ABSTRACT Cyber threats are currently on the rise, which has caused individuals, industrial control systems (ICSs), critical infrastructures (CIs), and nations to be subjected to attacks with great losses. Among the cyber threats used for these attacks is the advanced persistent threat (APT) which tends to use highly sophisticated tools to attack targeted organizations or a nation’s critical infrastructure. The capabilities of big data can be leveraged in conducting advanced analytics by ga...
Abstract Internet connectivity is one of the fundamental requirements for a successful mobile learning environment. However, within the context of Africa, availability and access, let alone cost, still pose a great challenge in higher education, especially in distance learning. Consequently, there arises a dire need for a native mobile learning application framework that would serve as an alternative to web-based learning environments in localized contexts such as Africa, where the problems...
ABSTRACT Recent breakthrough in mobile technology, wireless communication and sensing ability of smart devices promote the ease to detect real-world learning status of students as well as the context aware for learning. Targeted information can be provided to individual students in the right place and at the right time. This work is one of the three major modules of our Smart Learning Framework, others include Multimedia Module Contents (MMC) and Learning Style Index (LSI). However, this mod...
Abstract Fraud, waste, and abuse in many financial systems are estimated to result in significant losses annually. Predictive analytics offer government and private financial institutions the opportunity to identify, prevent or recover such losses. This work proposed a novel Big Data driven approach for fraud detection based on Deep Learning methods. A supervised Deep Learning solution leveraging Big Data was shown to be an effective Fraud predictor. Additionally, an unsupervised method base...
Abstract C-DEVS is a formalism for modeling and analysis of discrete event systems. It refers to the original formalism defined by Zeigler in 1976. While the simulation algorithms are well defined, their implementation is a challenge due to both correctness and efficiency issues. This work aims at studying the formalism and its operational semantics. We review and validate the meta-model for SimStudio - a Java implementation of the DEVS simulation protocol, and we debug its existing Java cod...
ABSTRACT Hepatitis C development is a public health concern globally; hence eliminating it has become a major public health goal by various countries. In Nigeria, monitoring Hepatitis C development with the view to eliminate it has faced several challenges such as lack of central national database on the virus, inadequate health intelligence and surveillance systems to monitor and control the incidences and prevalence of disease, manual system of health records collection, storage and access...
ABSTRACT Due to the vast amount of data that is being generated by the sensors through the smart devices in smart cities, streams of data must be processed in real time to gain insight quickly and to make decisions that are in most cases critical and time sensitive. The difficulty is diminished by using big data methods such as Cassandra, Hadoop, Kafka and Spark to perform real-time stream processing in an Internet of Things (IoT) environment, such as traffic monitoring in a smart city envir...
ABSTRACT Many Institutions offer on-line courses to people from all around the world. Learning Management Systems provides a convenient learning environment for on-line courses. Each learner has individual needs and characteristics such as, personality and learning styles. These investigations are supported by learning theorists who argue that, these differences affect individuals learning process, and that is why learners progress better under certain circumstances. Learning style is the ou...
ABSTRACT Main purpose of data mining is to extract valuable information from available data. With the enormous amount of data stored in files, databases, and repositories, in the healthcare sector, it’s increasingly important, if not necessary, developing powerful means for analysis and interpretation of such data for the extraction of knowledge that could help in decision-making. Classification is technique in data mining; it’s defined as distinguishing, assigning object to a certain cl...
ABSTRACT With the exponential growth of the information technology, nowadays tremendous amounts of data including images, audio, text and videos, up to millions or billions, are collected for training machine learning models. Deep neural networks (DNNs) are one of the widely used methods today. Large companies in the uses these methods to recommends buyers with products, filter junk email or text-based hate speeches, understand and translate major languages in real time, and so on. Inspired ...
ABSTRACT Developing countries have been plagued by recurrent cases of infectious disease outbreaks; coupled with the limitation of traditional disease control strategies, other approaches have been explored for disease control, with social media at the forefront. Data from this source is short, noisy, and informal in representation, thus, conventional natural language processing (NLP) methods are not well adapted for their structure. Hence, deep learning approaches for character-level word v...
Background of the study With the rapid development of computer networks, new and sophisticated types of attacks have emerged which require novel and more sophisticated defense mechanisms. Advanced Persistent Threats (APTs) are one of the most fast-growing cyber security threats that organizations face today [12]. They are carried out by knowledgeable, very skilled and well-funded hackers, targeting sensitive information from specific organizations. The objective of an APT attack is to stea...
ABSTRACT Recommender systems are powerful intelligent systems considered to be the solution to the problems of information overload. They provide users with personalized lists of recommended items, using some machine learning techniques. Traditionally, existing recommender systems have used single rating techniques to estimate users' opinions on items. Because user preferences might depend on the attributes of several items, the efficiency of traditional single-rating recommender systems is ...
ABSTRACT The dramatic progress of studies in human action recognition has being attributed to challenges inherent with conventional methods such as bag-of-words based description. As a result, researchers in the field of computer vision are still making efforts towards achieving structured interpretation of complex activities between multiple objects. This study proposes Pyramid of Histogram Oriented Gradients (PHOG) computed from Depth Motion Maps in a video stream as a new feature descripto...
ABSTRACT Advances in several key communication and information technologies are worth tracking for their impact on interactive health communication and ability to meet .customers' demands. One of these technologies is the inte1net. It is based on this that this research work is cal1'ied out to dete1mine the level at which the internet has been able to improve the delivery of healthcare services in the healthcare delivery system in Nigeria. An explanatory research methodology was adopted in th...