Fish Classification Algorithm using Single Value Decomposition

Automatic fish classification system plays a very useful role in the process of separating fishes into species for human consumption,ornamentation and other usages. Manual classificationof fishes into different types is difficult and boring. This work proposes a fast and accurate system capable of classifying fish images into distinct classes based on their physical form. The system comprises image-processing, feature extraction and classification method. Fishfeature vector is obtained from Single Value Decomposition (SVD) product extracted from fish block images. Training and testing of the proposed fish classification system are done using Artificial Neural Network (ANN). Experimental test was carried out to determine the species of query fish images. Thirty-six fish images were tested, 94% correct classification result is recorded

TIME SERIES FORECAST MODELS FOR FOREIGN EXCHANGE MARKET IN A DEVELOPING ECONOMY

Technicalities in foreign exchange forecasting have been of interest to investors and academia, particularly in a developing economy. Data of foreign exchange are time series in nature and several techniques have been developed to modeling and forecasting foreign exchange rates. In this study, Nigeria's foreign exchange rate against three world-leading currencies (US Dollars, Euro and Pounds Sterling) are modeled with ARIMA, Auto. arima, Box-Cox, random walk forecast, and Exponential Smoothing and subjected to comparative tests using  Diebold-Mariano criteria with a modern model time series model. The empirical analysis shows that that the modern model outperforms some of the other techniques in forecasting Nigeria exchange rates against world-leading currencies particularly when the forecast horizon is low

Forecasting Nigeria Foreign Exchange Risk with Extreme Value Theory

Foreign exchange forecasting is important in all forms of foreign investments and transactions, the skills which compliments the field of finance and related disciplines. This paper uses extreme value theory to estimate the Value-at-Risk (VaR) and Expected Shortfall (ES), by fitting negative log returns of Nigeria Naira (NGN) against nine other regional and world currencies into the Generalized Pareto Model. In this paper VaR is being used to determine daily foreign exchange risk on investments and the ES is used to determine the average risk over a period of time. Excess distribution and the tail of the underlying distribution were obtained over a required threshold. Empirical analysis shows that parameter estimate of the underlying distribution can be used to describe the performance of the VaR and ES. The findings contributes to the knowledge on foreign exchange forecasting and helps investors and policy makers in Nigeria to measure daily and possible risk over a period of time on certain investments

Social media usage amongst generation y in South Africa – does gender matter?

Abstract: Social media has become one of the most popular tools for social interaction, and has transformed how individuals socialise, seek and share information with each other. Despite the widespread usage of social media in South Africa, there is a lack of empirical research studies that crystallise the differences in usage of social media by men and women, and of the relationship between social media usage and behaviour. The purpose of the study was to establish the differences between how men and women use social media and if there are any differences in their behaviour on social platforms. The sample consisted of 1 176 individuals who have used a social media account within the last six months, and interviews were conducted via a self-administered questionnaire. The results indicate that most of the respondents had been on their preferred social media platform for five years or more, are of Generation Y, have a university degree, and were single and living alone. The results demonstrate that there are no statistically significant differences in the usage and behaviour of social media networking sites of men and women. Marketers therefore need to invest in developing and maintaining a presence on social media if they want to develop a loyal following amongst Generation Y. Social media can therefore be leveraged by marketers to disseminate information about new products or products that existing customers had not considered buying at the time of social media interaction

Using Extreme Value Theory to Model Insurance Risk of Nigeria's Motor Industrial Class of Business

Extreme losses have been recorded in Nigeria insurance companies due to motor insurance class claims; Nigeria Insurance market being a developing one requires building the confidence of the public to subscribe to their products. Nigeria’s motor industrial insurance claim data for five insurance companies in a two year period is modelled in this paper with extreme value theory (EVT) to estimate the Value-at-Risk (VaR), where VaR gives estimate of the minimum amount of claims an insurance company would pay in a given period of time. The time series plot was obtained which aimed at capturing the trend of the claims over the two-year period, the mean excess plot was obtained which helped to determine threshold and the shape of the distribution in the tail area. The returns were then fitted in a Generalized Pareto model (GPD), a similar model that would have been used is the Generalized Extreme Value model (GEV) but the GPD is used in this study because it describes what happens in the tail area of the distribution and not just the maximum tail. A linear Q-Q plot reveals that parametric model fits the data well. VaR estimate was finally obtained using the extreme value method and other two methods of Historical and Gaussian at 5% confidence interval. The three methods of estimating VaR were compared and the empirical result shows that extreme VaR is most suitable to calculate VaR as compared to the Historical and Gaussian method

EXPLORING THE METHODS OF COINTEGRATION PROCEDURES USING STOCK PRICES

Stationary models are an essential class of stochastic models for describing time series data which have received a great attention. In reality, however, business and economic data are non-stationary multivariate time series that are often better understood by cointegration analysis. This study investigates the cointegration testing methods of Engle-Granger two-step estimation technique, Phillip-Ouliaris test, and Johansen's multivariate test. The stock prices of selected companies in Nigeria from 2008-2014 are used in the study. Findings revealed that the three techniques produced different results and that the Johansen's method and Engle-Granger two steps procedure exhibits higher efficiencies than Phillips-Ouliaris methods but their efficiency is dependent on the number of variables and correct selection

A Hierarchical Clustering Approach for the Creation of a Simple Semantic Web Application

The goal of the Semantic Web is to develop enabling standards and technologies designed to receive more exact results when searching for information, and to help machines understand more information on the Web so that they can support richer discovery, data integration and navigation. This can be achieved if there is a common vocabulary for a set of domains. Information is published using standard vocabulary. This study explores the processes of creating a taxonomy for a set of journal articles using hierarchical clustering algorithm. 100 journal articles that cut across different fields were downloaded from the internet. These served as sample data. These journal articles were serialized, stemmed and tokenized. Term frequency was calculated for each journal article.  Some representative terms were selected from each journal article and similarity matrix was generated for the entire journal articles. Complete hierarchical clustering was used to create a cluster of the articles. JavaTree view program was used to view the dendrogram of the cluster. It was observed that the articles cluster around their subject, subject area, field of study, area of application, journal type, author, place of case study. This demonstrated that journal articles have properties on a taxonomy, could be created as a basis for a semantic web. Keywords: Semantic web, clustering, taxonomy, similarity, document collection

Development of Multilevel Distributed Database Architecture for Solving (GSM) Centralized Database Accessing Problem in Nigeria

Telecommunication is the basis of economic and political growth of any society. Since the advent of GSM in Nigeria, different operator have been battling with diverse challenges which erupted as a result of GSM growth and increased in number of GSM users. These challenges result in calls delay and poor quality of service which can be link to central database system. In this research work, a multilevel distributed database architecture for GSM network in Nigeria was developed and propose. It explores the use of the analytical model and numerical calling process algorithms for each location. The call arrival rate traffic to a database system is determine using mapping process ranging from state to region and finally to the center. Keywords: key Communication, Architecture, multi-level, centralized, networ