Malaria is a long-standing disease and one of the top life-threatening diseases, yet its treatment has not changed, while the world has already embraced the Fourth Industrial Revolution (4IR). A wave of research on digitizing monitoring mechanisms of such a deadly disease has surfaced. Automated malaria screening is one of the detection processes which are gaining popularity in the research domain. However, the process needs to be coupled with other processes aiming a nationally or regionally contextualised malaria monitoring system. This paper proposes a digital malaria monitoring system in the context of an African country or region. One advantage of such a digital system is that is enables a novel disease spread forecasting model based on the dynamics of different malaria types. The architecture of the diagnosis system is described, and the disease spread model is mathematically modelled in terms of a SPITR (Susceptible- Protected- Infected-Treated- Recovered) epidemic model which is further analysed. The forecasting model is expressed and analysed whereas experiments are conducted using a Monte Carlo simulation method. The design of the monitoring system has inspired how predictions can be made in the complex cases such as mixed infections. Results show that reinforcing the model parameter makes a significant improvement on the disease prediction.
Malaria is a long-standing disease and one of the top life-threatening diseases, yet its treatment has not changed, while the world has already embraced the Fourth Industrial Revolution (4IR). A wave of research on digitizing monitoring mechanisms of such a deadly disease has surfaced. Automated malaria screening is one of the detection processes which are gaining popularity in the research domain. However, the process needs to be coupled with other processes aiming a nationally or regionally contextualised malaria monitoring system. This paper proposes a digital malaria monitoring system in the context of an African country or region. One advantage of such a digital system is that is enables a novel disease spread forecasting model based on the dynamics of different malaria types. The architecture of the diagnosis system is described, and the disease spread model is mathematically modelled in terms of a SPITR (Susceptible- Protected- Infected-Treated- Recovered) epidemic model which is further analysed. The forecasting model is expressed and analysed whereas experiments are conducted using a Monte Carlo simulation method. The design of the monitoring system has inspired how predictions can be made in the complex cases such as mixed infections. Results show that reinforcing the model parameter makes a significant improvement on the disease prediction.
“…Therefore, it far surpasses Maple and REDUCE in its portability. CoCalc's relation to SageMath is that it is the cloud version of SageMath [SG17].…”
Section: Cocalcmentioning
confidence: 99%
“…Furthermore, its use in educational settings would allow teachers to create notebooks and conduct their lessons entirely on CoCalc by giving students the chance to interactive with and control the notebook. This is most notably achieved through the ability to create courses that students can be a part of, create handouts and assignments for students to complete which can then be graded either by the teacher or through the builtin peer grading system that randomly assigns the assignments to other students [SG17]. However, these features are part of the paid functionality.…”
While there are numerous linear algebra teaching tools, they tend to be focused on the basics, and not handle the more advanced aspects. This project aims to fill that gap, focusing specifically on methods like Strassen's fast matrix multiplication.
“…The system allows integrating interactive program code into the text of rnw-document. This code is compiled "on the fly" and the result is a finished report or article in pdf format [7].…”
Section: The Features and Advantages Of Lms Cocalcmentioning
Being commonly used worldwide, e-learning courses are only starting to evolve in regional Russian universities. Unlike the most Moodle-using colleagues, the authors created mathematical modeling e-course with not so well-known in Russia learning management system Cocalc. The biggest advantage of Cocalc is the ability to write and compile program code inside, with a lot of programming languages supported. Using statistical methods, the authors assessed the results of the course implementation, revealing that students began to perform tasks faster, learned to program fluently in R and Latex and increased their English level knowledge.
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