Appraisal of Cashless Policy on the Nigerian Financial System

The Central Bank of Nigeria (CBN) has been active in the inauguration of policies and schemes to foster the implementation of the cashless policy in Nigeria. However the current transition to cashless economy raises a lot of concerns with no substantial evidence yet to justify its implementation. This study was carried out in order to appraise the implementation of the cashless policy since its introduction into the Nigerian financial system in 2012 and also to examine the persistent challenges facing its implementation. In view of the above stated objective, primary data were collected with the aid of the questionnaire, which was randomly administered to 120 respondents ranging from First Bank, Zenith Bank and United Bank for Africa. The banks were selected based on their total assets and the information collected covered the activities of the CBN and that of these banks towards implementation of the cashless policy from 2012 till date.The data collected were presented and analyzed with the aid of the Statistical Package for Social Sciences (SPSS) using descriptive statistics and one-sample t-test. The results led to the conclusion that despite the need to operate cashless transactions dominating the modern Nigerian economy, the cashless policy will have the desired impact only if a lot is done to ensure the implementation of an effective cashless system

Polyphenols and Microvascular Function in Humans: A Systematic Review.

BACKGROUND: Polyphenol-rich dietary sources are acknowledged to have potential cardiovascular health benefits, particularly in reducing cardiovascular disease risk. METHODS: This systematic review sought to determine the effect of polyphenol-rich foods and beverages upon microvascular function, which is of considerable importance in its contribution towards the pathophysiology of microvascular-related complications but also in the future development of (macro-vessel) cardiovascular disease. RESULTS: Overall, consumption of polyphenol-rich foods and beverages demonstrate improved microvascular function, although this is dependent upon the polyphenol source, the dose of the product, the duration of consumption and the population group studied. Most subgroups reviewed suggest an overall beneficial effect on microvascular function, particularly grape-derived products, cocoa, tea, pine bark and Rutaceae aurantiae. Other groups remain equivocal and require further study due to the limited research performed to date. CONCLUSION: Polyphenols are abundant in the human diet and this systematic review demonstrates that they are an inexpensive, non-pharmacological approach for improving cardiovascular health in currently healthy individuals and in populations with microvascular dysfunction

Covariate factor mitigation techniques for robust gait recognition

The human gait is a discriminative feature capable of recognising a person by their unique walking manner. Currently gait recognition is based on videos captured in a controlled environment. These videos contain challenges, termed covariate factors, which affect the natural appearance and motion of gait, e.g. carrying a bag, clothing, shoe type and time. However gait recognition has yet to achieve robustness to these covariate factors. To achieve enhanced robustness capabilities, it is essential to address the existing gait recognition limitations. Specifically, this thesis develops an understanding of how covariate factors behave while a person is in motion and the impact covariate factors have on the natural appearance and motion of gait. Enhanced robustness is achieved by producing a combination of novel gait representations and novel covariate factor detection and removal procedures. Having addressed the limitations regarding covariate factors, this thesis achieves the goal of robust gait recognition. Using a skeleton representation of the human figure, the Skeleton Variance Image condenses a skeleton sequence into a single compact 2D gait representation to express the natural gait motion. In addition, a covariate factor detection and removal module is used to maximise the mitigation of covariate factor effects. By establishing the average pixel distribution within training (covariate factor free) representations, a comparison against test (covariate factor) representations achieves effective covariate factor detection. The corresponding difference can effectively remove covariate factors which occur at the boundary of, and hidden within, the human figure.The Engineering and Physical Sciences Research Council (EPSRC

Advanced Sensing and Image Processing Techniques for Healthcare Applications

This Special Issue aims to attract the latest research and findings in the design, development and experimentation of healthcare-related technologies. This includes, but is not limited to, using novel sensing, imaging, data processing, machine learning, and artificially intelligent devices and algorithms to assist/monitor the elderly, patients, and the disabled population

KC-135 and Other Microgravity Simulations

This document represents a summary of medical and scientific evaluations conducted aboard the KC-135 from June 23, 2004 to June 27, 2005. Included is a general overview of KC-135 activities manifested and coordinated by the Human Adaptation and Countermeasures Office. A collection of brief reports that describe tests conducted aboard the KC-135 follows the overview. Principal investigators and test engineers contributed significantly to the content of the report describing their particular experiment or hardware evaluation. This document concludes with an appendix that provides background information concerning the KC-135 and the Reduced-Gravity Program

Secure and private fingerprint-based authentication

This thesis studies the requirements and processes involved in building an authentication system using the fingerprint biometric, where the fingerprint template is protected during storage and during comparison. The principles developed in this thesis can be easily extended to authentication systems using other biometric modalities. Most existing biometric authentication systems store their template securely using an encryption function. However, in order to perform matching, the enrolled template must be decrypted. It is at this point that the authentication system is most vulnerable as the entire enrolled template is exposed. A biometric is irreplaceable if compromised and can also reveal sensitive information about an individual. If biometric systems are taken up widely, the template could also be used as an individual's digital identifier. Compromise in that case, violates an individual's right to privacy as their transactions in all systems where they used that compromised biometric can be tracked. Therefore securing a biometric template during comparison as well as storage in an authentication system is imperative. Eight different fingerprint template representation techniques, where templates were treated as a set of elements derived from the locations and orientations of fingerprint minutiae, were studied. Four main steps to build any biometric based authentication system were identified and each of the eight fingerprint template representations was inducted through the four steps. Two distinct Error Tolerant Cryptographic Constructs based on the set difference metric, were studied for their ability to securely store and compare each of the template types in an authentication system. The first construct was found to be unsuitable for a fundamental reason that would apply to all the template types considered in the research. The second construct did not have the limitation of the first and three algorithms to build authentication systems using the second construct were proposed. It was determined that minutiae-based templates had significant intra sample variation as a result of which a very relaxed matching threshold had to be set in the authentication system. The relaxed threshold caused the authentication systems built using the first two algorithms to reveal enough information about the stored templates to render them insecure. It was found that in cases of such large intra-sample variation, a commonality based match decision was more appropriate. One solution to building a secure authentication system using minutiae-based templates was demonstrated by the third algorithm which used a two stage matching process involving the second cryptographic construct and a commonality based similarity measure in the two stages respectively. This implementation was successful in securing the fingerprint template during comparison as well as storage, with minimal reduction in accuracy when compared to the matching performance without the cryptographic construct. Another solution is to use an efficient commonality based error tolerant cryptographic construct. This thesis lists the desirable characteristics of such a construct as existence of any is unknown to date. This thesis concludes by presenting good guidelines to evaluate the suitability of different cryptographic constructs to protect biometric templates of other modalities in an authentication system

Artificial Intelligence and Cognitive Computing

Artificial intelligence (AI) is a subject garnering increasing attention in both academia and the industry today. The understanding is that AI-enhanced methods and techniques create a variety of opportunities related to improving basic and advanced business functions, including production processes, logistics, financial management and others. As this collection demonstrates, AI-enhanced tools and methods tend to offer more precise results in the fields of engineering, financial accounting, tourism, air-pollution management and many more. The objective of this collection is to bring these topics together to offer the reader a useful primer on how AI-enhanced tools and applications can be of use in today’s world. In the context of the frequently fearful, skeptical and emotion-laden debates on AI and its value added, this volume promotes a positive perspective on AI and its impact on society. AI is a part of a broader ecosystem of sophisticated tools, techniques and technologies, and therefore, it is not immune to developments in that ecosystem. It is thus imperative that inter- and multidisciplinary research on AI and its ecosystem is encouraged. This collection contributes to that