Africa In An Age Of Globalization

The global markets continue to grow in developing countries. Global markets have created new businesses and provided opportunities for global employers and individuals in developing countries. Through globalization of economies, jobs have been created which reduce unemployment rates. However, economic growth rates in Africa have been lagged behind other developing countries. This paper examines the importance of global business to Africa. Also, this study explores how African countries can strengthen their macroeconomic policies and structural reforms in order to achieve globalization of their economies. In addition, this study evaluates the current state and future direction of globalization in Africa

A Glance at Tropical Operations and Tropical Linear Algebra

The tropical semiring is ℝ ∪ {∞} with the operations x ⊕ y = min{x, y}, x ⊕ ∞ = ∞ ⊕ x = x, x ⊙ y = x + y, x ⊙ ∞ = ∞ ⊙ y = ∞. This paper explores how ideas from classical algebra and linear algebra over the real numbers such as polynomials, roots of polynomials, lines, matrices and matrix operations, determinants, eigen values and eigen vectors would appear in tropical mathematics. It uses numerous computed examples to illustrate these concepts and explores the relationship between certain tropical matrices and graph theory, using this to provide proofs of some tropical computations

Modeling Financial Swaps and Geophysical data Using the Barndorff-Nielsen and Shephard Model

This dissertation uses Barndoff-Nielsen and Shephard (BN-S) models to model swap, a type of financial derivative, and analyze geophysical data for estimation of major earthquakes. From empirical observation of the stock market activity and earthquake occurrence, we observe that the distributions have high kurtosis and right skewness. Consequently, such data cannot be captured by stochastic models driven by a Wiener process. Non-Gaussian processes of Ornstein-Uhlenbeck type are one of the most significant candidates for being the building blocks of models of financial economics. These models offer the possibility of capturing important distributional deviations from Gaussianity and thus these are more practical models of dependence structures. Introduced by Barndorff-Nielsen and Shephard these processes are not only convenient to model volatility in financial market, but have an independent interest for modeling stationary time series of various kinds. For the financial data we use BN-S models to price the arbitrage-free value of volatility, variance, covariance, and correlation swap. Such swaps are used in financial markets for volatility hedging and speculation. We use the S&P500 and NASDAQ index for parameter estimation and numerical analysis. We show that with this model the error estimation in fitting the delivery price is much less than the existing models with comparable parameters. For any given time interval, the earthquake magnitude data have three main properties: (1) magnitude is a non-negative stationary stochastic process; (2) for any finite interval of time there are only finite number of jumps; (3) the sample path of the magnitude of an earthquake consists of upward jumps (significant earthquake) and a gradual decrease (aftershocks). For such geophysical data we specifically use Gamma Ornstein Uhlenbeck processes driven by a Levy process to estimate a major earthquake in a certain region in California. Rigorous regression analysis is provided, and based on that, first-passage times are computed for different sets of data. Both applications demonstrate the significance of BN-S models to phenomena that follow non-Gaussian distributions

Predicting suicide risk from online postings in Reddit : the UGent-IDLab submission to the CLPysch 2019 Shared Task A

This paper describes IDLab’s text classification systems submitted to Task A as part of the CLPsych 2019 shared task. The aim of this shared task was to develop automated systems that predict the degree of suicide risk of people based on their posts on Reddit. Bag-of-words features, emotion features and post level predictions are used to derive user-level predictions. Linear models and ensembles of these models are used to predict final scores. We find that predicting fine-grained risk levels is much more difficult than flagging potentially at-risk users. Furthermore, we do not find clear added value from building richer ensembles compared to simple baselines, given the available training data and the nature of the prediction task

The Implementation of Training and Development Programs in Civil Service Institutions of Oromia National Regional State, Ethiopia

The role of civil service in socio-economic and political development of a country is unquestionable. In some countries, however, the civil service is not aligned with the prevailing ideological, political and economic changes as well as management theories. Moreover, in some countries, especially in Africa, the civil service is blamed as a major cause for social and political upheavals and economic crises because of institutional and capacity weakness. As a result, it is common to see many countries engaged in the reform of their civil service. In 1991, Ethiopia experienced political changes that resulted in the introduction of multi-party system, market-oriented economy and federal form of government. Accordingly, the government introduced civil service reform that includes the issues of human resource development under human resource management reform since 1996.  Studies revealed, however, that the implementation process was not going well. This article, therefore, aims to assess the implementation of training and development programs in civil service institutions of Oromia National Regional State in Ethiopia. The findings reveal that though the government is committed in developing a system of human resource development, the implementation is not on the right track to fill the skill gaps evident in the civil service