A Review of Characterization Approaches for Smallholder Farmers: Towards Predictive Farm Typologies.

This research article published by Hindawi, 2019Characterization of smallholder farmers has been conducted in various researches by using machine learning algorithms, participatory and expert-based methods. All approaches used end up with the development of some subgroups known as farm typologies. The main purpose of this paper is to highlight the main approaches used to characterize smallholder farmers, presenting the pros and cons of the approaches. By understanding the nature and key advantages of the reviewed approaches, the paper recommends a hybrid approach towards having predictive farm typologies. Search of relevant research articles published between 2007 and 2018 was done on ScienceDirect and Google Scholar. By using a generated search query, 20 research articles related to characterization of smallholder farmers were retained. Cluster-based algorithms appeared to be the mostly used in characterizing smallholder farmers. However, being highly unpredictable and inconsistent, use of clustering methods calls in for a discussion on how well the developed farm typologies can be used to predict future trends of the farmers. A thorough discussion is presented and recommends use of supervised models to validate unsupervised models. In order to achieve predictive farm typologies, three stages in characterization are recommended as tested in smallholder dairy farmers datasets: (a) develop farm types from a comparative analysis of more than two unsupervised learning algorithms by using training models, (b) assess the training models' robustness in predicting farm types for a testing dataset, and (c) assess the predictive power of the developed farm types from each algorithm by predicting the trend of several response variables

Machine Learning Model for Imbalanced Cholera Dataset in Tanzania.

This research article published by Hindawi, 2019Cholera epidemic remains a public threat throughout history, affecting vulnerable population living with unreliable water and substandard sanitary conditions. Various studies have observed that the occurrence of cholera has strong linkage with environmental factors such as climate change and geographical location. Climate change has been strongly linked to the seasonal occurrence and widespread of cholera through the creation of weather patterns that favor the disease's transmission, infection, and the growth of , which cause the disease. Over the past decades, there have been great achievements in developing epidemic models for the proper prediction of cholera. However, the integration of weather variables and use of machine learning techniques have not been explicitly deployed in modeling cholera epidemics in Tanzania due to the challenges that come with its datasets such as imbalanced data and missing information. This paper explores the use of machine learning techniques to model cholera epidemics with linkage to seasonal weather changes while overcoming the data imbalance problem. Adaptive Synthetic Sampling Approach (ADASYN) and Principal Component Analysis (PCA) were used to the restore sampling balance and dimensional of the dataset. In addition, sensitivity, specificity, and balanced-accuracy metrics were used to evaluate the performance of the seven models. Based on the results of the Wilcoxon sign-rank test and features of the models, XGBoost classifier was selected to be the best model for the study. Overall results improved our understanding of the significant roles of machine learning strategies in health-care data. However, the study could not be treated as a time series problem due to the data collection bias. The study recommends a review of health-care systems in order to facilitate quality data collection and deployment of machine learning techniques

Maternal knowledge-seeking behavior among pregnant women in Tanzania

This research article was published by SAGE Publications Ltd, 2021Background: Maternal mortality continues to be a global challenge with about 830 women dying of childbirth and pregnancy complications every day. Tanzania has a maternal mortality rate of 524 deaths per 100,000 live births. Objective: Knowing symptoms associated with antenatal risks among pregnant women may result in seeking care earlier or self-advocating for more immediate treatment in health facilities. This article sought to identify knowledge-seeking behaviors of pregnant women in Northern Tanzania, to determine the challenges met and how these should be addressed to enhance knowledge on pregnancy risks and when to seek care. Methods: Interview questions and questionnaires were the main data collection tools. Six gynecologists and four midwives were interviewed, while 168 pregnant women and 14 recent mothers participated in the questionnaires. Results: With the rise in mobile technology and Internet penetration in Tanzania, more women are seeking information through online sources. However, for women to trust these sources, medical experts have to be involved in developing the systems. Conclusion: Through expert systems diagnosis of pregnancy complications and recommendations from experts can be made available to pregnant women in Tanzania. In addition, self-care education during pregnancy will save women money and reduce hospital loads in Tanzania

Mobile Application for Research Knowledge Sharing and Dissemination: The Case of Nm-Aist Univeristy Tanzania

This research article was published by Scientific Research Publishing Inc 2022The utilization of mobile and web applications has surpassed all other plat- forms in terms of disseminating researchers’ knowledge among diverse com- munities throughout the world. The current method of disseminating re- searchers’ knowledge to the communities in the Arusha region in Tanzania is through meetings, workshops, and focus group discussions held by research- ers, agricultural extension officers and community members after every three months or during field study. Yet the strategy is inefficient and ineffective in practice. The purpose of this study was to determine the most efficient and successful method of disseminating knowledge in communities. The study began with a qualitative phase, utilizing an interpretive technique and a qua- litative multiple case study research design. The Arusha region in Tanzania was selected as a case study where different social activities were undertaken, including farming, livestock keeping, tourism activities and fishing. Individu- al participants were interviewed by using a semi-structured questionnaire. In addition, focus group discussions were conducted to gather more information regarding the needs of the mobile application. Through the implementation of the application, the second phase of the study led to the development of a mobile application that includes community members, agricultural extension officers, and researchers that will enable anyone to install the application on their mobile phones to access knowledge regarding activities undertaken in Arusha. According to the findings of the first phase of the research, a sub- stantial percentage of community members own mobile phones, and hence a mobile application would be sufficient. The research also found that most re- searcher-community interactions occur at the data collection and interven- tion assessment (field trials) stages. Hence, the mobile application will benefit community members, district agricultural, irrigation, and cooperative officers (DAICO), and researchers

Climatology-aware health management information system to enhance cholera epidemic analysis and prediction in Tanzania

This research article published by the International Journal of Advanced Technology and Engineering Exploration (IJATEE), Volume-6 Issue-55 June-2019The cholera epidemic remains a public health threat in many developing countries including Tanzania. It affects vulnerable populations living with an unreliable water supply and sub-standard sanitary conditions. Various studies have found that the occurrence of cholera has strong linkage with environmental factors such as climatology aspects and geographical location. In addition, climatology has been strongly linked to the creation of weather patterns that favor the transmission and growth of Vibrio cholerae, which causes the disease. There are several studies that have been conducted to integrate environmental factors into the existing health management information systems (HMISs) in order to enhance the analysis of cholera epidemics in Tanzania. This work explored how well climatology factors have been integrated into these existing HMISs and the potential of the systems in enhancing cholera epidemics analysis. We found that most of the existing HMISs have not explicitly integrated environmental and climatology features for effective analysis of diseases. We thus proposed the design and development of an effective Climatology-aware HMIS. Then, evaluate it with clinical and environmental data such as; geographical location, weather, conditions of the day, and date on set, of 22 medical students staying in the Mweka district in Tanzania. The results of system evaluation showed that 87% provided positive feedback on the capacity of the developed system, towards enhancing the cholera epidemic analysis and prediction linked with environmental factors particularly the climate change variables. The study recommends the review of systems and policies in the health sectors in order to adapt climatology factors

A study of users’ compliance and satisfied utilization of biometric application system

This research article published by Taylor & Francis Online, 2020Currently, the adoption rate of biometric technology has speedily grown in all applications. The technology is considered as an effective measure for the protection against crime. However, there is a concern that it violates the privacy and rights of the individuals. For instance, the possibility of fraud, identity theft, civil liberty violations, and inaccuracy of data. As a result, create the conflicts between service provider and public as they may be accused of a crime or become a victim of discrimination. This study constitutes exploratory research and is restricted to the usage of the biometric application system within the passport. It aims at discovering the substantial acceptance of users in implementing the biometric application for the East African passport (Uganda). Factor influencing users’ opinions regarding the acceptance of the biometric application, User willingness, trust and techniques for securing the biometric information are presented. Strategies aimed at regulating the protection of biometric data on the usage of the application are explained. The findings suggested encryption techniques as the most favorable tactic of protecting the biometric data application. Therefore, best practices such as individual desirability, practical accurateness, and eagerness are required

Big Data Analytics Framework for Childhood Infectious Disease Surveillance and Response System using Modified MapReduce Algorithm

This research article published by International Journal of Advanced Computer Science and Applications,Vol. 12, No. 3, 2021Tanzania, like most East African countries, faces a great burden from the spread of preventable infectious childhood diseases. Diarrhea, acute respiratory infections (ARI), pneumonia, malnutrition, hepatitis, and measles are responsible for the majority of deaths amongst children aged 0-5 years. Infectious disease surveillance and response is the foundation of public healthcare practices, and it is increasingly being undertaken using information technology. Tanzania however, due to challenges in information technology infrastructure and public health resources, still relies on paper-based disease surveillance. Thus, only traditional clinical patient data is used. Nontraditional and pre-diagnostic infectious disease report case data are excluded. In this paper, the development of the Big Data Analytics Framework for Childhood Infectious Disease Surveillance and Response System is presented. The framework was designed to guide healthcare professionals to track, monitor, and analyze infectious disease report cases from sources such as social media for prevention and control of infectious diseases affecting children. The proposed framework was validated through use-cases scenario and performance-based comparison

The Role of User-Agent Interactions on Mobile Money Practices in Kenya and Tanzania

Digital financial services have catalyzed financial inclusion in Africa. Commonly implemented as a mobile wallet service referred to as mobile money (MoMo), the technology provides enormous benefits to its users, some of whom have long been unbanked. While the benefits of mobile money services have largely been documented, the challenges that arise -- especially in the interactions between human stakeholders -- remain relatively unexplored. In this study, we investigate the practices of mobile money users in their interactions with mobile money agents. We conduct 72 structured interviews in Kenya and Tanzania (n=36 per country). The results show that users and agents design workarounds in response to limitations and challenges that users face within the ecosystem. These include advances or loans from agents, relying on the user-agent relationships in place of legal identification requirements, and altering the intended transaction execution to improve convenience. Overall, the workarounds modify one or more of what we see as the core components of mobile money: the user, the agent, and the transaction itself. The workarounds pose new risks and challenges for users and the overall ecosystem. The results suggest a need for rethinking privacy and security of various components of the ecosystem, as well as policy and regulatory controls to safeguard interactions while ensuring the usability of mobile money.Comment: To be published in IEEE Symposium on Security and Privacy 202

Dissemination of Agro-based Information by Telecentres among Selected Rural Farmers in Tanzania with a focus on Moshi Rural District, Kilimanjaro Region

The study assessed the role of Telecentres in the dissemination of agro-based information among selected farmers in rural areas of Tanzania. A cross-sectional study design was conducted in Moshi Rural District, in Kilimanjaro Region, Tanzania. A total of 442 rural farmers aged 21-60 years were randomly selected as study respondents. Questionnaires were used to collect data from respondents. The study found that 205 (55%) respondents were not aware of the existence and services offered among Telecentres, whereas only 12 (7%) respondents reported visiting Telecentres once per day, and 70 (41%) once per year. A total of 140 respondents selected computer services including internet, printing, and scanning to be available among Telecentres. 162 respondents recommended promotion and marketing strategies to enhance the usage of Telecentres among rural farmers was recommended by 162 respondents, while 200 requested agro-based information on crop diseases and pest problems. Inadequate agro-based information in the local language (Swahili) was reported among the challenges hindering the usage of Telecentres among 180 respondents. We recommend the government to exploit the potential of Telecentres in the dissemination of agro-based information among farmers and societies at large

Developing an Algorithm for Securing the Biometric Data Template in the Database

This research article published by the International Journal of Advanced Computer Science and Applications, Vol. 10, No. 10, 2019In the current technology advancement, biometric template provides a dependable solution to the problem of user verification in an identity control system. The template is saved in the database during the enrollment and compared with query information in the verification stage. Serious security and privacy concerns can arise, if raw, unprotected data template is saved in the database. An attacker can hack the template information in the database to gain illicit access. A novel approach of encryption-decryption algorithm utilizing a design pattern of Model View Template (MVT) is developed to secure the biometric data template. The model manages information logically, the view shows the visualization of the data, and the template addresses the data migration into pattern object. The established algorithm is based on the cryptographic module of the Fernet key instance. The Fernet keys are combined to generate a multiFernet key to produce two encrypted files (byte and text file). These files are incorporated with Twilio message and securely preserved in the database. In the event where an attacker tries to access the biometric data template in the database, the system alerts the user and stops the attacker from unauthorized access, and cross-verify the impersonator based on the validation of the ownership. Thus, helps inform the users and the authority of, how secure the individual biometric data template is, and provided a high level of the security pertaining the individual data privac