The principal objective of this study is to demonstrate how green quality management and product life cycle costing may help an organization gain a competitive advantage. Green quality management's influence on increasing product quality and meeting environmental criteria, as well as tracking the activities of product life cycle before, during, and after production, is demonstrated. Orienting these activities toward the production of eco-friendly products that fulfill the needs of customers, hence increasing organization's market share. We found from our study that proposed framework can help organizations improve their competitiveness. Green quality management contributes to environmental protection and the provision of high-qualit

This research explains to us the role of the Islamic religion in the issue of accuracy in speech and work, and how it is closely related to human production in his life, and Islam affirms that his idea is mainly reflected in his production, and how it affects the perception of the meaning of creativity. Therefore, our Islam affirmed the accuracy in every word or work we do to build a society in which people enjoy high quality in ethics and dedication in their work so that the Islamic system depends on humanity to preserve our rights on the other hand the research discusses the deliberate default and how it reflects on our production and how it makes it less good.

In this study, poly4-(nicotinamido)-4-oxo-2-butenoic acid (PNOE) was prepared by the electro polymerization of 4-(nicotinamido)-4-oxo-2-butenoic acid (NOE) monomer on a 316 stainless steel (St.St) which acts as an anticorrosion coating.  Fourier transforms infrared (FTIR), atomic force microscopy (AFM), scanning electron microscopy (SEM), and cyclic voltammetry were used to diagnose the structure and the properties of the prepared polymer layer. The corrosion behavior of the uncoated and coated 316  St.St were evaluated by using an electro chemical polarization technique in 0.2 M hydrochloric acid  solution as a corrosive medium at a temperature range of 293 to 323 K. Nano materials, such as nano ZnO and graphene were added in di

One of the most severe problems with flexible asphalt pavements is permanent deformation in the form of rutting. Accordingly, the practice of adding fiber elements to asphalt mix to improve performance under dynamic loading has grown significantly in order to prevent rutting distress and ensure a safe and long-lasting road surface. This paper explores the effects of a combination of ceramic fiber (CF), a low-cost, easily available mineral fiber, and thermal insulator fiber reinforced to enhance the Marshall properties and increase the rutting resistance of asphalt mixes at high temperatures. Asphalt mixtures with 0%, 0.75%, 1.5%, and 2.25% CF content were prepared, and Marshall stability and wheel tracking tests were employed to stu

This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

Predicting vertical stress was indeed useful for controlling geomechanical issues since it allowed for the computation of pore pressure for the formation and the classification of fault regimes. This study provides an in-depth observation of vertical stress prediction utilizing numerous approaches using the Techlog 2015 software. Gardner's method results in incorrect vertical stress values with a problem that this method doesn't start from the surface and instead relies only on sound log data. Whereas the Amoco, Wendt non-acoustic, Traugott, average technique simply needed density log as input and used a straight line as the observed density, this was incorrect for vertical computing stress. The results of these methods

Background: Undergraduate dental students are more susceptible to situations of stress that affected quality of sleep, such profiles of stress may result in sleep bruxism and/or awake bruxism, parafunctions that can affect oral and general health. The aim of the study was to evaluate the association of sleep bruxism, awake bruxism and sleep quality among dental students. Materials and methods: A cross-sectional study was performed including 260 Iraqi dental students from university of Baghdad aged from 20to25years old. Students enrolled in the third and fifth class participated in the study. The Pittsburgh Sleep Questionnaire Index (PSQI) was used for data collection. The PSQI was distributed during lecture classes. Sleep bruxism and awake