In the recent years, remote sensing applications have a great interest because it's offers many advantages, benefits and possibilities for the applications that using this concept, satellite it's one must important applications for remote sensing, it's provide us with multispectral images allow as study many problems like changing in ecological cover or biodiversity for earth surfers, and illustrated biological diversity of the studied areas by the presentation of the different areas of the scene taken depending on the length of the characteristic wave, Thresholding it's a common used operation for image segmentation, it's seek to extract a monochrome image from gray image by segment this image to two region (for

In this paper ,six new mixed metal ligand complexes are reported with Cephalexin (Ceph.H)as a primary ligand and Dimethylglyoxime (DMG) as secondary ligand with metal Chloride [MCl2 .nH2O. M=Mn(II),Co(II),Cu(II),Ni(II) and Zn(II),n=0-6] ,CrCl3.6H2O.The complexes are of (1:1:1)(Metal:Ligand: Ligand) Stoichiometry.The structures of these complexes are confirmed by using FT-IR and UV- electronic spectroscopies, magnetic moments, melting points, molar conductivity measurements and the metal % analysis revealed that the complexes analyze indicates a four coordinated as (A)=[M(HDMG) (Ceph)] .M=[Ni(II)and Zn(II).Six coordinated as (B) = K2[M(DMG)(CePh)(H2O)]. M= Mn (II),Co(II) and Cu(II) and (C)=[Cr(DMG)(Ceph)]Cl2. Interestingly, the in-vitro anti

This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it

   The technology of reducing dimensions and choosing variables are very important topics in statistical analysis to multivariate. When two or more of the predictor variables are linked in the complete or incomplete regression relationships, a problem of multicollinearity are occurred which consist of the breach of one basic assumptions of the ordinary least squares method with incorrect estimates results.

 There are several methods proposed to address this problem, including the partial least squares (PLS), used to reduce dimensional regression analysis. By using linear transformations that convert a set of variables associated with a high link to a set of new independent variables and unr

Activity test of the inhibitors purified from barley and broad beans crop proved the inhibition activity against 6 types of rots Pencillium ssp and Aspergellusflavus and Aspergillus niger and Fusarium solani and Fusarium semitectum and Mucor with three concentrations 0.1 and 0.2 and 0.3 mg/ml, where the inhibitor purified from the second peak of broad beans proved that it had a higher inhibition activity against the growth of test rots which were 53.75 and 62.5 and 78.5 and 76.25 and 84 and 18.8% respectively, at 0.3 mg/ ml followed by the first peak of the inhibitor purified from broad beans the inhibition activity were 43.75 and 50 and 62.96 and 75 and 80 and 12.5 then the inhibitor purified from barley in which the inhibition activity

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In this study, the antimicrobial properties of newly synthesized Schiff bases (4a-4e) and thiazolidinone compounds (5a-5e) generated from 3,5-dinitrobenzoic acid were assessed. These compounds were obtained by reacting 3,5-dinitrobenzoic acid (1) with ethanol in a few drops of concentrated H2SO4 to produce the ester (2). The acid hydrazide (3), which was produced by treating the ester with hydrazine hydrate, reacted with the proper aldehydes, including 4-bromobenzaldehyde, 4-chlorobenzaldehyde, 4-hydroxybenzaldehyde, 4-methoxybenzaldehyde, and 4-hydroxy-3-methoxybenzaldehyde, respectively, to form Schiff bases (4a-4e). The thiazolidinone compounds (5a-5e) were produced by the cyclocondensation reaction of compounds (4a-4e) with thio

In this study, the antimicrobial properties of newly synthesized Schiff bases (4a-4e) and thiazolidinone compounds (5a-5e) generated from 3,5-dinitrobenzoic acid were assessed. These compounds were obtained by reacting 3,5-dinitrobenzoic acid (1) with ethanol in a few drops of concentrated H2SO4 to produce the ester (2). The acid hydrazide (3), which was produced by treating the ester with hydrazine hydrate, reacted with the proper aldehydes, including 4-bromobenzaldehyde, 4-chlorobenzaldehyde, 4-hydroxybenzaldehyde, 4-methoxybenzaldehyde, and 4-hydroxy-3-methoxybenzaldehyde, respectively, to form Schiff bases (4a-4e). The thiazolidinone compounds (5a-5e) were produced by the cyclocondensation reaction of compounds (4a-4e) with thio

    Language contains various kinds of grammatical rules that are used to express thoughts and feelings. The present paper studies some of the German language grammatical rules as being the most important basics needed to master and develop the art of writing for the German language learners. Writing is one of the productive language learning skills that transform thoughts into a written form. Hence, constant exercising on the use of the language to master the grammatical rules enables German language learners to develop their creative writing skills.

     The present study discusses the importance of grammatical exercises in developing the language learning abilities. The study provides a gener

Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr