Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

Wheat straw was modified with malonic acid in order to get low cost adsorbent have a good ability to remove copper and ferric ions from aqueous solutions, chemical modification temperature was 120°C and the time was 12 h. Parameters that affect the adsorption experiments were studied and found the optimum pH were 6 and 5 for copper and iron respectively and the time interval was 120 min and the adsorbent mass was 0.1 g. The values for adsorption isotherms parameters were determined according to Langmuir [qmax were 54.64 and 61.7 mg/g while b values were 0.234 and 0.22 mg/l] , Freundlich [Kf were 16.07 and 18.89 mg/g and n were 2.77 and 3.16], Temkin [B were 0.063 and 0.074 j/mol and At were 0.143 and 1.658 l/g] and for Dubinin-Radushkev

          Aleppo bentonite was investigated to remove ciprofloxacin hydrochloride from aqueous solution. Batch adsorption experiments were conducted to study the several factors affecting the removal process, including contact time, pH of solution, bentonite dosage, ion strength, and temperature. The optimum contact time, pH of solution and bentonite dosage were determined to be 60 minutes, 6 and 0.15 g/50 ml, respectively. The bentonite efficiency in removing CIP decreased from 89.9% to 53.21% with increasing Ionic strength from 0 to 500mM, and it increased from 89% to 96.9% when the temperature increased from 298 to 318 K. Kinetic studies showed that the pseudo second-order model was the best in describing  the adsorption sys

Mixed ligand complexes of bivalent metal ions, viz; M= Fe(II),Co(II),Ni(II),Cu(II), Zn(II), Cd (II), and Hg(II) of the composition Na2[M (Amox)(Sac)3] in 1:1:3 molar ratio, (where Amox = Amoxicillin tryhydrate (C16H19N3O5S.H2O) and Sac = Saccharine(C7H5NO3S) have been synthesized and characterized by repeated melting point determination, Solubility, Molar conductivity, determination the percentage of the metal in the complexes by flame(AAS), FT-IR, magnetic susceptibility measurements and electronic spectral data. The ligands and their metal complexes have been screened for their biological activity against selected microbial strains (gram +ve) and (gram -ve).

Mixed ligand complexes of bivalent metal ions, viz; M= Fe(II),Co(II),Ni(II),Cu(II), Zn(II), Cd (II), and Hg(II) of the composition Na2[M (Amox)(Sac)3] in 1:1:3 molar ratio, (where Amox = Amoxicillin tryhydrate (C16H19N3O5S.H2O) and Sac = Saccharine(C7H5NO3S) have been synthesized and characterized by repeated melting point determination, Solubility, Molar conductivity, determination the percentage of the metal in the complexes by flame(AAS), FT-IR, magnetic susceptibility measurements and electronic spectral data. The ligands and their metal complexes have been screened for their biological activity against selected microbial strains (gram +ve) and (gram -ve).

EM International