Flood Endangered Area Classification Using the K-Nearest Neighbour Algorithm

Preparing for the uncertainty of life is one aspect of the human existence that cannot be over emphasized. With the growth of technology especially the sophisticated nature of data mining and machine learning algorithms, these uncertainties can be predicted, planned and prepared for using existing variables and computer methodologies. The achievements and accomplishments of big data analytics over the past decade in diverse areas called for its implementation in meteorological and space data. Notably, enhancement of the proper management of life’s uncertainties when they eventually occur. This research work focuses on the classification of areas within the Nigerian Geographical territory that are prone to flood using the K-nearest neighbour Algorithm as a classifier. Data from Nigeria Meteorological Agency (NiMET) on seasonal rainfall prediction and temperature of different stations and cities for over three (3) years (2014-2017) was used as a dataset which was trained and classified with the k-Nearest Neighbour algorithm of machine learning. Results showed that some areas are prone to flood considering the historic data of both rainfall and temperature

Conceptual Design of a Cybersecurity Resilience Maturity Measurement (CRMM) Framework

African countries are at high risk with respect to cybersecurity breaches and are experiencing substantial financial losses. Amongst the top cybersecurity frameworks, many focus on guidelines with respect to detection, protection and response, but few offer formal frameworks for measuring actual cybersecurity resilience. This article presents the conceptual design for a cybersecurity resilience maturity measurement (CRMM) framework to be applied in organisations, notably for critical information infrastructure (CII), as part of cyber risk management treatment. The main thrusts of the framework are to establish, through assessment in terms of quantitative measures, which cybersecurity controls exist in an organisation, how effective and efficient these controls are with respect to cybersecurity resilience, and steps that need to be taken to improve resilience maturity. The CRMM framework we outline is conceptualised as being applicable both pre- and post-cyber attack. Drawing on the NIST cybersecurity framework (NIST CSF) and other relevant frameworks, the CRMM approach conceptualised in this article would be able to depict an organisation's cybersecurity practices and gauge the organisation's cybersecurity maturity at regular intervals. This CRMM approach is grounded in the idea that, by quantifying an organisation's current practices against established baseline security controls and global best practices, the resulting status measurement can provide the appropriate basis for managing cyber risk in a consistent and proportionate fashion. The CRMM framework defines four cybersecurity resilience quadrants (CRQs), which depict four different degrees of organisational preparedness, in terms of both risk and resilience

A Mathematical Model of Political Rumour in Assakio Community with Conditional Latent Period in a Varying Population

In this paper a rumour propagation model with conditional latent period and varying population is considered. In the literature, classical model assume that an ignorant individual enters the latent period and decide whether to become a spreader or stifler. In our model we introduce a new compartment called the blackmailers, another type of spreaders who spread the rumour for selfish reason. The model equations are first transformed into proportions, thus reducing the model equations from five to four differential equations. The model exhibit two equilibra, namely the Rumour Free Equilibrium (RFE) and the Rumour Endemic Equilibrium (REE). Using the method of linearized stability, we establish that the RFE state exist and is locally asymptomatically stable when R0 < 1  and that when R0 > 1 the endemic state exist. The model allows us to discuss the relationship between spreaders and blackmailers, and the effect of blackmailers on the stiflers. Finally, we present numerical simulations that show the impact of political motivated rumours and how its control can be achieved. Keywords: Rumor propagation, Political motivated rumour, Epidemiological models; stability analysis, Transition paramete