Aromatic Schiff-bases are known to have antibacterial activity, but most of these compounds are sparingly soluble in water. The present work describes the synthesis of new Schiff-bases derived from branched aminosugars. Treatment of 3-Amino-3-Cyano-3-Deoxy-1,2:5,6-Di-O-Isopropylene-α-D-Allofuranose (1) with the aldehydes (2) under reflux in methanol afforded the Schiff-bases (3) in good yields. The new Schiff-bases were in accord with their NMR, IR spectral data and elemental analysis.

Stable new derivative (L) Bis[O,O-2,3;O,O-5,6(carboxylic methyliden)]L-ascorbic acid was synthesized in good yield by the reaction of L-ascorbic acid with dichloroacetic acid with ratio (1:2) in presence of potassium hydroxide. The new (L) was characterized by 1H,13C-NMR, elemental analysis (C,H) and Fourier Transform Infrared (FTIR). The complexes of the ligand (L) with metal ion, M+2= (Cu, Co, Ni, Cd and Hg) were synthesized and characterized by FTIR, UV-Visible, Molar conductance, Atomic absorption and the Molar ratio. The analysis evidence showed the binding of the metal ions with (L) through bicarboxylato group manner resulting in six-coordinated metal ion.

The density-based spatial clustering for applications with noise (DBSCAN) is one of the most popular applications of clustering in data mining, and it is used to identify useful patterns and interesting distributions in the underlying data. Aggregation methods for classifying nonlinear aggregated data. In particular, DNA methylations, gene expression. That show the differentially skewed by distance sites and grouped nonlinearly by cancer daisies and the change Situations for gene excretion on it. Under these conditions, DBSCAN is expected to have a desirable clustering feature i that can be used to show the results of the changes. This research reviews the DBSCAN and compares its performance with other algorithms, such as the tradit

In this paper, preliminary test Shrinkage estimator have been considered for estimating the shape parameter α of pareto distribution when the scale parameter equal to the smallest loss and when a prior estimate α0 of α is available as initial value from the past experiences or from quaintance cases. The proposed estimator is shown to have a smaller mean squared error in a region around α0 when comparison with usual and existing estimators.

In recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor

   The notions Ǐ­semi­g­closedness and Ǐ­semi­g­openness were used to generalize and introduced new classes of separation axioms in ideal spaces. Many relations among several sorts of these classes are summarized, also.