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Food insecurity, a perceived barrier to healthy eating in the Lake Victoria Region, Kenya: Findings from a qualitative study
No full textConsumption of poor-quality diets was noted as prevalent in the Lake Victoria Region, Kenya. As a strategy to communicate desirable change and promote healthy eating in the region, a 30-member panel of policymakers and implementers developed and proposed 12 food-based dietary guidelines (FBDGs) in 2017-2018. The objective of this study was to assess barriers in adopting the proposed FBDGs amongst community members in the lowlands of Kisumu and Homa Bay counties. Qualitative, descriptive cross-sectional design was used to collect data from 72 focus-group discussions (FGD). The FGD was conducted among 216 school going children (10-13y), 216 high school students (15-18y), 207 adult males (26-74y) and 211 females (18-71y). The participants were asked to state whether the proposed FBDGs reflected their daily dietary practices? If the answer was no, the FGD participants were asked to elaborate on the perceived barriers. Each FGD consisted of 8-12 participants. The demographics of FGD participants were collected before the start of FGD sessions. All FGD proceedings were audio-recorded and transcribed verbatim. Demographic information of participants was analyzed and presented using descriptive statistics. The FGD responses were coded and analyzed based on the main code, the barriers. Barriers to healthy eating in the study area were mainly linked to low production of food, food unavailability and inaccessibility. Specific factors which contributed to the food insecurity situation included; dry and sunny weather, seasonality in food availability, limited resources to secure potential farmland with fences, gender influence on land use, high cost of food, lack of money to purchase food, low income, sale of farm produce with resultant inadequate quantities of food consumed and inappropriate meal composition. Food insecurity was a perceived barrier to healthy eating in the lowlands of the Lake Victoria region. This research suggests the need to address food systems and economic structures to improve food production, distribution, accessibility and consumption in the region. Coding was done with the aid of NVivo8 (QSR International Pty Ltd Version 8, 2008). This study was registered with the Kenyan National Commission for Science Technology and Innovation (NACOSTI/P/18/12634/22291)
Enhanced Deep Learning Model to Detect Anomalies in Surveillance Videos
No full textMaster of Science in Information Technology, 2022Increased security challenges and advancements in technology have led to heavy usage of surveillance cameras. This has resulted in an overwhelming abundance of video data which requires automated analytics for better utilization. The big volume of the video data generated by surveillance devices presents an enormous problem to the security personnel since they must monitor the footage frame by frame to identify the abnormal activities (security threats) like violence, and thuggery, among others. Successful identification of anomalies in surveillance footage will ease the work of Closed-Circuit Television (CCTV) operators greatly since they can search through a big volume of the video data easily. Another importance of this research is the contribution to computer vision since the model can be applied in other areas like robotic surveillance or unmanned surveillance. There have been attempts to automate the surveillance process using smart surveillance. However, these solutions are challenged due to high error rates and inefficiency while identifying abnormal scenes. Modern automated video analytics, use deep learning algorithms like; Convolutional Neural Networks (CNN), Long-Short Term Memory (LSTM), convolutional LSTM and 3DCNN.These approaches have their strengths and weaknesses, and it becomes a research challenge to determine the best model to use in detecting anomalies. Another challenge presented herein is the accuracy of detecting anomalies in surveillance videos. A comparative study was carried out to cross-examine deep learning models used in anomaly detection. Empirical data was collected to measure the accuracy of the deep learning models in anomaly detection. The best model was determined by analyzing the accuracies of the model published since 2016. Experiments were set up in Google Collab and Google Cloud. These environments were configured to use Python 3.7, Keras and TensorFlow machine learning frameworks. The study improved the selected deep learning model through, optimization of the model structure and depth tuning. The study found that deeper autoencoders have high prediction accuracy and deeper spatial autoencoders draws more features from the videos and that increases their accuracy. Validation of the enhanced model was done through further experiments that compared the prediction accuracy acquired from the enhanced model against the existing model set as the control group. Their Receiver Operating Characteristic Curve (ROC) scores from UCSD Ped1 and Ped2 datasets were compared. Comparative analysis of the recorded model accuracies was tabulated and a percentage increase in the model accuracy was noted. A sign test was used to test the significance of the improvement and at both 1% and 5% significance levels, empirical evidence of the enhancement was found. This work contributed to the autoencoder design paradigms, improvement of Spatial-Temporal Autoencoder accuracy through depth and regularization tuning and reduction of anomaly detection errors in surveillance videos. The study has shown that the depth of spatial-temporal autoencoder impacts its anomaly prediction accuracy. In future work, integration of continual learning and real-time anomaly detection should be considered.Murang'a University of Technolog
Newspaper Framing of The War on Terror and its Implications for Human Rights: The Case of Garissa Terrorist Attacks in Kenya
No full textThe study explores how the framing of the war on terror in Kenyan newspapers is re-shaping the human rights discourse. It principally explores how Kenya's counterterrorism responses since the late 1990s have impacted human rights enjoyment with a particular emphasis on the April 2015 Garissa terrorist attacks. The study examines media's portrayal of selected various human rights derogations such as the refoulement of refugees and asylum seekers, securitization and profiling of Muslim identities, and torture among others. The rights derogations are assessed within existing human rights provisions enshrined in both domestic and international law. The study adopts a qualitative content analysisapproach to identify media frames of terrorism in print media. The study analyzed the contents of 105 news articles that were published in The Standard newspaper regarding the Garissa University College terrorist attack within four weeks of the attacks. The findings indicate an increased media tolerance towards the violation of the rights of civilians in the context of the war on terror. The study recommends that the media should not abandon championing for human rights in the context of the war on terror
Termite species and functional groups in maize intercrop systems in Machakos County, Kenya
No full textTermites are important ecosystem engineers in the tropics but certain termite species cause damage to economically important crops. In Africa, termites cause >50% damage in maize. This study evaluated the effect of intercropping maize with soybean, common beans and sorghum on the level of termite damage, abundance of termite species and functional groups in Machakos County, Kenya during two cropping seasons. In both seasons, Macrotermes herus, M. subhyalinus, Coptotermes formosanus, Odontotermes badius, O. longignathus and Cubitermes ugandesis were recorded. There was a low percentage of lodged plants in maize-sorghum intercrop which also had low population densities of M. herus and O. badius in both seasons. There was no difference in the number of C. formosanus in both seasons. The lowest number of fungus-cultivators was in the maize-sorghum intercrop while soil feeders occurred in low populations. Intercropping maize and sorghum can be further explored alongside other integrated termite management techniques. The observed low populations of soil feeders necessitate adoption of farming practices that conserve them in order to improve crop productivity
Efficacy of Travel Motivation on Destination Loyalty Among Domestic Tourists in the Coast Region of Kenya
No full textDoctor of Philosophy in Hospitality and Tourism Management, 2022Despite the marginal growth recorded in the tourism sector in Kenya, the domestic visits and estimates fall far below the expectations. This study aimed at assessing the efficacy of travel motivation on destination loyalty among domestic tourists in the Kenyan Coast. The study was guided by the following specific objective to; determine the travel preferences and frequency of domestic tourists visiting diverse attractions in the Coast Region of Kenya; investigate the influence of travel motivation aspects on destination loyalty of domestic tourists in the Coast Region of Kenya; examine the mediating effect of satisfaction on the relationship between travel motivation and destination loyalty of domestic tourists in the Coast Region of Kenya; and assess the moderating effect of contextual factors on the relationship between travel motivation and destination loyalty among domestic tourists in the Coast Region of Kenya. The study area comprised frequented attractions in the Coast region of Kenya. The study adopted an embedded mixed approach comprising descriptive survey (quantitative) and explanatory research designs (qualitative). Simple random sampling and purposive techniques were adopted for domestic tourists, destination managers and experts respectively. Data was collected using questionnaires and interview schedules. Four hundred (400) questionnaires were distributed and the return rate was 73.3%. Further, 5 destination managers and experts were interviewed. Data analysis was done using various techniques such as; ANOVA, Chi-square, multiple linear regression, hierarchical multiple regressions, Pearson correlations, one sample t-test and descriptive analysis. The research findings were an indication that the majority of the National and Marine Parks within the Coastal touristic circuit are popular among domestic tourists since they were highly visited and revisited due to exceptional experiences on offer. The research findings were an indication that the majority of the museums and historical sites such as; Fort Jesus, Gede ruins and Malindi museum are popular among domestic tourists. These destinations denote the authentic and rich culture among the native people visiting the Coast Region of Kenya. The model summary results indicate that 44.2% of total variation in destination loyalty was explained by travel motivation aspects denoted as destination attributes and sociopsychological factors. The relationship between travel motivation and destination loyalty was mediated by satisfaction (β=0.234, t=07.356, p=<0.000) implying that when customers’ expectations are confirmed they tend to be satisfied and are likely to recommend and revisit. The hierarchical multiple regression demonstrated that contextual factors have a moderating effect on interaction between travel motivation and destination loyalty since the model was significant {R2 = 0.255, F (7, 371) = 12.12, p =0000}. The model accounted for 25.5% of variation on destination loyalty. This means that the composite elements of contextual factors namely; political, economic, technological and socio-cultural factors significantly moderates the interaction between travel motivation and loyalty behaviour of domestic tourists. All the three null hypotheses were tested and rejected. The study recommendations need to; prioritize the ever-growing youth market segment through legislation; creating exceptional tourist experiences and a comparable research studies should be carried out in other destination areas visited by domestic tourists in Kenya.Murang'a University of Technolog
Moderating Effect of Business Regulatory Requirements on The Effect of Firm Specific Factors on Financial Performance of Private Security Firms in Kenya
No full textDoctor of Philosophy in Business Administration (Finance Option), 2022Even though Kenya enacted Private Security Regulatory Act of 2016, majority of private security companies have continued to operate without complying with the regulation thus inhibiting their performance. For private security firms to survive and thrive, they need to be provided with a friendly business climate. The research therefore investigated the effect of firm specific factors and business regulatory requirements on the financial performance of private security firms. The firm specific factors included firm’s financial aspects, entrepreneur’s attributes and firm’s characteristics, making the independent variables. In the study, business regulatory requirements were the moderating variables. Business regulatory requirements included finance access regulations and private security industry regulation. The research findings will be useful to various groups including academia, government and management of private security firms. The research was guided by public interest, credit access, scale efficiency, Miller- Orr model and social network theories. Further, the research was based on descriptive survey research design. The study population was 75 private security firms operating in Kenya forming the census with no sampling being carried out. The study made use of primary and secondary data with primary data being sourced using structured questionnaires. The instrument was taken through pretesting to ensure validity and reliability of each construct measurements before actual study. Statistical tools including frequency distribution, mean, standard deviation and coefficient of variation were used as descriptive statistics. Multivariate OLS regression was applied to examine the effect of firm specific factors on financial performance. Stepwise regression was adopted to examine the moderating effect of business regulatory requirements on the relationship between firm specific factors and financial performance. The study established that firm financial aspects had a significant direct effect on financial performance of private security firm in Kenya. The study also revealed that firm entrepreneur attributes had a direct significant effect on private security firms’ financial performance in Kenya. The study also noted that firm characteristics had a significant direct effect on private security firms’ financial performance. Finance access regulations did not have a significant effect on the effect of firm specific factors on financial performance. Further, private security industry regulations had a significant moderating effect on the effect of firm specific factors on private security firms’ financial performance in Kenya. The study thus concluded that all firm specific factors significantly explained financial performance of private security firms in Kenya. The study also concluded that finance access regulations was not a moderator of the effect of firm specific factors on financial performance of private security firms in Kenya. Further, the study concluded that private security industry regulations moderated the effect of firm specific factors on financial performance of private security firms in Kenya. The study recommends that private security firms should enhance their financial aspects such as improving their cash flow and having financial statements audited. The owners of private security firms should enhance their entrepreneur attributes such as networking and financial literacy. The study also suggests to management of private security firm to enhance their firm characteristics such as firm size. The research also noted that the management of private security firms ought to align their operations with private security industry regulations such as minimum wages and training for staff to enhance their financial performance.Murang'a University of Technolog