Browsing by Author "Getachew Alemu"
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Item Determinants of Adoption of Vermicomposting Technology among Smallholder Farmers in Walmara Woreda, Oromia Region, Ethiopia(Addis Ababa University, 2023-11) Getachew Alemu; Aseffa Seyoum (PhD)The majority of the workforce in Ethiopia is employed in agriculture, which also has the largest economic contribution. However, agriculture is relied small-scale subsistence farming systems which practiced on infertile soil. Because of this low agricultural production owing to infertility problem, many people have been facing food insecure. Using vermicompost is among important solution for reducing such soil fertility problem and vulnerability to food insecurity although the practice is not adopted by farmers at expected level. Therefore, the purpose of this study is to analyze factors influencing the adoption of vermicomposting technology in Walmara woreda. To achieve the objective of the study, data were collected from 184 householders (HHs) where (76 vermicompost adopters and 108 non-vermicompost adopters HHs). In addition, key informants and focus group discussions were conducted to support the survey data. The quantitative data analysis were analysed using both descriptive and econometric methods. Data analysis was done using both descriptive and econometric methods. A logistic regression model was used to estimate the determinants of adoption of vermicomposting technology. The analysis revealed that age, education status, field demonstration, distance to nearest farmland, access to credit and the extent of soil fertility problem were the variables that were significantly affected. The studies also showed that vermicompost has a positive role to increase soil fertility, and thereby boosted crop production and productivity. The analysis showed the main challenge of adoption of vermicomposting technology in the study area are lack of awareness, interest, labour, vermin box, access of technology, land, government support, and capital. The study determined that vermicompost is the main possible solution to increase soil fertility and production in the study area. Thus, it is advised that vermicomposting technology be given priority by governments as well as other interested participants in order to increase soil fertility, production, and productivity.Item Survey and Investigation of the design framework of Brain-Machine Interfaces used in Neural Prosthetics(Addis Ababa University, 2020-10) Ermias Telahun; Getachew AlemuIn a world inundated in technology, the line between humans and machines has begun to blur; our thoughts and actions are increasingly shaped and substantiated by machines. Perhaps nowhere is this blurring more evident than in the scientific endeavor of Brain-Machine Interface (BMI; Brain Computer Interface, BCI). This endeavor seeks to use electrical signals generated by action potentials in the nervous system and interface it with a computer or a device so as to regain communication with the outside world as well as motor functions by using an artificial limb. The need for using a BMI is seen most clearly in paralyzed patients who have lost partial (paraplegia) or total (quadriplegia) use of their motor functions, as well as in patients of chronic progressive diseases as Amyotrophic Lateral Sclerosis (ALS). Over the past two decades a vast array of researches have been conducted in BMI Neural Prosthetics. Initially the experiments were performed on rodents. Then the studies developed to using primates in a grasping experiment. In the past couple of years electrodes implanted intracranially into the skull of a quadriplegic person has led to using a robotic arm through though only. Noninvasive BMI researches have also proliferated in the past couple of decades. The current study proposes to do a systematic review on the various studies already performed in BMI Neural Prosthetics in order to investigate and suggest the best approach to design a BMI system. An in-depth explorative survey was conducted to look into the various steps towards development of a complete system design to alleviate existing disabilities. A comparative analysis using the noninvasive EEG device ‘Emotiv EPOC’ was performed to compare the control signal types, feature extraction mechanisms, classification algorithms and their corresponding accuracies and applications. Accordingly, the best design framework of BMIs in Neural Prosthetics was suggested, which is a good addition to the pool of researches in the scientific community.