Semiconductor quantum dots (QDs) have attracted tremendous attentions for their unique characteristics for solid-state lighting and thin-film display applications. A simple chemical method was used to synthesis quantum dots (QDs) of zinc sulfide (ZnS) with low cost. The XRD) shows cubic phase of the prepared ZnS with an average particles size of (3-29) nm. In UV-Vis. spectra observed a large blue shift over 38 nm. The band gaps energy (Eg) was 3.8 eV and 3.37eV from the absorption and photoluminescence (PL) respectively which larger than the Eg for bulk. QDs-LED hybrid devices were fabricated using ITO/ PEDOT: PSS/ Poly-TPD/ ZnS-QDs/ with different electron transport layers and cathode of LiF/Al layers. The EL spectrum reveals a bro

Addition of bioactive materials such as Titanium oxide (TiO₂), and incorporation of bio inert ceramic such as alumina (Al₂O₃), into polyetheretherketone (PEEK) has been adopted as an effective approach to improve bone-implant interfaces. In this paper, hot pressing technique has been adopted as a production method. This technique gave a homogenous distribution of the additive materials in the proposed composite biomaterial. Different compositions and compounding temperatures have been applied to all samples. Mechanical properties and animal model have been studied in all different production conditions. The results of these new TiO₂/Al₂O₃/PEEK biocomposites with different

This paper proposes a new methodology for improving network security by introducing an optimised hybrid intrusion detection system (IDS) framework solution as a middle layer between the end devices. It considers the difficulty of updating databases to uncover new threats that plague firewalls and detection systems, in addition to big data challenges. The proposed framework introduces a supervised network IDS based on a deep learning technique of convolutional neural networks (CNN) using the UNSW-NB15 dataset. It implements recursive feature elimination (RFE) with extreme gradient boosting (XGB) to reduce resource and time consumption. Additionally, it reduces bias toward

This article presents a polynomial-based image compression scheme, which consists of using the color model (YUV) to represent color contents and using two-dimensional polynomial coding (first-order) with variable block size according to correlation between neighbor pixels. The residual part of the polynomial for all bands is analyzed into two parts, most important (big) part, and least important (small) parts. Due to the significant subjective importance of the big group; lossless compression (based on Run-Length spatial coding) is used to represent it. Furthermore, a lossy compression system scheme is utilized to approximately represent the small group; it is based on an error-limited adaptive coding system and using the transform codin

This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

The research stems from its goal of identifying the impact of visual management on the strategic acceleration of business organizations and the state of this effect through the knowledge embedding in the Iraqi oil companies. The oil sector was tested, represented by (3) oil companies, and a sample of (151) individuals who participated in activating the visual management, distributed in higher management levels. The research relied on the descriptiveanalytical approach and the questionnaire was a main tool for collecting data and information. The results showed that visual management positively affects strategic acceleration. Moreover, This effect is amplified by the mediating role played by Embedding Knowledge.

This study seeks to shed light on the aspects of visual pollution and its impact on the aesthetics of the town of Al-Eizariya known to suffer from the phenomenon. In order to identify the real causes of the problem which develops in various forms and patterns, threatening not only the aesthetic appearance of the towns, but also causes the emergence of new problems and phenomena that will have negative repercussions on the population. The researcher uses the analytical descriptive method to analyze the phenomenon of visual pollution in terms of reality, development, manifestations and spread and uses photos which document the visual pollution and its impact on the aesthetics of the known. The study concluded the existence of a strong rela

The extract of fig fruit has shown significant medical usefulness in various fields. The entrance of nanotechnology into the field of medicinal and pharmacology has shown remarkable advantages. Plants contain diverse molecules thatcan reduce metals, and provide a safe, eco-friendly approach for synthesizing nanoparticles. Iron oxide nanoparticles (IONPs) have been reported to possess an antimicrobial effect against some strains of bacteria and moulds. We have aimed to synthesize IONPs from fig fruit extract and investigate the influence of fig extract and IONPs in wound healing of mice. UV-Vis spectroscopy, X-ray diffraction (XRD), and field emission scanning electron microscopy were used to characterize the IONPs that were produced