Mr. EMUOBONUVIE ANDY ERHINYOJA
Publication Title Modelling Entrepreneurial Decision Making Process Using Fuzzy Inference Systems
Publication Type journal
Publisher www.isteams.net/ghanabespoke2021
Publication Authors Malasowe Bridget Ogheneovo & Emuobonuvie Andy
Year Published 2021-12-14
Abstract The essence of Entrepreneurship is making decisions that are constantly required to evaluate
alternatives and make decisions regarding a wide range of matters. Decision making involves a
lot of uncertainty and risk which poses serious challenges for Entrepreneurs to joggle among
them in other to take the best decision. Study have shown that focus has been mainly on the
analysis of the characteristics of potential entrepreneurs and the firm-creation process leaving
the critical incredient that will help in decision making. The increasing challenges and complexity
of business environments are making business decisions and operations more difficult for
entrepreneurs to predict the outcomes of these processes. Hence, this paper proposes a
decision support model -Fuzzy Inference System- that could be adapted for various business
decision processes. This system has the capability to handle decision making, by critically
considering the degree of membership of all the risk involved in a given problem space.
The model uses the concept of fuzzy set theory to judiciously select the variables in a given
problem space in an uncertain situations. From a real life practical point of view, this theory
offers a natural approach to the resolution of multidimensional and complex problems when the
available information is sparse and/or of poor quality. The fuzzy rule base sytem soften the
adverse effects that a business may suffer from these uncertain factors.
Publication Title State of the Art on Face Recognition – A Review
Publication Type journal
Publisher Journal of Multidisciplinary Engineering Science and Technology (JMEST)
Publication Authors Emuobonuvie E. Andy, Malasowe O. Bridget, Okeh O. Dono, Adeyemi B. Benjamin
Year Published 2020-09-01
Abstract The high demand for face recognition applications has attracted the interest of researchers in this area. As a result of this, several methodologies have been proposed by scholars in this field. Face recognition methodology aims to detect faces in still image and sequence images. Local, global, and hybrid are approaches used in this area. The major issue of face recognition includes intensity, illumination, difficult to control as well as pose. Face images are highly dynamic and they pose difficult issues and challenges to solve when in use, researchers in pattern recognition, computer vision, and artificial intelligence have proposed many models in other to reduce such difficulties to improve the efficiency, robustness, and accuracy. The objective of this paper is to provide a survey of the current state of research on face recognition methodologies that has been proposed by different researchers. The underlining principles and application areas of face recognition are also presented. Finally, a conclusion on the current state of the art in face recognition was given.
Publication Title LITTLE THINGS THAT MATTERS – GREEN INFORMATION TECHNOLOGY TODAY - A REVIEW
Publication Type journal
Publisher IJARCS
Publication Authors Malasowe Bridget Ogheneovo & Emuobonuvie Andy
Year Published 2018-10-25
Abstract Information Technology has been a very important tool in homes and organizations today. It has really enhanced human activities
greatly. Despite its enomous benefit, it has posed some level of serious risk to the society. While public awareness of environmental
sustainability is growing, there is concern about the economic costs of shifting to a greener economy and better undertsanding of Green
Information Technology. In other to satisfy IT users demand, production of IT equipment has increased. Its computing resources consume high
energy that have resulted to carbon footprints (CO2 emissions). Green IT plays an important role in addressing these issues by offering various
Green IT and IS initiatives and models through which efficiencies are met to reduce the emissions. Green IS is the usage of information systems
to achieve environmental objectives, while Green IT emphasizes reducing the negative environmental impacts of IT production, usage and
disposal. This paper reviews the extent of existing research work done on Green IS and IT, its level of awareness and its implementation. With
the increased rate of IT usage in recent time and the high negative effect caused by IT sector, its a great concern for all hands to be on deck to go
green in other to holisticly reduce the carbon footprint. The level of awareness and basic understanding of green IT and IS is a key for better
adoption and implementation of Green Technology.
Publication Title A Survey Of DNA Computing
Publication Type journal
Publisher Quest Journals
Publication Authors Malasowe Bridget, Awodele Oludele, Maitanmi Olusola, Emuobonuvie Andy
Year Published 2013-12-30
Abstract In recent times, computer chip manufacturers are frantically racing to make the next microprocessor that will overthrow speed records. So Microprocessors made of silicon will eventually reach their limits of speed and miniaturization and their manufacturers will need a new material to produce faster computing speeds. But fortunately scientists have found the new material they need to build the next generation of microprocessors. Millions of natural supercomputers exist inside living organisms, including our body. DNA (deoxyribonucleic acid) molecules, the material our genes are made of, have the potential to perform calculations many times faster than the most powerful human-built computers. DNA might in the nearest future be integrated into a computer chip to create a so-called BIOCHIP that makes computers even faster. DNA molecules have already been harnessed to perform complex mathematical problems by researchers.While still in its early life,DNAcomputers will be capable of storing billions of times more data than today personal computer. In this article, a survey of recent research on DNA computing is discussed and the possibility that it might take the place of silicon-based computers in the next decade.
Publication Title NEURAL NETWORK MODELS: A Basic Statistical Tool for Data analysis and Forecasting
Publication Type journal
Publisher International Journal of Computer (IJC)
Publication Authors Maitanmi Olusola, Malasowe Bridget , Emuobonuvie Erhinyoja Andy, Adekunle Yinka, Gregory Onwodi
Year Published 2013-02-16
Abstract Neural network model is a model of brain’s cognitive process. Neural network originated as a model of how the brain works and
has its beginnings in psychology. Today, neural network models are used to solve numerous problems associated with
forecasting, pattern recognition, classification, manufacturing, medical diagnostic, signal processing, system control, checking,
and modelling among others. This paper reveals the processes involved in using a neural network model in forecasting future
events by effectively and efficiently utilizing extracted rules from trained neural networks and domain knowledge of the applied
area. The structural method of operations and rules of extraction of neural networks were also discussed.