Our recent work displays the successful preparation of Schiff_bases that carried out between hexane-2,5-dione and 2 moles of (Z)-3-hydrazineylideneindolin-2-one forming in Schiff-bases-(L), Which in turn allowed combining with each of the next metal ions: (M²⁺) = Ni, Mn, Zn, Cu and Co forming complexes_ in high stability. The formation of resulting Schiff_ bases (L) is detected spectrally using LC_Mss which gave approximately matching results with theoretical incomes, ¹HNMR proves the founding of doublet signal of (2H) for 2NH, FTIR indicates the occurrence of two interfered imine bands and UV-VIS mean is also indecates the formation of ligand. On the other hand, complexes-based-Schiff were characterized using the s

This project aims to fabricate nanostructures (AgNPS) using the  electrical exploding wire (EEW) technique using Rhodamine 6G dye as the probe molecule, investigate the effect of AgNPS on the absorption spectra and surface-enhanced Raman scattering (SERS) activities, and advance  using porous silicon as an active substrate for surface-enhanced Raman scattering (SERS). X-Ray diffraction (XRD) was used to investigate the structural properties of the nanostructures (AgNPs). Field emission scanning electron microscopy (FE-SEM) was used to investigate surface morphology. A double beam UV-Vis Spectrophotometer was used to analyze the mixed R6G laser dye(of concentration 1x  M)  absorption spectra with the nanostructures AgNPS (of concentra

We studied the effect of certain environmental conditions for removing heavy metal elements from contaminated aqueous solutions (Cd, Cu, Pb, Fe, Zn, Ni, Cr) using the bacterium Bacillus subtilis to appoint the optimal conditions for removal ,The best optimum temperature range for two isolate was 30-35○C while the hydrogen number for the maximum mineral removal range was 6-7. The best primary mineral removal was 100 mg/L, while the maximum removal for all minerals was obtained after 6 hrs of Cu element time and the maximum removal efficiency was obtained after 24 hrs of Cu element. The results have proved that the best aeration for maximum removal was obtained at rotation speed of 150 rpm/minute. Inoculums of 5ml/100ml which contained 1

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 designer must find the optimum match between the object's technical and economic needs and the performance and production requirements of the various material options when choosing material for an engineering application. This study proposes an integrated (hybrid) strategy for selecting the optimal material for an engineering design depending on design requirements. The primary objective is to determine the best candidate material for the drone wings based on Ashby's performance indices and then rank the result using a grey relational technique with the entropy weight method. Aluminum alloys, titanium alloys, composites, and wood have been suggested as suitable materials for manufacturing drone wings. The requirement

     Lately, a growing interest has been emerging in age estimation from face images because of the wide range of potential implementations in law enforcement, security control, and human computer interactions. Nevertheless, in spite of the advances in age estimation, it is still a challenging issue. This is due to the fact that face aging process is not only set by distinct elements, such as genetic factors, but by extrinsic factors, such as lifestyle, expressions, and environment as well. This paper applied machine learning technique to intelligent age estimation from facial images using J48 classifier on FG_NET dataset. The proposed work consists of three phases; the first phase is image preprocessing which include

As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detec