Text Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as t

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

This study is aimed to Green-synthesize and characterize Al NPs from Clove (Syzygium aromaticum
L.) buds plant extract and to investigate their effect on isolated and characterized Salmonella enterica growth.
S. aromaticum buds aqueous extract was prepared from local market clove, then mixed with Aluminum nitrate
Al(NO3)3. 9 H2O, 99.9% in ¼ ratio for green-synthesizing of Al NPs. Color change was a primary confirmation
of Al NPs biosynthesis. The biosynthesized nanoparticles were identified and characterized by AFM, SEM,
EDX and UV–Visible spectrophotometer. AFM data recorded 122nm particles size and the surface roughness
RMs) of the pure S. aromaticum buds aqueous extract recorded 17.5nm particles s

In this work, multilayer nanostructures were prepared from two metal oxide thin films by dc reactive magnetron sputtering technique. These metal oxide were nickel oxide (NiO) and titanium dioxide (TiO2). The prepared nanostructures showed high structural purity as confirmed by the spectroscopic and structural characterization tests, mainly FTIR, XRD and EDX. This feature may be attributed to the fine control of operation parameters of dc reactive magnetron sputtering system as well as the preparation conditions using the same system. The nanostructures prepared in this work can be successfully used for the fabrication of nanodevices for photonics and optoelectronics requiring highly-pure nanomaterials.

The analysis of Iraqi light oil (light naphtha) by capillary gas chromatography- mass spectrometry (GC-MS) was performed by the injection of whole naphtha sample without use of solvents. Qualitative analysis and the identification of the hydrocarbon constituents of light naphtha was performed and comparison had been done with American light oil (light naphtha). The obtained results showed a major difference between the two-light naphtha.

The insulation system of a machine coil includes several layers made of materials with different characteristics. The effective insulation design of machine coils, especially in the machine end winding, depends upon an accurate model of the stress grading system. This paper proposes a modeling approach to predict the transient overvoltage, electric field, and heat generation in machine coils with a stress grading system, considering the variation of physical properties in the insulation layers. A non-uniform line model is used to divide the coil in different segments based on material properties and lengths: overhang, stress grading and slot. The cascaded connection of chain matrices is used to connect segments for the representation of the