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Post-disaster management requires a proportional deployment of human and material resources. The number of resources required to manage a disaster cannot be known without first evaluating the extent of casualty and consequence. This study proposed a taxonomy for classifying natural disasters based on casualty and consequence. Using a secondary data on global disasters from 1900 to 2021, the hierarchical cluster analysis technique was deployed for taxonomy formation. The learning algorithm evaluated the similarities in numbers of deaths, injuries, and the cost of damaged property caused by disasters. Three clusters were extracted which sub-grouped historical disasters based on similarities in casualty and consequence. Further, a taxonomy that defines the ranges of what constitute low, average, and high deaths/injuries/damage was established. Classifying a future disaster with this taxonomy prior to the deployment of resources for rescue, resettlement, compensation, and other disaster management operations will guide efficient resource allocation on a case-by-case basis.

In this study, the artificial neural network was deployed to develop a classification model for predicting the class of a drug-related suspect into either the drug peddler or non-drug peddler class. A dataset consisting of 262 observations on drug suspects and offenders in central Nigeria was used to train the model which uses parameters such as exhibit type, suspect’s age, exhibit weight, and suspect’s gender to predict the class of a suspect, with a predictive accuracy of 83%. The model sets the pace for the implementation of a full system for use at airports, seaports, police stations, and by security agents concerned with drug-related matters. The accurate classification of suspects and offenders will ensure a faster and correct reference to the sections of the drug law that correspond to a particular offence for appropriate actions such as prosecution or rehabilitation.

Presents several letters to the editor referencing articles and topics discussed in previous issues. Refusal of the Yale University and the Harvard University to continue in the federal scholarship program, as mentioned in the December 5, 1959 issue of the journal; Information on the tragic end of the life of Povl Bang-Jensen, one of the few people in the West who did something effective to help the Hungarian freedom fighters; Appeal for financial aid to anyone who might be interested in helping to crystallize conservative, anti-socialistic feeling among college students.