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Assessment On The Level Of Financial Providers Access Strategy On Farmers Economic Empowerment Among Small Scale Tea Farmers In Kisii County- Kenya
No full textFull textEconomic empowerment remains an important goal for any Government. Agriculture is a major
source of income for Kenyans. Various agencies have carried many interventions to ease
financial accessibility. The study used a sample of 398 tea farmers in Kisii to investigate their
economic empowerment in focus areas of enhancing the Service levels of Financial Access. The
study adopted a descriptive research design and the findings were presented in descriptive and
inferential statistics. Findings showed that there was significant positive relationship between the
financial service providers’ accessibility strategies and economic empowerment. Conclusion was
that enhanced level of access to financial service providers is vital for economic empowerment
of the farmers. The study recommends that financial institutions should develop financial
products that are relevant to the needs of tea farmers to increase their finances. The state and
non-state actors should sustain their FA interventions for yielding significant contribution to
economic empowerment
INTRODUCTION TO FINANCIAL ACCOUNTING 1
No full textKABARAK UNIVERSITY EXAMINATIONS
FOR THE DEGREE OF BACHELOR OF COMMERCE
COURSE CODE: ACCT 110
COURSE TITLE: INTRODUCTION TO FINANCIAL ACCOUNTING 1
Time Allowed: 2 Hours
Instructions:
Answer ALL Questions
Show all your Workings
Be nea
An Assessment of Suitable and Affordable Smart armband for preeclampsia Management in Antenatal Care
No full textFULL TEXTBlood pressure is one of the measurements that is taken during antenatal care visits. Though motherhood is a fulfilling experience in the society, it is connected to ill-health and even death in some women leading to maternal morbidity and mortality due to preeclampsia syndromes. United Nations’ Sustainable Development Goal 3 aims to reduce global maternal mortality ratio to less than 70 per 100,000 live births. Therefore, this study sought to assess the suitability and affordability of smart armbands for preeclampsia management in antenatal care. An exploratory design was adopted in the study to assess the suitability and affordability of the device in antenatal care to ensure real time monitoring. Twelve categories were used in assessment to select the most suitable smart armband. It was found out that F1 smart armband was suitable and affordable. The study has shown great potential for actual adoption in health care systems in developing countrie
MODEL FOR IMPROVING PERFORMANCE OF NETWORK INTRUSION DETECTION BASED ON MACHINE LEARNING TECHNIQUES
No full textFULL TEXTDigital crimes have increased in number and sophistication affecting the networks quality of services parameters like confidentiality, integrity and availability of resources. Network Intrusion Detection Systems (NIDS) are deployed to optimize detection and provide comprehensive view of intrusion activities. However, NIDSs generates large volumes of alerts mixed with false positives, and repeated warnings for the same attack, or alert notifications from erroneous activity. This prevents Security Analyst in evaluating the severity of each attack and selecting suitable response plan to prevent information and resources‘ loss in the network at the right time. To achieve high accuracy while lowering false alarm rates there are major challenges in designing an intrusion detection system. To address this issue, this work proposes a three-level model for network Intrusion detection that offers multiple types of correlations. In the first level, several feature selection techniques are integrated to find the best set of features used in this work. The existing feature selection techniques includes Correlation Feature Selection (CFS) based evaluator with Best-first searching method, Information Gain (IG) based Attributes Evaluator with ranker searching method, and Chi square and ranker searching method. The second level enhances the structural based alert correlation model to improve the quality of alerts and detection capability by grouping alerts with common attributes based on unsupervised learning techniques. This work compares four unsupervised learning algorithms namely Selforganizing maps (SOM), K-means, Expectation and Maximization (EM) and Fuzzy C-means (FCM) to select the best cluster algorithm based on Clustering Accuracy Rate (CAR), Clustering Error (CE) and processing time. Then an anomaly classification module is designed in the third level based on fusion of five heterogeneous classifiers Support Vector Machine (SVM), Instance based Learners (IBL), Random Forest, J48, and Bayes Net using Voting as a Multi-Classifier. Network Intrusion Detection model based on hybridizing machine learning techniques (feature selection, enhanced structural and enhanced causal) is implemented on WEKA platform. This research is executed through a series of experiments and testing to achieve the goal of the research. The controlled experiment is preferred as the main method due to certain characteristics, such as performance measures, dataset evaluations and the usability of the results. The NSL KDD and UNSW-NB15 dataset are evaluated based on five measures, detection accuracy, False Positive Rate (FPR), Precision, Total Accuracy (TA), and F– Measures (FM). The results of the proposed model are compared with recent alert correlation models. The overall detection rate is 99.9%, false error rate 0.1% and execution rate of 1340.7 seconds. This shows that HAC is effective and practical in providing complete correlation even on high dimensionality, large scaled and low-quality dataset used in intrusion detection system
COHESION IN THE WRITTEN ENGLISH TEXTS OF HEARING IMPAIRED LEARNERS IN SELECTED HIGH SCHOOLS FOR THE DEAF IN KENYA
No full textoai:ir.kabarak.ac.ke:123456789/292FULL TEXTPrevious studies reveal that the hearing impaired learners face several challenges in their written English. These challenges affect their communication, which is likely to affect their education and career aspirations. This study investigated the use of cohesion in hearing-impaired learners’ English written texts. It investigated ways by which hearingimpaired learners in Form Three have been able to achieve cohesion in their written texts as well as the errors related to the use of cohesion. The study was guided by the following objectives: identify the grammatical and lexical features that the hearing-impaired learners use in writing to achieve cohesion; describe the grammatical and lexical features that the hearing-impaired learners use in writing to achieve cohesion; determine the types of cohesion that are prominent in the writing of hearing-impaired learners; analyze the errors in the use of cohesive devices in the hearing-impaired learners’ written texts; and investigate the grammatical errors related to use of cohesive devices in the written texts of hearing-impaired learners. The study is significant because it embraces the means by which hearing-impaired written texts are linguistically and logically connected. The study confined its investigation to the use of cohesion in the hearing-impaired learners’ English written texts. The data for the study was collected from the written texts of Form Three hearing impaired students sampled from three secondary schools located in Nyeri County, Nakuru County, and Machakos County. The written texts were picked from written assignments from different subjects as well as from one free composition. The data from the class assignment captured normal English writing situation. The study was guided by Halliday and Hasan’s theory of Cohesion to identify, describe and categorize cohesive devices in the texts. Corder’s Error Analysis theory guided the research in identifying and categorizing the errors made by the hearing impaired learners in an attempt to write cohesively, while Selinker’s Interlanguage theory was used to explain the learners’ interlanguage and causes of the errors. The researcher found out that all the cohesive devices posited by Halliday and Hasan were present, but at varying frequency. In grammatical cohesion, reference had the highest frequency of occurrence and ellipsis the least. In lexical cohesion, reiteration was higher than collocation. The researcher also found out that the hearing-impaired learners had challenges in writing cohesively. There were several errors related to the use of cohesive devices as well as grammatical errors. The study concluded that the hearing impaired learners use cohesive devices though with challenges. It recommended further research in the writing of the hearing impaired and that teachers give a lot of emphasis in the teaching of parts of speech and grammatical categories. The findings of this study provide a theory-governed description of cohesive ties used by the hearing impaired learners in Kenya. The findings also contribute to the increasing body of knowledge in studies related to the writing and communication of deaf learners. The study is useful to teachers, researchers, the Kenya Institute of Curriculum Development and the Ministry of Education in the formulation of future educational policies regarding the education of the hearing-impaired learners in Kenya
Structural Properties of Photocatalytic Copper Pigmented Anodized titanium
No full textFull textThe performance of TiO2photocatalyst depends on its surface morphology andthe orientation of
its crystal structure. In this study, commercial pure grade 1 titanium substrate was anodized at
200V for different anodization times, pigmented and annealed for a period of 4500C for 4 hours.
Structural properties of the samples was done using AFM, XRD and SEM. Prolonging
anodization time engineered the formation of pores and eventual pore merging on the surface of
the TiO2 film thereby significantly influencing the surface morphology and crystallinity of the
sample.The XRD measurements confirmed the coexistence of both rutile and anatase phases
inthe samples
The Mediating Influence of Bixa Ollerana Value Chain Government Policy on the Relationship between Product Strategy and sales performance
No full textThe main aim of this study was to assess the Mediating Influence of Bixa Ollerana Value Chain Government Policy on the
Relationship between Product Strategy and sales performance. The study is based on the following theories; ResourceBased
Theory, Competency Theory, and Distribution Channel Theory. The study adopted descriptive and exploratory
research design mixed method approaches. The target population of the study was 2,419 Bixa farmers registered by the
Ministry of Agriculture in Kwale County. A sample size of 106 farmers was drawn using simple random sampling
technique. The study used structured questionnaire to collect the required data from the respondents. The study used
descriptive statistics such as means, standard deviation and percentages and inferential statistics using Regression
Analysis. The study established that product strategy influenced the sales performance of small scale Bixa Ollerana
farmers in Kwale County, Kenya. The interaction of the moderating effect of Government policy on Bixa Ollerana value
chain did not change the relationship between product strategy and sales performance of small scale Bixa Ollerana
farmers. The findings from the study will be of importance to practice, marketing scholarship and Ministries of Industry,
Trade and Cooperatives and Agriculture on Policy formulation for local and international marketing of Bixa Ollerana
products. The study recommends that the Government of Kenya puts in place a policy framework now that Bixa Ollerana
is a scheduled crop, to regulate and promote its production, processing and marketing. Small scale Bixa Ollerana farmers
and marketers have knowledge from this study which is useful for the design and implementation of effective marketing
strategies to increase sales performance
Artificial Neural Network Power Demand Forecasting Model for Energy Management a Case Study of Kabarak University.
No full textFull textWorld governments face challenges of increasing rate of power consumption and energy
insecurity. There is need for countries to increase supply sustainability by reduction of
demand through energy efficient investments. Load forecasting is important in electric
power industry. It provides future load demand information necessary for improving
decision making thus enhancing reduction of power demand. Currently many world
organizations depend on technical expert’s knowledge and experience to assess, evaluate
and advice on energy conservation and efficiency status. These methods suffer from
inaccuracies and biasness leading to uncertainty in power generation, supply and high costs
of energy. The current adoption and advancement of information technology, application of
machines learning and artificial intelligence techniques will provide unbiased and more
accurate information on energy efficiency status. The research study developed an Artificial
Neural Networks Based Power Demand Forecasting Model for Energy Management
(ANNPDFMEM). A Multi-Layer Feed Forward Neural Networks structure was used. The
electricity load data was collected from the Kenya Power and Lighting company (KPLC)
smart meters for Kabarak University in Nakuru County. The collected data set was divided
into 70% training set, 15% validation set and 15% testing set. The model was trained using
the Back-Propagation learning algorithm. The smallest Mean Square Error in the training
iteration is selected and validated with independent set of test samples. Actual smart meter
load data from KPLC was compared against the predicted load. The performance
evaluation of the model was done to predict the actual load values. The results obtained a
Mean Squared Error (MSE) of 9.5%, and R value of 1. The results indicated high accuracy
forming the basis for recommendation for adoption of the (ANNPDFMEM) as a tool for
future power demand information. This information platform is important for decision
making on energy efficiency and conservation strategies for sustainability and energy
management
The factors impeding Clean Development Mechanism (CDM) implementation and carbon emissions reductions and energy management in relation to climate change and sustainable development in Africa.
No full textFULL TEXTThe paper focuses on experimentally researched information on factors that are an impediment to
the implementation of clean development mechanism, the effects and solutions on carbon
emissions reduction and energy management initiatives for sustainable development in relation
to climate change in Africa. The objectives are to identify some countries in Africa where
experimental studies have been done on factors which hinter implementation of CDM and the
research methods, results, findings obtained and application in providing solutions on the way
forward for implementation of CDM in Africa., to highlight the impacts of the failure and or
success to implement the clean development mechanism on carbon emissions reductions and
energy management in relation to climate change and sustainable development in Africa and to
suggest solutions that can be used to accelerate the implementation of CDM in Africa. The
methods used to collect data in both Kenya and Burkina Faso studies were questionnaires,
interviews and workshops, whereas SPSS computer package method was used to analyze the
data. CDM is a tool provided by Kyoto Protocol in 1997 established by United Nations
Framework convention on Climate Change, that ensures all parties (developed & Developing
Countries) of the Protocol benefit from the project activities designed to reduction of greenhouse
gases in to the earth’s atmosphere. The findings of the studies done in Kenya, and Burkina Faso
show the following factors to be hindering implementation of CDM:- policy barriers, project
financing gaps, institutional barriers and gaps, lack of information and knowledge on CDM,
government bureaucracy, corruption, limited resources and insecurity due to terrorism attacks.
The solutions proposed for Burkina Faso and Kenya are given as- introduce efficient
carbonization techniques, enhance community participation, create a black and white lists for
approving CDM projects, promote in-country expert capacity building in CDM projects and
provide tax incentives to CDM investors.1. National Research Fund
2. Sentimental Energy Lt
Influence Of Strategic Innovation On Revenue Streams Sources Of Public Universities In Kenya
No full textFull textIn spite of rapid increase of number of public universities in Kenya from 5 to 31 in the last two
decades, in the last three years the number of qualifying fresh undergraduate students has
significantly decreased – yet traditional this is what has been the cash cow for these institutions.
These public universities have been relying on capitation fund for government placement
admissions which has been largely augmented with own source revenue from self-sponsored
programmes or privately placed admissions. With the slinking numbers of qualifying admissible
students many public universities are reporting alarming revenue shortfalls and operational
deficits. This precarious scenario has necessitated need for strategic innovations on own source
revenue streams. The study therefore evaluated the influence of strategic innovations on revenue
streams sources of public universities in Kenya. It was assessed the influence of technological
innovation, and diversification innovation on revenue streams sources of selected public
universities. It was based on descriptive research design using a cross-sectional survey with
quantitative and qualitative data collected using questionnaires. Data was analyzed using
descriptive and inferential statistics. A multiple linear regression model was used to present the
relationship between the independent variables and the dependent variable. From the analysis the
conclusion was that there is a positive relationship between the independent variables technology
innovation and diversification innovation on the dependent variable revenue stream sources in
the selected public universities in Kenya (p <0.05). The researcher recommends that there is the
need for university management to adopt strategic innovations in order to achieve new revenue
stream sources of their institutions and their long time survival