High performance self-consolidating concrete HP-SCC is one of the most complex types of concrete which have the capacity to consolidated under its own weight, have excellent homogeneity and high durability. This study aims to focus on the possibility of using industrial by-products like Silica fumes SF in the preparation of HP-SCC enhanced with discrete steel fibers (DSF) and monofilament polypropylene fibers (PPF). From experimental results, it was found that using DSF with volume fraction of 0.50 %; a highly improvements were gained in the mechanical properties of HP-SCC. The compressive strength, splitting tensile strength, flexural strength and elastic modulus improved about 65.7 %, 70.5 %, 41.7 % and 80.3 % at 28 days age, respectively with retaining the main properties of HP-SCC. Furthermore, using PPF with volume fraction up to 0.10 %; an enhancement in the compressive and elastic modulus of HP-SCC about 47.4 % and 31 % was obtained at age of 28 days, respectively. Moreover, using PPF with volume fraction of 0.15 %, the splitting tensile strength and flexural strength of HP-SCC improved about 44.5 % and 20.3 %, respectively.
Many faces are exposed to degradation, discoloration, changes in humidity. The primary objective has improved some properties of hybrid nanocomposites materials that used for restoring of the function maxillofacial prosthesis and improving the esthetic. In the present research different lengths chopped and continuous of ultrahigh molecular weight polyethylene (UHMWPE) fiber was added at selected percentage (0.0, 0.2% and 1%) to polymer blend composite (95%SR /5%PMMA: 0.2% Pomegranate Peels Powder (PPP)) for developing the properties of silicone rubber used for the maxillofacial prosthesis applications. Some mechanical and physical properties were done on the all prepared samples. The results showed that all properties have improved when add
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ZnO nanostructures were synthesized by hydrothermal method at different temperatures and growth times. The effect of increasing the temperature on structural and optical properties of ZnO were analyzed and discussed. The prepared ZnO nanostructures were characterized by X-ray diffraction (XRD), UV–Vis. absorption spectroscopy (UV–Vis.), Photoluminescence (PL), and scanning electron microscopy (SEM). In this work, hexagonal crystal structure prepared ZnO nanostructures was observed using X-ray diffraction (XRD) and the average crystallite size equal 14.7 and 23.8 nm for samples synthesized at growth time 7 and 8 hours respectively. A nanotubes-shaped surface morphology was found using scanning electron microscopy (SEM). The optic
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In this work, yttrium oxide particles (powder) reinforced AL-Si matrix composites (Y2O3/Al-Si) and Chromium oxide particles reinforced AL-Si matrix composites (Cr2O3/AL-Si) were prepared by direct squeeze casting. The volume percentages of yttrium oxide used are (4, 8.1, 12.1, 16.1 vol %) and the volume percentages of the chromium oxide particles used are (3.1, 6.3, 9.4, 12.5 vol. %). The parameters affecting the preparation of Y2O3/Al-Si and Cr2O3/AL-Si composites by direct squeeze casting process were studied. The molten Al-Si alloy with yttrium oxide particles or with chromium oxide particles was stirred again using an electrical stirrer at speed 500 rpm and the molten alloy was poured into the squeeze die cavity. Th
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ABSTRACT Background: Piezosurgery device is a system developed recently to overcome the limitation of the traditional surgical technique in implant site preparation, which use the principle of ultrasonic microvibrations to create precise & selective cut in bone in harmony with the surrounding tissues. The aim of this study was to evaluate the outcomes of implants inserted by ultrasonic implant site preparation protocol (UISP) using piezosurgery device, regarding the survival rate, stability and other related factors, at 16 weeks postoperative follow up period. Materials and Methods: A total of (24) patients, (6) males and (18) females, aged between (19-51) years old, contributed in this study receiving a total of (42) implants, all of these
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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Survival analysis is widely applied to data that described by the length of time until the occurrence of an event under interest such as death or other important events. The purpose of this paper is to use the dynamic methodology which provides a flexible method, especially in the analysis of discrete survival time, to estimate the effect of covariate variables through time in the survival analysis on dialysis patients with kidney failure until death occurs. Where the estimations process is completely based on the Bayes approach by using two estimation methods: the maximum A Posterior (MAP) involved with Iteratively Weighted Kalman Filter Smoothing (IWKFS) and in combination with the Expectation Maximization (EM) algorithm. While the other
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In this paper normal self-injective hyperrings are introduced and studied. Some new relations between this concept and essential hyperideal, dense hyperideal, and divisible hyperring are studied.