İrfan EMRE, Osman GEDİK, Murat KURŞAT, Yaşar KIRAN

Karyotype Analysis of Lallemantia Fisch. & C.A.Mey. Species Grown in Turkey: A Detailed Karyotype Asymmetry Study

The study aimed to karyologically analyse three Lallemantia species [L. peltata, L. iberica Mey. and L. canescens] grown in Turkey. Also, it was calculated various karyotype asymmetry and S/AI, CVCL and MC values in this study. Current study found that the chromosome numbers are 2n=14 and they possess median (m) and submedian (sm) centromere. In addition, this study suggested that three Lallemantia species are 2A group based on Stebbins classifications. Furthermore, present study showed Pearson correlation using karyotype asymmetry values and a scatter diagram was formed using A1 and A2. On the other hand, the results obtained from the study were compared with the results of karyotype analysis performed by different literatures and it was concluded that there may be differences according to locality.

Anahtar Kelimeler:

Chromosome, Lallemantia, Karyotype, Asymmetry, Stebbins Classification

Investigation of Cloud Computing Based Big Data on Machine Learning Algorithms.

Cloud computing technology is a model that allows access to a common pool of configurable computing resources whenever and wherever. With the developing technology, the use of this model is increasing day by day. There are many benefits of cloud computing to its users. The data that users keep in their data sets is the simplest example of this. With the cloud technology, the size of the data stored in databases is also increasing. For this reason, cloud technology and big data concepts are intertwined due to the large amount of data stored in databases. It is of great importance that the obtained data is evaluated by machine learning methods and produces results that can be used for technical and commercial purposes. In this study, first of all, cloud technology, the big data brought by this technology and the classification of these data with machine learning methods and algorithms have been examined. Then the studies in the literature were evaluated.

Keywords:

Big Data, Cloud Computing, Resource Allocation, Machine Learning.,

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