Mathematical science department

A number of discussions on mortality or survival patterns of under-five children in Nigeria have been presented in the literature over years, most of which were characterized by descriptive analysis, in which facts were reported by percentages, ratio and measures of association to mention a few.  In this study, binary logistic regression model was employed to model the survival status (dead or alive) of under-five children in Nigeria as a function of some socio-demographic variables. Results from this study revealed that ten socio-demographic variables among several others were significantly associated with the survivals of under-five children in Nigeria. Specifically, the results showed that children that were born in urban area, that were exclusively breastfed, that were among the first four children in the family, whose mothers have secondary education and post-secondary education have significant increased odds, to about 27%, 580%, 20%, 22% and 102% respectively, of surviving be...

Information on rate of changes in longitudinal surveys with certain types of population can robustly considered only by Successive sampling in estimate population parameters. Therefore, this study proposed a more efficient estimator technique in successive sampling schemes to determine the population estimates of the two occasions. The proposed estimator was obtained over mathematical expectation and statistical assumptions to derived an unbiased estimate of mean ( ), minimum variance ( ) and Relative efficiency comparison (REC). A Real-life data were used to validate the expression in the study. The data were last two population census conducted in Nigeria in 1991 and 2006 respectively by National Population Commission (NPC). The findings of the study include a proposed estimator obtained by hybridization of linear and ratio estimator, mathematical estimations of the mean in first and second occasions, minimum variance with maximum precision and relative gain in efficiency of the f...

The role of universities as centre of research and diffusion of findings is becoming increasingly important in the 21st century. Higher institute is crucial to long running economic growth because it is the source of knowledge workers and an important ...

This research studies the application of hybrid algorithms for predicting the prices of crude oil. Brent crude oil price data and hybrid intelligent algorithm (time delay neural network, probabilistic neural network, and fuzzy logic) were used to build intelligent decision support systems for predicting crude oil prices. The proposed model was able to predict future crude oil prices from August 2013 to July 2014. Future prices can guide decision makers in economic planning and taking effective measures to tackle the negative impact of crude oil price volatility. Energy demand and supply projection can effectively be tackled with accurate forecasts of crude oil prices, which in turn can create stability in the oil market. The future crude oil prices predict by the intelligent decision support systems can be used by both government and international organizations related to crude oil such as organization of petroleum exporting countries (OPEC) for policy formulation in the next one ye...

As most of human activities are being moved to cyberspace, phishers and other cybercriminals are making the cyberspace unsafe by causing serious risks to users and businesses as well as threatening global security and economy. Nowadays, phishers are constantly evolving new methods for luring user to reveal their sensitive information. To avoid falling victim to cybercriminals, a phishing detection algorithms is very necessary to be developed. Machine learning or data mining algorithms are used for phishing detection such as classification that categorized cyber users in to either malicious or safe users or regression that predicts the chance of being attacked by some cybercriminals in a given period of time. Many techniques have been proposed in the past for phishing detection but due to dynamic nature of some of the many phishing strategies employed by the cybercriminals, the quest for better solution is still on. In this paper, we propose a new phishing detection model based on Ex...

The increase use of cloud computing infrastructure has led to a security consciousness by users and cloud service providers to protect data available in the cloud from illegal users. Even though, different techniques have been proposed by different researchers, yet, more techniques are still proposed all in the quest to achieve better and flexible security techniques that will utilize less resource and minimize cost, because user pay as they go in the cloud. In this paper we proposed an improved multi-channel security technique in the cloud using image steganography and RSA algorithm. The proposed method was used to conceal the existence of data communication using the image steganography and protect the concealed data using RSA encryption algorithm in order to prevent illegal access. Different data set such as text, image, audio and video were used to evaluate the system. It is shown in the analysis that text data utilizes less processing time, memory storage and processing power f...

The efficiency of Internet services is determined by the Cloud computing process. Various challenges in computing are being faced, such as security, the efficient allocation of resources, which in turn results in the waste of resources. Researchers have explored a number of approaches over the past decade to overcome these challenges. The main objective of this research is to explore the task scheduling of cloud computing using multi-objective hybrid Ant Colony Optimization (ACO) with Bacterial Foraging (ACOBF) behavior. ACOBF technique maximized resource utilization (Service Provider Profit) and also reduced Makespan and user wait times Job request. ACOBF classifies the user job request in three classes based on the sensitivity of the protocol associated with each request, Schedule Job request in each class based on job request deadline and create a Virtual Machine (VM) cluster to minimize energy consumption. Based on comprehensive experimentation, the simulated results show that t...

Information and communication technologies (ICT) have become commonplace entities in all aspects of life. Across the past twenty years the use of ICT has fundamentally changed the practices and procedures of nearly all forms of endeavour within business ...

The idea of integrating SDH/SONET with WDM network technology in a multilayer dynamic network has proven to be reliable alternative for changing from static to automatic switched transport network (ASTN) together with a dynamic photonic layer. ASTN can be defined as a network that can control signal and routing automatically while Static refer to a manual routing of signal by the admin, who manually configured the network routers by providing the necessary information required for a successful packet transmission.WDM has the capability of exploiting larger number of bandwidth given to it by optical fibers, for instance hundreds of 10 Gb/s channels can be transmitted over the same fiber when channel spacing is reduced down bleow100 GHz. We evaluate how WDM can enhances the performance SDH/SONET in terms of high capacity point-to-point links, wide and metro area networks and of course the multiple access WDM

Task scheduling in fog computing is one of the areas where researchers are having challenges as the demand grows for the use of internet of things (IoT) to access cloud computing resources. Many resource scheduling and optimization algorithms were used by many researchers in fog computing; some used single techniques while others used combined schemes to achieve dynamic scheduling in fog computing, many optimization techniques were assessed based on deterministic and meta-heuristic to find out solution to task scheduling problem in fog computing but could not achieve excellent results as required. This article proposes hybrid meta-heuristic optimization algorithm (HMOA) for energy efficient task scheduling in fog computing, the study combined modified particle swarm optimization (MPSO) meta-heuristic and deterministic spanning tree (SPT) to achieve task scheduling with the intention of eliminating the drawbacks of the two algorithms when used separately, the MPSO was used to schedul...

the rise in cyber attacks has overwhelmed the monetary resources and human ability to analyze and combat every new form of cyber threat in the cyber security industry. With the increasing digital presence, there is a large amount of personal and financial information that should be protected from cyber attacks. In fact, cyber attacks can ruin the reputation of an organization or letdown the organization completely. This research examines the use of AI in the enhancement of cyber security. Recent developments in artificial intelligence are transformational and have exceeded the level of human performance in tasks such as data analytics. The study adopted the thematic literature review method, and data were sourced from Google scholar, science direct, research gates, academia, and others. The investigation revealed that application of AI in controlling cyber attack has advantages and disadvantages; however, the advantages outweigh the disadvantages. This researcher discovers that with...

Internet of Things (IoT) devices generates a huge volume of data that needs to be processed at real time. Cloud computing paradigm has been a requisite part of this process, consequently, the physical distance between users and cloud increases transmission latency which makes cloud computing not too suitable for real time applications. To address this issue, Edge Computing (EC) which collaborates with the cloud computing allows the processing and storage of applications and data in real time from different geographical locations. As EC is being accepted in the ICT environment, it is also faced with a lot of security issues. In this paper, an investigation on the impacts of ransomware attacks on EC devices is conducted and presents some ransomware families that target edge devices. The study presented some solutions proposed in the literature on securing EC devices against ransomware attacks, however there is a need to provide proactive measures and also apply more robust methods such as, deep learning than the traditional signature based or shallow machine learning approaches which are not recommendable and robust enough in handling complex malwares like ransomware. Thus, the researchers proposed a deep learning framework for the detection of ransomware on EC devices.