Researchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model wa

The purpose of this paper is to solve the stochastic demand for the unbalanced transport problem using heuristic algorithms to obtain the optimum solution, by minimizing the costs of transporting the gasoline product for the Oil Products Distribution Company of the Iraqi Ministry of Oil. The most important conclusions that were reached are the results prove the possibility of solving the random transportation problem when the demand is uncertain by the stochastic programming model. The most obvious finding to emerge from this work is that the genetic algorithm was able to address the problems of unbalanced transport, And the possibility of applying the model approved by the oil products distribution company in the Iraqi Ministry of Oil to m

           Housing finance is one of the main components of housing, and it is relied upon to help families buy, build, add building, and housing improve. Accordingly, different countries all over the world set policies and strategies for the purpose of organizing and developing the financial sector to solve quantitative and qualitative housing problems.

This research aims to identify housing finance policies and strategies in Iraq and Baghdad governorate.

The most prominent sources of housing financing are the Real Estate Bank and the Housing Fund, and accordingly the focus has been on the role of these two institutions in filling

This research deals with the nature of the Turkish attitude towards the events of the Arab Spring which the Arab region witnessed recently, as this attitude is characterized by hesitation and utter confusion about those events at its beginning. However, the development of events and the consequent repercussions led the Turkish decision makers of the foreign policy to reconsider their attitude towards those events for political, economic, cultural and social motives.

Transit agencies constantly need information about system operations and passengers to support their regular scheduling and operation planning processes. The lack of these processes and cultural motivations to use public transportations contributes enormously to the reliance on the private cars rather than public transportation, resulting in traffic congestions. The traffic congestions occur mainly during peak hours and the accidents happening as a result of road accidents and construction works.  This study investigates the effects of weekday and weekend travel variability on peak hours of the passenger flow distribution on bus lines, which can effectively reflect the degree of traffic congestion. A study of passen

BN RASHİD, 2023

This study examines the causes of time delays and cost overruns in a selection of thirty post-disaster reconstruction projects in Iraq. Although delay factors have been studied in many countries and contexts, little data exists from countries under the conditions characterizing Iraq during the last 10-15 years. A case study approach was used, with thirty construction projects of different types and sizes selected from the Baghdad region. Project data was gathered from a survey which was used to build statistical relationships between time and cost delay ratios and delay factors in post disaster projects. The most important delay factors identified were contractor failure, redesigning of designs/plans and change orders, security is

This research was designed to investigate the factors affecting the frequency of use of ride-hailing in a fast-growing metropolitan region in Southeast Asia, Kuala Lumpur. An intercept survey was used to conduct this study in three potential locations that were acknowledged by one of the most famous ride-hailing companies in Kuala Lumpur. This study used non-parametric and machine learning techniques to analyze the data, including the Pearson chi-square test and Bayesian Network. From 38 statements (input variables), the Pearson chi-square test identified 14 variables as the most important. These variables were used as predictors in developing a BN model that predicts the probability of weekly usage frequency of ride-hai