Abstract

This research aims to design a multi-objective mathematical model to assess the project quality based on three criteria: time, cost and performance. This model has been applied in one of the major projects formations of the Saad Public Company which enables to completion the project on time at an additional cost that would be within the estimated budget with a satisfactory level of the performance which match with consumer requirements. The problem of research is to ensure that the project is completed with the required quality Is subject to constraints, such as time, cost and performance, so this requires prioritizing multiple goals. The project

Due to the continuous development in society and the multiplicity of customers' desires and their keeping pace with this development and their search for the quality and durability of the commodity that provides them with the best performance and that meets their needs and desires, all this has led to the consideration of quality as one of the competitive advantages that many industrial companies compete for and which are of interest to customers and are looking for. The research problem showed that the Diyala State Company for Electrical Industries relies on some simple methods and personal experience to monitor the quality of products and does not adopt scientific methods and modern programs. The aim of this research is to desi

Variable selection in Poisson regression with high dimensional data has been widely used in recent years. we proposed in this paper using a penalty function that depends on a function named a penalty. An Atan estimator was compared with Lasso and adaptive lasso. A simulation and application show that an Atan estimator has the advantage in the estimation of coefficient and variables selection.

Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

Individuals across different industries, including but not limited to agriculture, drones, pharmaceuticals and manufacturing, are increasingly using thermal cameras to achieve various safety and security goals. This widespread adoption is made possible by advancements in thermal imaging sensor technology. The current literature provides an in-depth exploration of thermography camera applications for detecting faults in sectors such as fire protection, manufacturing, aerospace, automotive, non-destructive testing and structural material industries. The current discussion builds on previous studies, emphasising the effectiveness of thermography cameras in distinguishing undetectable defects by the human eye. Various methods for defect

This paper aims to validate a proposed finite element model to be adopted in predicting displacement and soil stresses of a piled-raft foundation. The proposed model adopts the solid element to simulate the raft, piles, and soil mass. An explicit integration scheme has been used to simulate nonlinear static aspects of the piled-raft foundation and to avoid the computational difficulties associated with the implicit finite element analysis.

The validation process is based on comparing the results of the proposed finite element model with those of a scaled-down experimental work achieved by other researchers. Centrifuge apparatus has been used in the experimental work to generate the required stresses to simulate t