.ac.ke/handle/123456780/19892 Sentiment analysis on social media tweets using dimensionality reduction and natural language processing Omuya, Erick Odhiambo; Okeyo, George; Kimwele, Michael Social media has been embraced by different people as a convenient and official medium of communication. People write or share messages and attach images and videos on Twitter, Facebook and other social media platforms. It therefore generates a lot of data that is rich in sentiments. Sentiment analysis has been used to determine the opinions of clients, for instance, relating to a particular product or company. Lexicon and machine learning approaches are the strategies that have been used to analyze these sentiments. The performance of sentiment analysis is, however, distorted by noise, the curse of dimensionality, the data domains and the size of data used for training and testing. This article aims at developing a model for sentiment analysis of social media data in which dimensionality reduction and natural language processing with part of speech tagging are incorporated. The model is tested using Naïve Bayes, support vector machine, and K-nearest neighbor algorithms, and its performance compared with that of two other sentiment analysis models. Experimental results show that the model improves sentiment analysis performance using machine learning techniques. Thu, 01 Sep 2022 00:00:00 GMT http://ir.mksu.ac.ke/handle/123456780/19892 2022-09-01T00:00:00Z http://ir.mksu.ac.ke/handle/123456780/15807 An Appraisal on the Potential uses of Bentonite and its Availability and Exploitation in Kenya Mutisya, Peter K.; Maranga, SM; Ikua, Bernard W — Bentonite is a smectite clay formed from the alteration of siliceous, glass-rich volcanic rocks such as tuffs and ash deposits. The major mineral in bentonite is montmorillonite, which is a hydrated sodium, calcium, magnesium or aluminum silicate, or a combination of these. The industrial bentonites are generally either the sodium or calcium variety. Bentonites are important and essential in a wide range of applications including well drilling, foundry sand binding, iron ore pelletizing, pet waste absorbents, and civil engineering uses such as waterproofing and sealing. In many developing countries, local bentonite producers provide the livelihood for many marginalized workers. This paper presents the many economic uses to which bentonite can be put. In addition, the paper gives highlight on the numerous opportunities for investment in which bentonite is key. Special focus is given on the use of bentonite in deep drilling and foundry which together use the largest quantity of bentonite in the world. Wed, 01 Jun 2022 00:00:00 GMT http://ir.mksu.ac.ke/handle/123456780/15807 2022-06-01T00:00:00Z