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A Survey of Machine Learning Approaches and Techniques for Student Dropout Prediction
(Data Science Journal, 2019-04-17)
School dropout is absenteeism from school for no good reason for a continuous number of days. Addressing this challenge requires a thorough understanding of the underlying issues and effective planning for interventions. ...
Machine learning approach for reducing students dropout rates
(International Journal of Advanced Computer Research, 2019-05-06)
serious issue in developing countries. On the other hand, machine learning techniques have gained much attention on addressing this problem. This paper, presents a thorough analysis of four supervised learning classifiers ...
An Ensemble Predictive Model Based Prototype for Student Drop-out in Secondary Schools
(Journal of Information Systems Engineering & Management, 2019-08-22)
When a student is absent from school for a continuous number of days as defined by the relevant authority, that student is considered to have dropped out of school. In Tanzania, for instance, drop-out is when a student is ...
Enhancing Management of Nutrition Information Using Mobile Application: Prenatal and Postnatal Requirements
(IST-Africa, 2017)
Malnutrition contributes to over one half of the deaths of children under
age of five years in developing countries and is the single greatest cause of child
mortality in Tanzania. Investigations reveal that the issue ...
An Integrated Mobile Application for Enhancing Management of Nutrition Information in Arusha Tanzania.
(International Journal of Computer Science and Information Security, 2015-07)
Based on the fact that management of nutrition
information is still a problem in many developing countries
including Tanzania and nutrition information is only verbally
provided without emphasis, this study proposes ...
Combining Clinical Symptoms and Patient Features for Malaria Diagnosis: Machine Learning Approach
(Taylor & Francis online, 2022-01-30)
Presumptive treatment and self-medication for malaria have been used in limited-resource countries. However, these approaches have been considered unreliable due to the unnecessary use of malaria medication. This study ...
Poultry diseases diagnostics models using deep learning
(Frontiers in Artificial Intelligence, 2022-08-01)
Coccidiosis, Salmonella, and Newcastle are the common poultry diseases that
curtail poultry production if they are not detected early. In Tanzania, these
diseases are not detected early due to limited access to agricultural ...
A Deep Learning Model for Predicting Stock Prices in Tanzania
(Engineering, Technology & Applied Science Research, 2023-04-02)
Stock price prediction models help traders to reduce investment risk and choose the most profitable stocks.
Machine learning and deep learning techniques have been applied to develop various models. As there is a
lack ...
Machine Learning Imagery Dataset for Maize Crop: A Case of Tanzania
(Elsevier, 2023-03-31)
Maize is one of the most important staple food and cash crops that are largely produced by majority of smallholder farmers throughout the humid and sub-humid tropic of Africa. Despite its significance in the household food ...
A Battery Voltage Level Monitoring System for Telecommunication Towers
(Engineering, Technology & Applied Science Research, 2021-12)
Voltage fluctuations in batteries form a major challenge the telecommunication towers face. These fluctuations mostly occur due to poor management and the lack of a battery voltage level monitoring system. The current paper ...