The prostheses sockets use normally composite materials which means that their applications may be related with the human body. Therefore, it was very necessary to improve the mechanical properties of these materials. The prosthetic sockets are subjected to varying stresses in gait cycle scenario which may cause a fatigue damage. Therefore, it is necessary or this work to modify the fatigue behavior of the materials used for manufacturing the prostheses sockets. In this work, different Nano particle materials are used to modify the mechanical properties of the composite materials, and increase the fatigue strength. By using an experimental technique, the effect of using different volume fractions for various types for Nano particle materials on the fatigue behavior for composite materials, and preparing the fatigue samples and tested using the fatigue apparatus. The Nano particles used were (Nano SiO2 and Nano Al2O3) materials with volume fraction as (0% to 2%), for each type of Nano material used. The artificial neural network technique was adopted to have a verification for the experimental results and calculating the fatigue life and strength for composite materials, with the addition of nanoparticles and then, a comparison of the results was achieved. The comparison of the results indicate a maximum error between results calculated by two technique did not exceeded about (1%). Then, the results calculated showed that the mechanical properties and fatigue life and strength increase with reinforcement with Nano particle. Also, the results showed that the modified for fatigue limits with materials by (Nano SiO2) Nano particle was more than the modified for fatigue limits for materials reinforcement with other materials. Finally, it can be concluded that the modified for fatigue strength, by reinforcement with (Nano SiO2), leads to 60% more than fatigue limit without Nano additive.
In this paper, numerical and experimental studies on the elastic behavior of glass fiber reinforced polymer (GFRP) with stiffeners in the GFRP section's web (to prevent local buckling) are presented. The GFRP profiles were connected to the concrete deck slab by shear connectors. Two full-scale simply supported composite beams (with and without stiffeners) were tested under impact load (three-point load) to assess its structural response. The results proved that the maximum impact force, maximum deflection, damping time, and damping ratio of the composite beam were affected by the GFRP stiffeners. The experimental results indicated that the damping ratio and deflection were diminished compare
... Show MoreObjective: The goal of this research is to load Doxorubicin (DOX) on silver nanoparticles coupled with folic acid and test their anticancer properties against breast cancer. Methods: Chitosan-Capped silver nanoparticles (CS-AgNPs) were manufactured and loaded with folic acid as well as an anticancer drug, Doxorubicin, to form CS-AgNPs-DOX-FA conjugate. AFM, FTIR, and SEM techniques were used to characterize the samples. The produced multifunctional nano-formulation served as an intrinsic drug delivery system, allowing for effective loading and targeting of chemotherapeutics on the Breast cancer (AMJ 13) cell line. Flowcytometry was used to assess therapy efficacy by measuring apoptotic induction. Results: DOX and CS-Ag
... Show MoreBackground: This study was formulated to compare the effect of 5%hydrofluoric acid in comparison to 37%phosphoric acid with and without the application of silane on bond strength of composite to porcelain. Materials and Methods: Specimen preparation was divided in to two phases, metal-disks fabrication (8mm-diameter and 4mm-thickness) and ceramic veneering. Thirty two specimens were prepared, sandblasted with 50 μm aluminum oxide, and divided into four groups of eight samples. Groups I and III were etched with 37%phosphoric acid while groups II and IV were etched with 5%hydrofluoric acid; and groups I and II were silaneted while groups III and IV were not. Heliobond, and resin composite were applied to each specimen using a plastic transpa
... Show MoreBackground: The main drawback of soft lining materials was that they debonded from the denture base after a certain period of usage. Therefore, the purpose of this research was to determine the impact of oxygen and argon plasma treatment on the shear bonding strength of soft liners to two different kinds of denture base materials: conventional acrylic resin and high impact acrylic resin. Materials and Methods: Heat cure conventional and high impact acrylic blocks (40 for each group) were prepared. A soft liner connected the final test specimen of two blocks of each acrylic material. Shear bond strength (SBS) was assessed using universal testing machine. Additional blocks were also prepared for analyzing Vickers microhardness, contact ang
... Show MoreThe matter of handwritten text recognition is as yet a major challenge to mainstream researchers. A few ways deal with this challenge have been endeavored in the most recent years, for the most part concentrating on the English pre-printed or handwritten characters space. Consequently, the need to effort a research concerning to Arabic texts handwritten recognition. The Arabic handwriting presents unique technical difficulties because it is cursive, right to left in writing and the letters convert its shapes and structures when it is putted at initial, middle, isolation or at the end of words. In this study, the Arabic text recognition is developed and designed to recognize image of Arabic text/characters. The proposed model gets a single l
... Show MoreOver the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.
The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame
The purpose of my thesis is to prepare four new ligands (L1-L4) that have been used to prepare a series of metal complexes by reacting them with metal ions: M=(Mn(II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II), Hg(II) Where succinyl chloride was used as a raw material for the preparation of bi-dented ligands (L1-L4) by reacting it with potassium thiocyanate as a first step and then reacting with (2-aminobenzothiazole, Benzylamine, 4-aminoantipyrine, Sulfamethoxazole) respectively as a second step with the use of dry acetone as a solvent, the chemical formula of the four ligands prepared in succession: N1,N4-bis(benzo[d]thiazol-2-ylcarbamothioyl)succinamide (L1) N1,N4-bis(benzylcarbamothioyl)succinami
... Show MoreThis 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 MoreArtificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le
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