A Computation Investigation of the Impact of Convex Hull subtour on the Nearest Neighbour Heuristic

This study investigated the computational effect of a Convex Hull subtour on the Nearest Neighbour Heuristic. Convex hull subtour has been shown to theoretically degrade the worst-case performances of some insertion heuristics from twice optimal to thrice optimal, although other empirical studies have shown that the introduction of the convex hull as a subtour is expected to minimize the occurrences of outliers, thereby potentially improving the solution quality. This study was therefore conceived to investigate the empirical effect of a convex-hull-based initial tour on the Nearest Neighbour Heuristic vis-a-vis the traditional use of a single node as the initial tour. The resulting hybrid Convex Hull-Nearest Neighbour Heuristic (CH-NN) was used to solve the Travelling Salesman Problem. The technique was experimented using publicly available testbeds from TSPLIB. The performance of CH-NN vis-à-vis that of the traditional Nearest Neighbour solution showed empirically that Convex Hull can potentially improve the solution quality of tour construction techniques

Performance Evaluation of Convex Hull Node-Based Heuristics for Solving the Travelling Salesman Problem

This experimental study investigated the effect of Convex Hull on Nodebased Heuristics. This was motivated by the assertion in the literature that starting some insertion tours with a convex hull theoretically degrades their worst case from twice optimal to thrice optimal. The Node-based techniques considered were Nearest Neighbour Heuristic (NNH) and Nearest Insertion Heuristic (NIH). The derived heuristics with Convex Hull were referred to in this study as Convex Hull Nearest Neighbour (CHNN) and Convex Hull Nearest Insertion (CHNI), respectively. The techniques were experimented on eleven benchmark instances from TSPLIB using Python Programming Language. Experimental results showed that the performances of both the Nearest Neighbour and Nearest Insertion were enhanced in terms of Computational speed and solution qualit

Egungun Be Careful Na Express You Dey Go A Technical Treatise On The Mitigation Of Malware for Semi-Technical Users

We present a semi-technical approach to mitigating the malware menace. Our approach is twopronged vis-à-vis detection and prevention. We present existing state-of-the-art detection techniques as well as some readily available malware analysis tools for semi-technical users. We concluded by providing suggestions on malware prevention best practices

A Maximum Entropy Classification Scheme for Phishing Detection using Parsimonous Features

Over the years, electronic mail (e-mail) has been the target of several malicious attacks. Phishing is one of the most recognizable forms of manipulation aimed at e-mail users and usually, employs social engineering to trick innocent users into supplying sensitive information into an imposter website. Attacks from phishing emails can result in the exposure of confidential information, financial loss, data misuse, and others. This paper presents the implementation of a maximum entropy (ME) classification method for an efficient approach to the identification of phishing emails. Our result showed that maximum entropy with parsimonious feature space gives a better classification precision than both the Naïve Bayes and support vector machine (SVM

AI-PaaS Towards the Development of an AI-Powered Accident Alert System

The development of an accident detection system is a crucial step towards improving emergency response times, saving lives and achieving the ambitious projection of the United Nations General Assembly to drastically reduce the global fatality rate of road traffic crashes by half by the year 2030. It is also cardinal to the attainment of the United Nation’s SDG 11 goal of making cities and human settlements inclusive, safe, resilient and sustainable. In this study we present a preliminary development of an AI-powered Accident Alert System (AI-PaaS). The system has four modules namely, sensors module, detection module, registration module and messaging module. The detection module is powered by sensing technology and the Hidden Markov Model to intelligently and correctly detect that an accidents sound. The MPU 6050 containing both accelerometer and gyroscope is also integrated to detect any sharp variation in the acceleration and angular vis-à-vis a predefined threshold value. Once an accident has been detected, the messaging module is triggered to communicate first responders and the victims’ pre-registered kin. Preliminary results are presented. The system can potentially reduce road accident fatality by providing accurate and timely location-based information to emergency service providers

Strengthening Bioinformatics and Genomics Analysis Skills in Africa for Attainment of the Sustainable Development Goals Report of the 2nd Conference of the Nigerian Bioinformatics and Genomics Network

The second conference of the Nigerian Bioinformatics and Genomics Network (NBGN21) was held from October 11 to October 13, 2021. The event was organized by the Nigerian Bioinformatics and Genomics Network. A 1-day genomic analysis workshop on genome-wide association study and polygenic risk score analysis was organized as part of the conference. It was organized primarily as a research capacity building initiative to empower Nigerian researchers to take a leading role in this cutting-edge field of genomic data science. The theme of the conference was “Leveraging Bioinformatics and Genomics for the attainments of the Sustainable Development Goals.” The conference used a hybrid approach—virtual and in-person. It served as a platform to bring together 235 registered participants mainly from Nigeria and virtually, from all over the world. NBGN21 had four keynote speakers and four leading Nigerian scientists received awards for their contributions to genomics and bioinformatics development in Nigeria. A total of 100 travel fellowships were awarded to delegates within Nigeria. A major topic of discussion was the application of bioinformatics and genomics in the achievement of the Sustainable Development Goals (SDG3—Good Health and Well-Being, SDG4—Quality Education, and SDG 15—Life on Land [Biodiversity]). In closing, most of the NBGN21 conference participants were interviewed and interestingly they agreed that bioinformatics and genomic analysis of African genomes are vital in identifying population-specific genetic variants that confer susceptibility to different diseases that are endemic in Africa. The knowledge of this can empower African healthcare systems and governments for timely intervention, thereby enhancing good health and well-bein

An Enhanced Speech Recognition Algorithm Using Levinson-Durbin, DTW and Maximum Likelihood Classification

In this paper, we applied techniques such as Levinson-Durbin, DTW and maximum likelihood classification to achieve an enhanced speech recognition algorithm. Speech recognition has been adversely affected by noise and some other impairments factors making speech difficult to be recognized. Speech is distorted by a background noise and echoes, electrical characteristics. We used the combinatorial approach of Levinson-Durbin, DTW and maximum likelihood classification to develop a system for speech recognition. The system compares the speech with phonetics lattice and database of enrolled speeches from different speakers and output the enrolled speech with the recognition Id and name of the identified speech if it found a match. Otherwise error of unknown is returned to show speech mismatch. The system is able to distinguish two different speakers at any point in time using speech identity and phonetic pattern analysis

The Impact of Knowledge-Based Trust (Kbt) on The Adoption and Acceptability of Cashless Economy in Nigeria

The introduction of cashless policy in Nigeria had gained a number of reactions over the adoption of cashless economy (or cashless banking). The implication of this is that not many people have the understanding of the benefits the cashless system would accrue to entire Nigerian populace. Although, many have argued that the technological infrastructures available for the implementation of the cashless economy is still a matter of concern. This study attempts to examine the impact of integrating Technology Acceptance Model (TAM) with Knowledge-based Trust (KBT) on the adoption and acceptance of cashless economy among Nigerian populace. We designed a paper-based questionnaire to harvest people’s view about their intention on the adoption of cashless economy in Nigeria as well as their readiness to accept the policy. Consequent upon the impact of trust on the acceptability of the cashless economy, we formulated some hypotheses which was analysed with the use of T-statistics. The results of the hypothesis testing indicate that the integration of KBT with TAM has a significant relationship on intention towards the adoption and acceptance of cashless economy in Nigeria

A REVIEW OF TRENDS OF AUTHENTICATION MECHANISMS FOR ACCESS CONTROL

This work is a comprehensive overview of trends of authentication mechanisms for access control. It elaborates on different classes of authentication mechanisms such as PINs, Passwords, Smartcards and Biometrics, their uses and decryption. These authentication technologies are used to protect vital information as well as prevent unauthorized accessing of physical and logical resources in all information technology system. Of the entire authentication mechanisms worked upon, biometric is the most effective method of authentication, but it is very expensive to configure and maintain

Factors Influencing the Adoption of Smart Phones by University Students – A Cross-border Approach

This study explains the factors influencing the adoption of smart phones by undergraduate students in Nigeria and Republic of Benin. Questionnaire was used as the data collection instrument, and the design was guided by Rogers’ diffusion theory of innovations. Most of the sampled students agreed that factors such as relative advantage of smart phones, complexity of the phone, trial before buying the phone, observation before buying the phone, and compatibility of smart phone with their lifestyle influence their adoption of smart phones. The study also shows that internet browsing has a major influence on the adoption of smart phones