PhD Theses and Dissertations [CoCSE]
https://dspace.nm-aist.ac.tz/handle/20.500.12479/34
2024-03-28T19:53:30ZA Monitoring System for Transboundary Foot and Mouth Disease (FMD) considering the Demographic Characteristics in Gairo, Tanzania
https://dspace.nm-aist.ac.tz/handle/20.500.12479/2423
A Monitoring System for Transboundary Foot and Mouth Disease (FMD) considering the Demographic Characteristics in Gairo, Tanzania
Kijazi, Ahmed; Kisangiri, Michael; Kaijage, Shubi; Shirima, Gabriel
Foot and Mouth Disease (FMD) is present in many
countries, including Tanzania. Gairo is among the districts that
frequently face FMD. This study found that the current
mechanism for communicating FMD in Gairo district suffers
from a long chain of information flow that causes delay and
insufficient information for FMD control. Therefore, this study
aimed to explore the implementation of an information system
named "Monitoring System for Transboundary Foot and Mouth
Disease," developed purposely to provide a standard platform for
communicating FMD between livestock keepers and other
stakeholders in the district. The system enables timely sharing of
FMD events such as outbreaks, precaution measures, clinical
signs, and negative impacts using Short Message Services (SMS),
Unstructured Supplementary Service Data (USSD), and Voice
Calls (robo-calls) through the mobile phones. Also, livestock
keepers may report FMD outbreaks direct to the system using
feature phones. The Statistical Package for Social Sciences
(SPSS) was used to analyze data and Microsoft Visio was used for
drawing the system architecture and information flow diagram.
Finally, the system was implemented using PHP hypertext
processor, JQuery, HTML, JSON, JavaScript, MySQL, and Apache webserver
This journal article was published in Engineering, Technology & Applied Science Research journal in 2021
2021-01-01T00:00:00ZDevelopment of a secure multi-factor authentication algorithm for mobile money applications
https://dspace.nm-aist.ac.tz/handle/20.500.12479/2210
Development of a secure multi-factor authentication algorithm for mobile money applications
Ali, Guma
With the expansion of industry 4.0, financial technology (FinTech) has become paramount in
this era. Mobile money as one of the FinTech has immensely contributed to improving financial
inclusions among the unbanked population in many developing countries. Several mobile
money schemes were developed to ensure easy access to mobile money services. However,
they have suffered severe authentication security challenges since implementing two-factor
authentication (2FA). Therefore, this research developed a secure multi-factor authentication
(MFA) algorithm for mobile money applications that combines personal identification number
(PIN), one-time password (OTP), and biometric fingerprints to authenticate the mobile money
subscribers. It also used the customer’s biometric fingerprints and the agent’s quick response
(QR) code to authorise money withdrawal. The PINs and OTP are secured by secure hashing
algorithm-256 (SHA-256) and biometric fingerprints by Fast IDentity Online (FIDO), where
the Rivest-Shamir-Adleman (RSA) encryption protects the public/private key pair and the
fingerprint templates. The QR codes, confidential financial information in the databases, and
all the data before transmission to the remote databases are secured using Fernet encryption. A
design science research approach was employed in the research using a mixed-method. The
review results identified and grouped the threat models into attacks against privacy,
authentication, confidentiality, integrity, and availability. The cryptographic functions and
personal identification were the countermeasures. The survey identified authentication attacks,
identity theft, phishing attacks, and PIN sharing as the crucial security issues Uganda’s mobile
money systems encountered. The security analysis of the designed algorithm and developed
native genuine mobile money (G-MoMo) applications proved that it provided robust security
during authentication and ensured data confidentiality, integrity, privacy and user anonymity.
It is highly effective against several security attacks and resilient to non-repudiation. The
performance analysis results showed that the algorithm enhanced security but had high
communication overhead and computational cost. Lack of a forward navigation button, lack of
uniformity in the applications menu title, lack of search field options, lack of actions needed
for recovery, and lack of help & documentation, were identified as the results of the usability
issues with the native G-MoMo applications’ user interfaces. While the results of the usability
testing showed that the native G-MoMo applications were learnable, effective, efficient,
memorable, had few errors, satisfaction, ease of use, aesthetic, helpful, easy to integrate, and
understandable. In conclusion, implementing a secure mobile money authentication using the
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novel approach combining multiple factors helps mobile money subscribers and other
stakeholders trust the mobile money industry since the security goals are highly maintained.
A Thesis Submitted in Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Information and Communication Science and Engineering of the Nelson Mandela African Institution of Science and Technology (NM-AIST
2023-08-01T00:00:00ZDeveloping a high-performance soil fertility status prediction voting ensemble using brute exhaustive optimization in automated multiprecision weights of hybrid classifiers
https://dspace.nm-aist.ac.tz/handle/20.500.12479/2208
Developing a high-performance soil fertility status prediction voting ensemble using brute exhaustive optimization in automated multiprecision weights of hybrid classifiers
Josephat, Augustine
With the advent of machine learning (ML) techniques, various algorithms have been applied in
previous studies to develop models for predicting soil fertility status. However, these models are
observed to use varying fertility target classes, and variations have been reported in these models'
predictive performances. As a result, practical applications of these models for obtaining the most
accurate predictions may become hindered. While the weighted voting ensemble (WVE) ML
technique can be used to improve soil fertility status prediction by aggregating individual models
prediction, guaranteeing finding of an optimal WVE assignment weights is challenging. Whereas
a brute exhaustive search procedure can be applied for the mentioned task, there is a lack of
exploration on the exploitation of automated classifiers' precise weights combinations as search
spaces for successful optimization. This research aims to develop a high-performance soil
fertility status prediction voting ensemble using brute exhaustive optimization in automated
1EXP(-)Z+ multi-precision weights of hybrid classifiers. Soil chemical properties and ML
modeling algorithms for modeling soil fertility status were identified. Base hybrid ML
classification models for predicting soil fertility status were evaluated using Tanzania as a case
study. Finally, the base ML hybrids WVE models were optimized using brute exhaustive search
procedure’s novel developed search spaces generation algorithm for guaranteed optimal solution
finding. The research was designed using design science research methodology, with the
application of unsupervised machine learning K-mean algorithm with a knee detection method
to find the optimal number of soil fertility status target classes, and supervised learning
algorithms were applied to model classifiers for those optimal classes. Three soil fertility target
classes were identified by clustering technique. The model achieved on test data a predictive
accuracy of 98.93%, with respective AUC of 82%, 83%, and 87% for low, medium, and high
soil fertility targets classes. Whereas these performances are observed higher compared to models
in previous studies, 92% correct classifications were obtained on validation against external
unseen laboratory-based tested soil results. Therefore, soil testing laboratories and farmers should
consider using the model to smartly manage soil fertility which may lead to improved crop
growth and productivity. The government could set agricultural-related policies that require the
use of the model by farmers with the provision of agricultural inputs subsidies. Future work could
be to develop an integrated real-time web and mobile application for providing farmers with soil
fertility status information.
A Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Information and Communication Science and Engineering of the Nelson Mandela African Institution of Science and Technology
2023-08-01T00:00:00ZA monitoring system for transboundary foot and mouth disease considering livestock keepers demographic characteristics
https://dspace.nm-aist.ac.tz/handle/20.500.12479/2205
A monitoring system for transboundary foot and mouth disease considering livestock keepers demographic characteristics
Kijazi, Ahmed
Foot and Mouth disease (FMD) is a transboundary disease caused by a virus that affects domestic
and wild cloven-hooved animals such as sheep, goats, pigs, and buffalos. FMD is transmitted from
one animal to another through direct or indirect contact. Apart from other animal diseases, FMD has
been given great attention due to its unique behaviour, such as being potentially dangerous, rapidly
spreading disease, and it has no cure. Therefore, immediate information flow among livestock
stakeholders could help to mitigate FMD. Realizing the importance of animal disease surveillance,
many agencies developed systems for monitoring animal health (fast disease reporting and
response). The challenge is that they were developed using advanced technologies like web-based
and android, requiring skills, internet connectivity, computers, and smartphones to access them.
However, most livestock keepers lack these facilities, especially in developing countries. In that
case, they deny access to livestock keepers positioned at the grass-root of animals’ disease reporting
chain since illnesses always begin with their animals. Therefore, their lack of participation in
reporting or receiving animal disease information through the electronic-based animal disease
surveillance system causes a delay in identifying and reporting disease cases and provides
insufficient information for controlling contiguous diseases like FMD, which require more
precautionary measures through timely information sharing.
This study aims to bridge the gap between livestock keepers and top-level stakeholders by
developing an animal diseases surveillance system named “Monitoring System for Transboundary
Foot and Mouth Disease Considering Livestock Keepers Demographic Characteristics (AMoS4T-
FMD)”. The system provides a standard platform for sharing FMD-related information between top-
level stakeholders and livestock keepers in time using various mobile technologies based on their
demographic characteristics.
Gairo district in the Morogoro region was selected as a study area. Therefore, the surveillance system
was developed and tested in Gairo district settings. However, it has flexible settings to work
elsewhere. In Gairo, livestock keepers’ mobile phone usage and demographic data were collected to
determine the appropriate mobile technologies to communicate animal disease surveillance
information among themselves and top-level stakeholders through AMoS4T-FMD. After that, an
algorithm (FMD communication algorithm) which enables livestock keepers to communicate with
AMoS4T-FMD using Unstructured Supplementary Service Data (USSD), Short Message Service
(SMS) and Robot calls (Robocalls) based on their demographic data was developed. Also, a Model
for predicting and alerting FMD outbreaks in the Gairo district using an Agent-Based Simulation
modelling technique was developed. Lastly, the FMD communication algorithm and the Agent-
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Based Simulation model were combined into the software using the waterfall model for system
development. Finally, the system was tested using verification and validation techniques.
A Thesis Submitted in Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Information and Communication Science and Engineering of the Nelson Mandela African Institution of Science and Technology
2023-03-01T00:00:00Z