The Need for Marker-Less Computer Vision Techniques for Human Gait Analysis on Video Surveillance to Detect Concealed Firearms

Crimes involving the use of firearms have been on the increase in the past few years. One of the measures adopted to prevent these crimes is the use of CCTV operators at video surveillance centers to detect persons carrying concealed firearms on their bodies by monitoring their behavior. This paper has found that this technique has challenges associated with human weaknesses and errors. A review of the current attempts to automate video surveillance for concealed firearm detection has found that they have the limitation that the techniques can only be employed on stationary and cooperative persons. This makes them inappropriate for real-life surveillance. This paper highlights the need for automated video surveillance solutions that can detect persons carrying concealed firearms when they are not stationary and aware of the scanning process. We further explore automated behavioral analysis and specifically gait analysis as a possible technique for concealed firearm detection on video surveillance. Lastly, the paper highlights the possibility and viability of human gait analysis using marker-less computer vision techniques for detecting persons carrying firearms on their waist line

Lessons learnt from the 2014 West Africa ebola viral disease (EVD) outbreak: economic, political and social impacts of disease outbreaks

In many disease outbreaks, their effects can invariably be measured in both direct and indirect terms; directly by observable, measurable outcomes and indirectly by looking for knock-on effects post the disease outbreak. Some of these angles and degrees of measure could matter more and provide a different yet more objective measure of a true disease outbreak’s impact. Such measures include the economic, social and political implications following a disease outbreak. This research looks to study and document the economic, social and political implications of the 2014 West African EVD outbreak that mainly ravaged Guinea, Liberia and Sierra Leone. Whilst the outbreak may have been theoretically localized around the three countries, other neighboring and far flung but somewhat affiliated nations also had their share of the outbreak’s implications. This research also looks to study and identify knock-on effects of the outbreak in the other countries (outside the three at the outbreak’s epicenter). The research looks to inform and boost the focus on early and targeted mitigation efforts if only to safeguard the interests of regional blocks and other nations that may be victims of negative downturns as a result of such disease outbreaks. The research hopes to inform and spur intraregional and inter-national discussions and engagements on how to best deal with such disease outbreak in a measurable and sustainable manner, with an aim to possibly safeguard their socio-economic and political interests

A Conceptual Data Mining Model (DMM) used in Selective Dissemination of Information (SDI): a case study of Strathmore University library

Rationale - The process of locating and acquiring relevant information from libraries is getting more complicated due to the vast amount of information resources one has to plough through. To serve users purposefully, an academic library should be able to avail to users the tools and services that lessen the task of searching for information. Design - The research proposed a two-phase data mining through analysing the access behaviour of users. In the first phase, the Ant Colony Clustering Algorithm was used as the data mining method and separated users into several clusters depending on access records used. The clusters were in the form of course groupings. Users who have similar interests and behaviour were collected in the same cluster. In the second phase, the user records in the same cluster were analysed further. The second phase relied on association which was used to discover the relationship between users and information resources, users’ interests and their information access behaviour. Findings - It was ascertained that although users were able to locate and retrieve the information they needed, it was not up to the degree of satisfaction they expected. Furthermore, it took them some time to acquire the information. Using data mining together with selective dissemination of information would enable users to access relevant information without promptly thus saving time and other resources. Practical implications - The mining of user data within library databases would facilitate a better understanding of user needs and requirements leading to the development and delivery of specialised and more fulfilling services. Originality - The proposed DMM model is original as it is one of a kind that suggests integrating SDI with data mining in libraries