ABSTRACT Education is a vital ingredient for a sustainable economy where “knowledge is power”. Mlearning initiatives can lessen the digital divide in education and promote a knowledge-based economy. The high saturation of mobile technology has made it imperative to have mobile applications that provide solutions in many aspects of the economy, including education. Smartphones/tablets have gradually become widely adopted mobile learning devices. In Science and Engineering, Automata Theory...
Abstract With more than millions of pages, the Web has become a greatly enormous information source. This information is in form of documents, images, videos as well as text. With such vast sizes of data, it is a common problem to get the right information that one wants. Oftentimes users have to search for the right content they are looking for from the Web with the help of search engines. Searching can be done manually by use of available platforms like Google or automatically in form of w...
ABSTRACT Cervical cancer is the third major killer disease in developed and developing countries. Whereas screening and other preventive measures reduce the mortality rate in developed countries, mortality rates still remain very high in developing countries. This project focuses on the analysis of a digital image of the cervix; captured with a low-level camera, under a contrast agent: the visual inspection with acetic acid (VIA) is known as one of the reference methods to detect cervical ca...
ABSTRACT In recent times, the rate of growth in information available on the internet has resulted in large amounts of data and an increase in online users. The Recommendation System has been employed to empower users to make informed and accurate decisions from the vast abundance of information. In this Research, we propose a hybrid recommender engine which combines Content-Based and Collaborative filtering recommendations. This seeks to explore how prediction accuracy can be enhanced in ex...
ABSTRACT Sentiment Analysis is the task of classifying documents based on the sentiments expressed in textual form, this can be achieved by using lexical and semantic methods. The purpose of this study is to investigate the use of semantics to perform sentiment analysis based on probabilistic graphical models and recurrent neural networks. In the empirical evaluation, the classification performance of the graphical models was compared with some traditional machine learning classifiers and a ...
ABSTRACT Taking Nigeria as a case study, most educational institutions, be it at the primary, secondary or tertiary level are faced with the challenge of over population of student’s in a single classroom. Also, the teacher who teaches an over populated class finds it quite difficult to have a one on one interaction or communication with each student in order to learning challenges. As a result of that, most students find it difficult to understand in the classroom. This research is concer...
ABSTRACT The Internet of Things (IoT) has generated a large amount of research interest across a wide variety of technical areas. These include the physical devices themselves, communications among them, and relationships between them. One of the effects of ubiquitous sensors networked together into large ecosystems has been an enormous flow of data supporting a wide variety of applications. In this work, we propose a new “IntelliFog-Cloud” approach to IoT Big Data Management by leveragi...
ABSTRACT Wireless sensor network is application specific, which is deployed in an interested area like about hundred or thousands of sensor nodes. All the sensor nodes communicate via a wireless medium and works cooperatively to sense the environment in order to achieve the required task. Such sensor nodes which is application specific needs a good fault tolerance scheme to keep the system working. Since this sensor nodes are battery operated, have a small memory, deployed in harsh environme...
Abstract Smart media devices such as: smartphones and tablets are getting more powerful, smarter, cheaper and hence more popular. Recommendation systems become very common in e-business and e-Commerce, for example: Amazon, Google, eBay, Facebook, etc. all are using recommendation systems to promote their business. Recommendation systems are rarely used in learning; however it can be very useful.
ABSTRACT Artificial Neural network (ANN) is an area of computing that is modeled after the neural network of the biological brain and over the last few decades, has experienced huge success in its application in areas such as business, Medicine, Industry, Automotive, Astronomy, Finance, etc. Since Neural Networks are inherently parallel architectures, there have been several earlier researches to build custom ASIC based systems that include multiple parallel processing units. However, these ...
ABSTRACT Recommender systems are web-based platforms or software that use various machine learning methods to propose useful items to users. Several techniques have been used to develop such a system for generating a list of recommendations. Multi-criteria is a new technique that recommends items based on multiple characteristics or attributes of the items. This technique has been used to solve many recommendation problems and its predictive performance has been tested and proven to be more ...
ABSTRACT After many years of rigorous research and development in wireless sensor network (WSN) technology with numerous responses to innovative applications, WSNs still have some interesting unanswered questions. In this thesis we explain the challenges of the state of art in WSN for environmental monitoring applications using open-source hardware platforms, Arduino UNO, DHT11 temperature-humidity sensor, XBee and Raspberry Pi. The system is not only low cost but scalable enough to accept m...
ABSTRACT Research in computer vision and machine learning is a significant part of research in computer science departments of many leading institutions resulting in ideas and products that have direct applications in different industries such as medical image segmentation in the medical industry, and face recognition and tracking in the entertainment and security industry. Face recognition is a significant part of research in computer vision and machine learning and has a wide range of appl...
ABSTRACT The telecommunication industry has a lot of data related to households, individuals and devices. Advertisers pay a premium to ensure they advertise to their target audience. To ensure that content is personalized, it is necessary to accurately predict who is using a device in real time. A probabilistic matching algorithm to determine the profile of an individual based on behavioural analytics is developed and implemented. Two datasets ‘People data’ and ‘Device data’ were lin...
ABSTRACT Text analysis is a branch of data mining that deals with text documents. This project brings to light the classification of texts into their various categories. The structured and unstructured data seems to on a high rise in this era. Thus, to be able to classify this data is important. Classification however starts from collection, preprocessing, and feature extraction. There are several techniques that can be used for text classification, but machine learning algorithms will be em...