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AFRICAN ORAL LITERATURE: ANALYSIS OF VISUAL RESOURCES AND IMPROVISED TECHNIQUES IN SELECTED BUKUSU CIRCUMCISION SONGS
No full textTHESIS SUBMITTED TO THE SCHOOL OF EDUCATION AND SOCIAL SCIENCES IN PARTIAL FULFILMENT OF THE REQUIREMENT FOR THE DEGREE OF MASTER OF ARTS IN LITERATURE OF KARATINA UNIVERSITYThe study is an analysis of visual resources and improvised techniques in the actualization of the Bukusu circumcision songs. The study examines the roles, social cultural values and dynamisms of visual resources and improvised techniques in actualizing Bukusu circumcision songs. Visual resources and improvised techniques in the Bukusu circumcision songs are likely to vanish due to social and cultural chamges. The purpose of this study was to determine the specifics impact of these valuable components in Bukusu circumcision songs. The study's objectives examined the role of improvised techniques and visual resources in actualizing Bukusu circumcision songs, analyze the social-cultural values attached to them and evaluate their dynamic nature. There are scanty and generally analysed literary studies on Bukusu oral literature; this study intends to fill the gap by focusing on visual resources and improvised techniques integral to the Bukusu circumcision songs. The research was conducted among the Bukusu sub-community of Luhya community in Kimilili- Sub County, Bungoma County with a sample size of 220 respondents. The study employed Performance Theory because it was a performance-cantered approach and more adequate for analysing visual resources and improvised techniques employed in Bukusu circumcision songs more effectively. The study relied on mixed methods research designs. The primary and secondary sources were exploited in data collection. Data analysis was done using Statistical Package of Social Sciences then subjected to the rating scale. Regarding study objective number one, the study found that visual resources and improvised techniques played a role actualising Bukusu circumcision songs. The study's second objective found that social-cultural values are attached to visual resources and improvised techniques in Bukusu circumcision songs. In analysing the dynamism of visual resources and improvised techniques in Bukusu circumcision songs, this study found that that education and theme change in BCS impacted visual resources and improvised techniques. The researcher demonstrated that visual resources and improvised techniques components exhibited during the actualization of Bukusu circumcision songs are integral parts of Bukusu circumcision songs, without which the songs are deemed incomplete. This work will be critical to scholars in various institutions where subjects including music, dance, and creative sculptures are fields of interest to societies. Based on the objective of study, the researcher recommends that the roles of visual resources and improvised techniques in Bukusu circumcision songs cannot be ignored; there is a need for the government of Kenya and other cultural stakeholders to appreciate these components and initiate programs that promotes traditional circumcision songs as a source of tourist attraction activities in Kenya
An Enhanced Data Transmission in Mobile Banking Using LSB-AES Algorithm.
No full textEnhanced Data Transmission in Mobile Banking Usin
Analysis of Short-Term Drought Episodes Using Sentinel-3 SLSTR Data under a Semi-Arid Climate in Lower Eastern Kenya.
No full textAnalysis of Short-Term Drought Episodes Using
Sentinel-3 SLSTR Data under a Semi-Arid ClimateThis study uses Sentinel-3 SLSTR data to analyze short-term drought events between
2019 and 2021. It investigates the crucial role of vegetation cover, land surface temperature, and
water vapor amount associated with drought over Kenya’s lower eastern counties. Therefore, three
essential climate variables (ECVs) of interest were derived, namely Land Surface Temperature (LST),
Fractional Vegetation Cover (FVC), and Total Column Water Vapor (TCWV). These features were
analyzed for four counties between the wettest and driest episodes in 2019 and 2021. The study
showed that Makueni and Taita Taveta counties had the highest density of FVC values (60–80%)
in April 2019 and 2021. Machakos and Kitui counties had the lowest FVC estimates of 0% to 20%
in September for both periods and between 40% and 60% during wet seasons. As FVC is a crucial
land parameter for sequestering carbon and detecting soil moisture and vegetation density losses,
its variation is strongly related to drought magnitude. The land surface temperature has drastically
changed over time, with Kitui and Taita Taveta counties having the highest estimates above 20 ◦C in
2019. A significant spatial variation of TCWV was observed across different counties, with values
less than 26 mm in Machakos county during the dry season of 2019, while Kitui and Taita Taveta
counties had the highest estimates, greater than 36 mm during the wet season in 2021. Land surface
temperature variation is negatively proportional to vegetation density and soil moisture content, as
non-vegetated areas are expected to have lower moisture content. Overall, Sentinel-3 SLSTR products
provide an efficient and promising data source for short-term drought monitoring, especially in
cases where in situ measurement data are scarce. ECVs-produced maps will assist decision-makers
with a better understanding of short-term drought events as well as soil moisture loss episodes that
influence agriculture under arid and semi-arid climates. Furthermore, Sentinel-3 data can be used to
interpret hydrological, ecological, and environmental changes and their implications under different
environmental conditions
Investigation of noradrenergic receptor system in anti-nociception using formalin test in the naked mole rat (Heterocephalus glaber).
No full textABSTRACTThe naked mole rat (NMR) is a rodent that has gained importance as a biomedical research model for various conditions like hypoxic brain injury, cancer and nociception. This study was designed to investigate possible involvement of the noadrenergic receptor system in antinoception in the NMR, using the alpha-2 adrenergic receptor specific ligands clonidine (agonist) and yohimbine (antagonist) in the formalin test. Formalin test followed 30 min after intraperitoneal administration of ligands or control. A total of 96 naked mole rats were used. A significant reduction in nociceptive behaviours was demonstrated after administration of clonidine in the doses 1,3,10 and 30 μg/kg (n = 8 per group). Doses of clonidine above 30 μg/kg caused loss of motor and proprietion skills exhibited by prostration and failure to turn over when placed on their backs. The antinociception by 3 μg/kg clonidine was reversed by administration of 30 μg/kg of yohimbine. The present study demonstrates that the noradrenergic receptor system is present and involved in formalin test-related antinociceptive mechanisms in the NMR, similar to other mammals. Given the increasing importance of the NMR as a model for pain and nociception, the species may prove useful as an animal model for noradrenergic mechanisms in pain modulation
The Influence of Technology Enabled Service Differentiation Strategy on Post-Pandemic Reopening Performance of Star-Rated Hotels in The South Rift Circuit
No full textPost-Pandemic Reopening Performance of Star-Rated Hotels in The South Rift Circuit.One of the most competitive industries in Kenya and the entire continent of Africa is the hotel industry, which contributes significantly to the country's economy. As a result, the sector is a significant source of foreign exchange, employment, and revenue for the nation. However, the emergence of the Covid-19 global pandemic has had a significant impact on the hotel industry in the country as elsewhere globally with travel restrictions, social distance requirements, and low visitor turnout affecting their operations. The researcher sought to examine the influence of technology enabled service differentiation strategy on reopening performance of the hotel industry in Kenya in the post-pandemic context. Marketing Mix Theory guided the study. The study adopted expressive cross sectional survey research design and targeted 47 star rated hotels, lodges, camps and as well as guest houses in the South Rift Circuit, that is, Nakuru and Narok counties using a census. Data was collected through questionnaires from the marketing managers of the hotels. Qualitative data was analyzed through thematic and content analysis using Nvivo while quantitative data was coded and analyzed through SPSS computer software version 24.0 using both descriptive and inferential statistics. The outcome revealed that technology enabled strategy affecting post-pandemic reopening performance of star-rated hotels in the South Rift Circuit, Kenya is significant. Therefore, the study recommends that the hotels should make provision for continuous training of staff on modern technologies. The hotels’ management need to provide tailored services to individuals and group clients as need arises. The hotels need to diversify their markets to ensure that they are able to tap into more potential markets locally and internationally. Finally, the hotels need to emphasize on market growth strategies
Identification of Maize leaf diseases based on Support Vector Macina and Convolutional Neural Networks Alex Net and ResNet
No full textThesis AbstractProtecting maize crops from devastating plant diseases ensures global food security. Accurate
disease identification is essential for implementing effective control measures. However,
traditional visual analysis of symptomatic leaves used by maize farmers in Kenya is time
consuming, costly, subjective and prone to errors. Embracing computer vision technologies, such
as deep learning and machine learning, offers promising solutions to these challenges, enhancing
crop productivity. The general objective of this study was to develop models for maize lethal
necrosis (MLN) disease, maize streak disease (MSD) and Gray leaf spot diseases (GLS) detection
and classification using AlexNet and ResNet 50 convolutional neural networks (CNN)
architectures and machine learning Support Vector Machine (SVM). The specific objectives of this
study were to: identify maize leaf disease (MLN, MSD and GLS) using AlexNet, ResNet-0 and SVM
models, to evaluate the performance of the AlexNet, ResNet-50 and SVM models in the
classification of MLN, MSD and GLS. Digital maize leaf disease images were collected from maize
farms in Embu County, resulting in a dataset of 3200 images, with 800 images for each disease
category. The results indicate that AlexNet and ResNet50 achieved high accuracy in identifying
maize leaf diseases, recording average accuracies of 98.3% and 96.6%, respectively. In contrast,
the SVM model exhibited the lowest average accuracy of 85.5%. AlexNet demonstrated
exceptional accuracy in classifying Maize Streak Virus (MSV) with a rate of 99.85%, followed by
ResNet50 at 99.2%. Conversely, SVM had a lower recall value of 81.7% for Grey Leaf Spot disease.
By incorporating these advanced models, farmers and stakeholders in maize crop protection can
identify diseases early, allowing for timely interventions and improved disease management
strategies. Consequently, this will lead to increased maize productivity and enhanced crop
quality. Early disease detection also facilitates the judicious use of pesticides, safeguarding the
environment and human health. The findings underscore the importance of leveraging these
technologies to enhance food security, optimize agricultural practices, and promote sustainable
maize production
