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Children with Disabilities in Kenyan Media: Lessons from the Abled Differently Programme
No full textThe chapter explores how the national broadcaster Kenya Broadcasting Corporation Television (KBC TV), through its premier programme, Abled Differently, represents children with disabilities. Using media representation theory and a mixed methods design that incorporated both quantitative and qualitative approaches, they find that while KBC TV tended to produce content for persons with disabilities that involved collaboration and dialogue with various disability stakeholders, there was insufficient coverage of content related to children with disabilities in educational contexts. They conclude with several recommendations for improving the representation of children with disabilities on television, including portraying them in inclusive learning environments and protecting their identities to avoid stigmatization and victimization. Because Abled Differently is the only disability-specific programme in Kenya, they further recommend that more disability-specific programmes featuring children with disabilities be produced by other media organizations in Kenya as well
Speech by Prof. Joachim Osur, Acting Chancellor, Murang'a University of Technology, on the occasion of the 6th graduation ceremony held on Tuesday, 29th November 2022 at the graduation ground.
No full textSustainable Adaptation
No full textSustainable-adaptation is defined as adaptation measures and strategies aimed to reduce vulnerability and enhance resilience of an individual, society or system without compromising social justice and environmental integrity (Njoroge 2014; Brown, 2011; Ericksen et al., 2011). Climate change remains one of the most challenging phenomena facing humanity in the 21st century. Climate sensitive industries, including tourism, are not only already affected but will continue to feel the impact of climate change. In order to cope from extreme eventualities of climate change, adaptation and mitigation strategies have been proposed and are already being implemented in some tourism destinations. Climate change has been advanced to cover these five knowledge domains: Destination adaptation, Consumer adaptation, Adaptation policy, Business adaptation and Frameworks and Policy. Not all adaptation strategies are good. An adaptation at one area or level in the complex tourism system would lead to maladaptation in another part of the tourism system. This has created keen interest in advancing knowledge on ‘the good adaptation’ hence the word sustainable-adaptation has been coined.
Sustainability research has placed emphasis on climate change, modelling, values, behaviour and theoretical progression according to the Butland review (Ruhanen et al 2019). Tourism is both a vector and a victim of climate change. Climate change has been linked to sea level rise, extreme events, biodiversity loss, and water stress among other direct and indirect impacts that pos
Comparative Analysis of Machine Learning Algorithms Accuracy for Maize Leaf Disease Identification
No full textThe number of data points predicted correctly out of the total data points is known as accuracy in image classification models. Assessment of the accuracy is very important since it compares the correct images to the ones that have been classified by the image classification models. Image classification accuracy is a challenge since image classification models classify images to the class they don’t belong to hence there is an inaccurate relationship between the predicted class and the actual class which results in a low model accuracy score. Therefore, there is a need for a model that can classify the images with the highest accuracy. The paper presents image classification models together with the feature extraction methods used to classify maize disease images. The researcher used an augmented maize leaf disease dataset obtained from the Kaggle website. Features are extracted from maize disease images and passed to the machine learning classification algorithm to identify the possible disease based on the features detected using the feature extraction method. The maize disease images used include images of common rust, leaf spot, and northern leaf blight and healthy images. An evaluation was done for the feature extraction methods and the outcomes revealed Histogram of Oriented Gradients performed best with classifiers compared to KAZE and Oriented FAST and rotated BRIEF. The experimental outcome also indicated that the Artificial Neural Network model had the highest accuracy of 0.82 compared to Logistic Regression, K-Nearest Neighbors, Random Forest, Linear Support Vector Classifier, Decision Tree, and Support Vector Machine
Effects of Lysinibacillus sphaericus on Physicomechanical and Chemical Performance of OPC Blended with Natural Tuff and Pulverized Fly Ash
No full textThis paper reports study findings on the use of Lysinibacillus sphaericus (at 1.0 × 107 cells/ml concentration) to enhance and improve the physicomechanical and chemical properties of blended Ordinary Portland Cement (OPC). Blending was done separately with pulverized fly ash (PFA) and natural pozzolana (volcanic tuff) at substitution levels of 10%, 20%, 30%, 40%, 50%, 60%, and 70%. Mortar prisms of dimensions 40 mm by 40 mm by 160 mm were prepared and cured for the 2nd, 7th, 28th, 56th, and 90th days using Lysinibacillus sphaericus solution as mixing water and curing media. Commercial OPC and PPC mortar prisms cast and cured using distilled water were used as controls. Results showed that prisms treated with bacteria exhibited the highest performance on compressive strength development. Further microstructure analysis of blended cement incorporated with Lysinibacillus sphaericus bacteria showed significant amounts of reacted secondary cementitious materials compared to samples without bacteria. Bacteria presence was also found to reduce water demand during mixing and setting times and exhibited low porosity in relation to samples without bacteria. These results showed that the presence of alkaliphilic bacteria in the blended cement resulted in synergistic effect in enhancing the physicochemical and mechanical properties
Parental Career Support as a Correlate of Career Decision Making Among Secondary Students in Muranga County, Kenya
No full textThe ability to decide on a career is an important decision made by students while at secondary school level, the choice determining future engagement in the world of work. Studies in Kenya have identified fewer secondary school students selecting viable career options in science and technology, with many choosing careers that are saturated or not in the job market. Parents have been found to be influential in students career choices and subsequently many related factors have been explored, such as parental participation, profession, social status, and level of education. However, there is inadequate documented information on studies done in Muranga County on specific parental support aspects as proposed by the Social Cognitive Career Theory (SCCT). The study therefore aimed to investigate the relationships among parental career support and students’ career decision making among students in public secondary schools. A correlational research design was used to establish the relationship among the variables. Form three students in public secondary schools in Murang’a County, formed the target population. Cochran’s sample size formula was utilized to compute the sample size of 498 students. Purposive sampling and proportionate stratified random sampling determined 11 schools which included boys, girls and mixed schools. Random sampling was used to select the participants. Quantitative data was collected using a questionnaire comprising of the Career Related Parent Support Scale (CRPSS), and the Career Decision Scale (CDS). Data gathered was coded and analyzed using SPSS. Pearson’s correlation coefficient, Analysis of variance and multiple regression analyzed the inferential data. The findings established significant positive correlations among the parent career support factors, Instrumental assistance (r(488)=0.29, p< .01), Emotional support (r(488)=0.34, p<.01)), with career decision making . The study recommended provision of the parental support factors in guiding students’ occupational choices
Facile Removal of Phenol from Aqueous Solution Using Modulated Cornstarch Impregnated With Triethanolamine as Adsorbent: Sorption Isotherms and Kinetics
No full textBackground: The sources of phenolics pollutants in water are mainly pharmaceutical and chemical industries. The compounds are carcinogenic, cytotoxic, mutagenic and teratogenic even at modest concentrations. These health effects are unrectifiable and it is prudent to remove phenols from water to overcome them. Despite substantial achievements on modern methods for removal of phenol from aqueous media, there is need to search for bio-adsorbent which is non-toxic, ecofriendly, cost-effective and efficient. This study reports on the modulation of cornstarch by chlorination followed by amination using triethanolamine, to be used as adsorbent.
Materials and Methods: Starch was derived from corn (maize) enriched flour purchased from Mukuyu and Maragua in Murang’a County, Kenya. All solutions were prepared using double deionized water obtained from Kenyatta University (K.U) Chemistry Laboratory. Reagents and chemicals used were of analytical grade (AR). Characterization of raw and modulated cornstarch, was done using Fourier Transform Infrared (FTIR) spectrophotometer. The modulated cornstarch was used in the removal batch experiments (optimization of adsorption parameters) on model solutions. The efficiency of modified cornstarch in phenol removal at different pH levels (pH3.0-10), contact time (5-120 minutes), initial phenolics concentration (5-40ppm) and bioadsorbent dosage (0.1-1.2g) of aminated cornstarch (ACS) in aqueous mediaat laboratory temperature (25±10C) were investigated.
Results: The results showed that the maximum uptake of phenol was realized at equilibrium contact time of 10 mins, pH of 5.0. The uptake of phenol increased with increase in dosage of ACS and initial concentration of phenol. The maximum uptake of phenol occurred at initial concentration of 10ppm and then plateaued. In kinetic models, the adsorption mechanism of phenol was best described by the pseudo – second order (K2) kinetic model with R2=0.9978. The batch experimental data obtained best fitted into the Langmuir isotherm with regression coefficientR2=0.999839and monolayer adsorption capacities of 4.2977mg/g for phenol. Conclusion: These adsorption capacities were relatively higher than reported processes, indicating that aminated cornstarch (ACS) is an effective adsorbent for removal of phenol from aqueous media. The findings from this study will provide remedy to water treatment using effective ecofriendly adsorbent and recycling of wastewater for reuse
Career Development and Employee Value Proposition People Management Future
No full textCareer development has gained a lot of interest over time as organizations and employees attempt to match individual goals with organizational goals to maximize performance. Value proposition, in human resource management focuses on the value that organizations and employees place on their worth, thereby the future of work for both. This chapter reviewed existing literature and linked the relationship between the two constructs to inform on their contribution to the future of people management. Global changes have made it necessary for employers and employees to re-examine the world of work and people management. How organizations manage employee careers is strategic in adding value to both the organization and the employees. The methodology employed was to search online and identify literature, review, and analysis were done per construct reviewed literature. Further the link between the career development and employee value proposition was identified. The limitation is that most of the available literature on the two constructs is before the Covid-19 pandemic and does not emphasize the future. The findings are that career though fast changing remains an important motivator for employees as an aspect of the employee value proposition that would impact people’s management futures
Implementation of AI-based assistive technologies for learners with physical disabilities in Kenya: a practical design thinking approach
No full textInclusion of Learners with disabilities continues to extensively rely on digital and Artificial Intelligence (AI) enabled Assistive Technologies (AT) as enablers for teaching and learning. However, the provision of ATs to meet the unique needs of PWDs continues to be a challenge. Moreover, such AI enabled ATs exist within areas of innovations, learning and working environments, hence the need for ease of learning, usage and cost effective acquisition and implementation. This paper introduces a systematic approach that matches the unique needs of PwD learners and abilities of innovators using AI-ATs. The research approach applies Design Thinking (DM), participatory elements enhanced with online collaborative tools. The study was conducted in 3 physically challenged pilot schools and an AT Centre at Meru University of science and technology. The objective of the study was to create better understanding of learners with physical disabilities and innovators with a view of enabling accurate identification, evaluation and choice of appropriate AI-ATs so as to develop learning and innovation spaces that enable the creation, introduction and testing of AI-ATs for e-inclusion. The expected outcome of this research is socio-economic inclusivity for livelihood empowerment as well as de-stigmatization of PwDs
