Improved secondary education is essential to the creation of effective human capital in any country (Evoh, 2007). The need for ICT in Nigerian higher schools cannot be overemphasized. Unfortunately, many developing counties, especially in Africa, are still low in ICT application and use .This paper focuses on ICT application in Nigerian higher schools. It particularly dwells on the importance of ICT and the causes of low levels of ICT application in Nigerian secondary schools. Recommendations for improvement are offered

The paper provides a good alternative method for quadratic fractional programming problem (QFPP) concern with non-linear programming problem (NLPP) because the technique is useful to apply on numerical problems, reduces the labor work and save valuable time.

The aim of this paper is to introduce a new class of closed sets in topological spaces called π^g-closed sets and obtain some of its characteristics. Also, the concept of continuity called   π^g-continuity is defined and obtained some of its properties.

One of the most successful approaches to obtain hedging with transaction cost is the utility based approach pioneered by Hodges and Neuberger (1989). Judging against the best possible trade off between the risk and cost of hedging strategy, this approach seems to achieve excellent empirical performance. However, the approach has one major drawback that prevents the broad application  of it in practice, which is lack of rehedging  function calibrated when the hedge ratio moves outside the prescribed tolerance. We overcome this draw back by presenting a simple efficient rehedging model and some other well known strategies and find that our model outperforms all others..

Data science algorithms are on the way to becoming an integral part of every company, and we can already see the effects in many corporations that have invented their own data science teams and also implemented the latest data science algorithms. To be able to work with all the different challenges that are emerging, new powerful data science tools have been developed (e.g. Python, R, H2O, Weka, Tensorflow, Spark, Flink, BigML or KNIME). One balance that companies that want to use these new tools have to face is the cost of implementation vs. the enhanced development that they give in return. Nowadays, most of the advanced algorithms are open source and available on multiple platforms and programming languages, which helps to minimize the development cost challenges that each company has to overcome.

Still, one of the main dangers lurking inside these development teams is that they do not know what the state of the art of advanced algorithms is and which problem they can address. To help mitigate this problem, a review of algorithms has been implemented in this paper. This review gives us a perspective on which algorithms are being developed and which problem areas they can address. With the development of more powerful data science algorithms, we are also enabling the possibility of tackling more complex and interesting problems. However, one characteristic of the review is that there are missing algorithms from the many that are currently being produced and frequently selected by the community as the best performers in many benchmark datasets.