The cost of pile foundations is part of the super structure cost, and it became necessary to reduce this cost by studying the pile types then decision-making in the selection of the optimal pile type in terms of cost and time of production and quality .So The main objective of this study is to solve the time–cost–quality trade-off (TCQT) problem by finding an optimal pile type with the target of "minimizing" cost and time while "maximizing" quality. There are many types In the world of piles but  in this paper, the researcher proposed five pile types, one of them is not a traditional, and   developed a model for the problem and then employed particle swarm optimization (PSO) algorithm, as one of evolutionary algorithms with t

The importance of this study stems from the importance of preserving the environment and creating a clean sustainable environment from waste and emissions and all the operations of industrial companies in general and cement companies in particular by activating sustainability accounting standards. The research aims to identify and diagnose deviations in violation of sustainability standards by employing the non-renewable resources standard (NR0401) For the construction industries to create a sustainable audit environment, the deductive approach was followed in the theoretical side and the inductive and descriptive approach to the practical side. The most important results of the research were the possibility of applying sustainab

The partial level density PLD of pre-equilibrium reactions that are described by Ericson’s formula has been studied using different formulae of single particle level density . The parameter  was used from the equidistant spacing model (ESM) model and the non- equidistant spacing model (non-ESM) and another formula of  are derived from the relation between  and level density parameter . The formulae used to derive  are the Roher formula, Egidy formula, Yukawa formula, and Thomas –Fermi formula. The partial level density results that depend on  from the Thomas-Fermi formula show a good agreement with the experimental data.

Background Psoriasis is one of the most prevalent chronic inflammatory skin conditions; its prevalence ranges from 1 to 3%. Tumor necrosis factor-alpha (TNF-α), a cytokine that enhances inflammation, is overexpressed in synovium and skin plaques in psoriasis. TNF-α plays a critical role in the pathogenesis of psoriasis. IL-10 is the most crucial cytokine for reducing excessive immune responses and decreasing pro-inflammatory reactions in all autoimmune disorders.   Objective To evaluate the effect of Apremilast on ILـ10, TNFـα, and BMI in obese psoriatic patients.   Methods Thirty patients included in this investigative study to measure the concentrations of TNFـα, ILـ10 and BMI, before and after receiving Apremilast. TNFـα and

Abstract Background: This study is aimed to assess the maxillary incisors’ root position, angulation, and buccal alveolar bone thickness in both genders and different classes of malocclusion using cone‑beam computed tomography (CBCT). Materials and Methods: Two hundred and six CBCT images were gathered and analyzed by three‑dimensional On‑Demand software to measure the variables of 803 maxillary central and lateral incisors. Genders and class difference was determined by unpaired t‑test, one‑way ANOVA, and Chi‑square tests. Results: Buccal root position of the maxillary incisors accounted for in the majority of the cases followed by the middle and palatal positions. The thickness of alveolar bone appears to have nearly the sam

In this study, a genetic algorithm (GA) is used to detect damage in curved beam model, stiffness as well as mass matrices of the curved beam elements is formulated using Hamilton's principle. Each node of the curved beam element possesses seven degrees of freedom including the warping degree of freedom. The curved beam element had been derived based on the Kang and Yoo’s thin-walled curved beam theory. The identification of damage is formulated as an optimization problem, binary and continuous genetic algorithms
(BGA, CGA) are used to detect and locate the damage using two objective functions (change in natural frequencies, Modal Assurance Criterion MAC). The results show the objective function based on change in natural frequency i

This paper reports test results and describes a numerical investigation of the effectiveness of using carbon fibre reinforced polymer (CFRP) fabrics for strengthening concrete cylinders that have been undamaged and damaged due to heating under preload. The purpose of this research was to investigate whether there is any difference in the performance of CFRP-wrapped cylinders if the wrapping is done under preload, and those for which neither heating, cooling nor wrapping was done under preload. The cylinders were exposed to 30% of maximum load at ambient temperature during heating and cooling before being wrapped under preload. Of 18 Ø 100 × 200 mm identical cylinders, 6 were left as control samples without heating, 12 were exposed t

 A dynamic analysis method has been developed to investigate and characterize embedded delamination on the dynamic response of composite laminated structures. A nonlinear finite element model for geometrically large amplitude free vibration intact plate and delamination plate analysis is presented using higher order shear deformation theory where the nonlinearity was introduced  in the Green-Lagrange sense. The governing equation of the vibrated plate were derived using the Variational approach. The effect of different orthotropicity ratio, boundary condition and delamination size on the non-dimenational fundamental frequency and frequency ratios of plate for different stacking sequences are studied. Finally th

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca