Mehmet C. Okur

Big data challenges in information engineering curriculum

The amount of accumulated data is growing at unprecedented rates. This data is mainly unstructured or semi structured and comes from different sources in a variety of forms. Recently, a range of supporting storage and distributed parallel computing technologies have been developed and put into use by the sector.The products and implementations include; Apaches Hadoop, data processing framework Map Reduce, distributed big data management system Cassandra and other NoSQL database and data storage systems. Among the major challenges are; data representation, reliable shared storage, efficient algorithms and scalable distributed HW/SW infrastructures. Surprisingly, current curricula lack the necessary components to create awareness and a good understanding of these state of the art concepts and technologies. There is an urgent need for integrating the developments in big data technologies into the educational programs and computing curricula. This need not only is dictated by the industry, but also by the employement dynamics in the related professions. This paper discusses fundemental big data issues and technologies that are considered to be necessary for the existing educational programs in computing, information systems and information engineering areas.

Metadata and Semantic Research

Reading a book is also kind of better solution when you have no enough money or time to get your own adventure. This is one of the reasons we show the metadata and semantic research 5th international conference mtsr 2011 izmir turkey october 12 14 as your friend in spending the time. For more representative collections, this book not only offers its strategically book resource. It can be a good friend, really good friend with much knowledge.

On fitting the generalized λ-distribution to air pollution data

Abstract The generalized λ-distribution is a four-parameter flexible probability model which includes a wide variety of univariate distributions. This model can be used to represent frequency distributions of air pollutant concentrations. In this paper, it is demonstrated by means of daily smoke and SO 2 data from Ankara, Turkey, that the generalized λ-distribution has good fitting properties. Some results concerning quantite estimation and goodness-of-fit are also discussed and comparisons with classical lognormal distribution are carried out.

A Monte Carlo Evaluation of the Methods for Estimating the Parameters of the Generalized Lambda Distribution

This paper presents the results of a Monte Carlo study concerning the problems of parameter estimation in the generalized lambda, distribution. Statistical properties of estimates obtained by using four available methods are contrasted and it is concluded that the exact least squares procedure performs better than the other methods.