Browsing Computational and Communication Science Engineering by Author "Mduma, Neema"
Now showing items 1-20 of 27
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Automatic Railway Road Crossing (RLC) Traffic Light System for Metric Gauge Railway Network in Tanzania
NKUNZIMANA, Libere; Minja, Gilbert; Mariki, Christina; Zirakwiye, Innocent; Mduma, Neema; Dida, Mussa (International Journal of Advances in Scientific Research and Engineering (ijasre), 2021-11)The verdict has been established that Railway Level Crossings (RLCs) present a possible risk to roads users. Because of the ever- increasing number of vehicles on the road every day, it was determined that employing ... -
A Battery Voltage Level Monitoring System for Telecommunication Towers
Uwamahoro, Rahab; Mduma, Neema; Machuve, Dina (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 ... -
Characterisation of Malaria Diagnosis Data in High and Low Endemic Areas of Tanzania
Mariki, Martina; Mduma, Neema; Mkoba, Elizabeth (East African Health Research Journal, 2022)Background: Malaria remains a significant cause of morbidity and mortality, especially in the sub-Saharan African region. Malaria is considered preventable and treatable, but in recent years, it has increased outpatient ... -
Combining Clinical Symptoms and Patient Features for Malaria Diagnosis: Machine Learning Approach
Mariki, Martina; Mkoba, Elizabeth; Mduma, Neema (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 ... -
Computer Science Education in Selected Countries from Sub-Saharan Africa
Bainomugisha, Engineer; Bradshaw, Karen; Ujakpa, Martin; Nakatumba-Nabende, Joyce; Nderu, Lawrence; Mduma, Neema; Kihoza, Patrick; Irungu, Annette (ACM Inroads, 2024-02-20)Computer Science education in sub-Saharan Africa has evolved over the past decades. The number of institutions offering distinct undergraduate programs has grown, thus increasing the number of students enrolling in the ... -
Data Balancing Techniques for Predicting Student Dropout Using Machine Learning
Mduma, Neema (MDPI, 2023-02-27)Predicting student dropout is a challenging problem in the education sector. This is due to an imbalance in student dropout data, mainly because the number of registered students is always higher than the number of dropout ... -
Data driven approach for predicting student dropout in secondary schools
Mduma, Neema (NM-AIST, 2020-06)Student dropout is among the challenges that face most schools in developing countries particularly in Africa. In Tanzania alone, student dropout in secondary schools is pronounced to be around 36%. In addressing the ... -
Data Synthesis Technique for Categorical Pestes Des Petits Ruminants (PPR) Data Using CTGAN Model
Nyambo, Devotha; Mduma, Neema; Sinde, Ramadhani; Lyimo, Tumaini (Pre prints,org, 2023-05-11)Data scarcity is a significant challenge in the field of Machine Learning (ML), as data collection can be expensive, time‐consuming, and difficult, particularly in developing countries. This challenge is exaggerated on ... -
Dataset of banana leaves and stem images for object detection, classification and segmentation: A case of Tanzania
Mduma, Neema; Leo, Judith (Elsevier, 2023-06-16)Banana is among major crops cultivated by most smallholder farmers in Tanzania and other parts of Africa. This crop is very important in the household economy as well as food security since it serves as both food and cash ... -
A Deep Learning Model for Predicting Stock Prices in Tanzania
Joseph, Samuel; Mduma, Neema; Nyambo, Devotha (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 ... -
Development of a smart ugali cooker
Katwale, Samwel; Daudi, Ngollo; Hassan, Amran; Mduma, Neema; Dida, Mussa; Kisangiri, Michael (International Journal of Advanced Technology and Engineering Exploration, 2021-02-21)Ugali is a thick porridge that is one of the popular staple foods in East Africa. Traditional methods of ugali preparation, cooking, and consumption are described. Firewood has been used as the primary energy source ... -
Development of the RFID Based Library Management and Anti-Theft System:A Case of East African Community (EAC) Region
Irankunda, Deo; Sinde, Ramadhani; Mduma, Neema; Dida, Mussa (International Journal of Advances in Scientific Research and Engineering, 2021-05)Radio Frequency Identification (RFID) Systems are becoming very useful in our daily life due to its advantages such as reduction of human error, theft prevention, time consuming reduction, the auto identification ... -
Enhancing Management of Nutrition Information Using Mobile Application: Prenatal and Postnatal Requirements
Mduma, Neema; Kalegele, Khamisi (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 Ensemble Predictive Model Based Prototype for Student Drop-out in Secondary Schools
Mduma, Neema; Kalegele, Khamisi; Machuve, Dina (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 ... -
An Integrated Deep Learning-based Lane Departure Warning and Blind Spot Detection System: A Case Study for the Kayoola Buses
Ziryawulawo, Ali; Mduma, Neema; Lyimo, Martine; Mbarebaki, Adonia; Madanda, Richard; Sam, Anael (IEEE, 2023-11-16)Deep learning-based driver assistance systems (ADAS) have attracted interest from researchers due to their impact on improving vehicle safety and reducing road traffic accidents. In Uganda, road accidents have continued ... -
An Integrated Mobile Application for Enhancing Management of Nutrition Information in Arusha Tanzania.
Mduma, Neema; Kalegele, Khamisi (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 ... -
An integrated mobile application for enhancing management of nutrition information in Tanzania
Mduma, Neema (NM-AIST, 2016-04)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. Studies reveal that, the issue of ... -
Machine learning approach for reducing students dropout rates
Mduma, Neema; Kalegele, Khamisi; Machuve, Dina (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 ... -
Machine Learning Imagery Dataset for Maize Crop: A Case of Tanzania
Mduma, Neema; Laizer, Hudson (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 Machine Learning Model for detecting Covid-19 Misinformation in Swahili Language
Mlawa, Filbert; Mkoba, Elizabeth; Mduma, Neema (Engineering, Technology & Applied Science Research, 2023-06-02)The recorded cases of corona virus (COVID-19) pandemic disease are millions and its mortality rate was maximized during the period from April 2020 to January 2022. Misinformation arose regarding this threat, which spread ...