ZnS nanoparticles were prepared by a simple microwave irradiation method under mild condition. The starting materials for the synthesis of ZnS quantum dots were zinc acetate (R & M Chemical) as zinc source, thioacetamide as a sulfur source and ethylene glycol as a solvent. All chemicals were analytical grade products and used without further purification. The quantum dots of ZnS with cubic structure were characterized by X-ray powder diffraction (XRD), the morphology of the film is seen by scanning electron microscopy (SEM). The particle size is determined by field effect scanning electron microscopy (FESEM), UV-Visible absorption spectroscopy and XRD. UV-Visible absorption spectroscopy analysis shows that the absorption peak of the as-prepared ZnS sample (310 nm) displays a blue-shift comparing to the bulk ZnS (345 nm). Photoluminescence spectra of the samples revealed a broad peak centered at 404nm, which were related to excitonic emission. Photocatalytic degradation of Methylene Blue (MB) dye catalyzed by synthesized nanoparticles was studied under solar radiation, photocatalytic degradation increased with increasing time exposure to solar light.
A new ligand complexes have been synthesis from reaction of metal ions of Mn(II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II), Hg(II), Pd(II) and Pt(II) with schiff base LH. 5-[(2-Hydroxy-naphthalen-1-ylmethylene)-amino]-2-phenyl-2,4-dihydro-pyrazol-3-one, this ligand was characterized by Fourier transform infrared (FTIR), UV-vis, 1H, 13CNMR, and mass spectra. All complexes were characterized by techniques micro analysis C.H.N, UV-vis and FTIR spectral studies, atomic absorption, chloride content, molar conductivity measurements and magnetic susceptibility. The ligand acts as bidentate, coordination through nitrogen atom from azomethin group and deprotonated phenolic oxygen atom. The spectroscopic and analytical measurements showed that
... Show MoreA new Schiff base [1-((2-(1H-indol-3-yl)ethylimino)methyl)naphthalene-2-ol] (HL) has been synthesized by condensing (2-hydroxy-1-naphthaldehyde) with (2-(1H-indol-3-yl)ethylamine). In turn, its transition metal complexes were prepared having the general formula; [Pt(IV)Cl2(L)2], [Re(V)Cl2(L)2]Cl and [Pd(L)2], 2K[M(II)Cl2(L)2] where M(II) = Co, Ni, Cu] are reported. Ligand as well as metal complexes are characterized by spectroscopic techniques such as FT-IR, UV-visible, 13C & 1H NMR, mass, elemental analysis. The results suggested that the ligand behaves like a bidentate ligand for all the synthesized complexes. On the other hand, theoretical studies of the ligand as well its metal complexes were conducted at gas phase using Hyp
... Show More
(27)
(10)
CNC machine is used to machine complex or simple shapes at higher speed with maximum accuracy and minimum error. In this paper a previously designed CNC control system is used to machine ellipses and polylines. The sample needs to be machined is drawn by using one of the drawing software like AUTOCAD® or 3D MAX and is saved in a well-known file format (DXF) then that file is fed to the CNC machine controller by the CNC operator then that part will be machined by the CNC machine. The CNC controller using developed algorithms that reads the DXF file feeds to the machine, extracts the shapes from the file and generates commands to move the CNC machine axes so that these shapes can be machined.
This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance
... Show More
(4)
(2)
The microbend sensor is designed to experience a light loss when force is applied to the sensor. The periodic microbends cause propagating light to couple into higher order modes, the existing higher order modes become unguided modes. Three models of deform cells are fabricated at (3, 5, 8) mm pitchand tested by using MMF and laser source at 850 nm. The maximum output power of (8, 5, 3)mm model is (3, 2.7, 2.55)nW respectively at applied force 5N and the minimum value is (1.9, 1.65, 1.5)nW respectively at 60N.The strain is calculated at different microbend cells ,and the best sensitivity of this sensor for cell 8mm is equal to 0.6nW/N.
(3)
(1)
Aspect-based sentiment analysis is the most important research topic conducted to extract and categorize aspect-terms from online reviews. Recent efforts have shown that topic modelling is vigorously used for this task. In this paper, we integrated word embedding into collapsed Gibbs sampling in Latent Dirichlet Allocation (LDA). Specifically, the conditional distribution in the topic model is improved using the word embedding model that was trained against (customer review) training dataset. Semantic similarity (cosine measure) was leveraged to distribute the aspect-terms to their related aspect-category cognitively. The experiment was conducted to extract and categorize the aspect terms from SemEval 2014 dataset.
(5)
(3)
This study aims to demonstrate the role of artificial intelligence and metaverse techniques, mainly logistical Regression, in reducing earnings management in Iraqi private banks. Synthetic intelligence approaches have shown the capability to detect irregularities in financial statements and mitigate the practice of earnings management. In contrast, many privately owned banks in Iraq historically relied on manual processes involving pen and paper for recording and posting financial information in their accounting records. However, the banking sector in Iraq has undergone technological advancements, leading to the Automation of most banking operations. Conventional audit techniques have become outdated due to factors such as the accuracy of d
... Show More
(1)
(8)
(65)
(59)
Objectives. The current study aimed to predict the combined mesiodistal crown widths of maxillary and mandibular canines and premolars from the combined mesiodistal crown widths of maxillary and mandibular incisors and first molars. Materials and Methods. This retrospective study utilized 120 dental models from Iraqi Arab young adult subjects with normal dental relationships. The mesiodistal crown widths of all teeth (except the second molars) were measured at the level of contact points using digital electronic calipers. The relation between the sum mesiodistal crown widths of the maxillary and mandibular incisors and first molars and the combined mesiodistal crown widths of the maxillary and mandibular canines and premolars was as
... Show More
(4)
(3)
This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as
... Show More