Delays and disruption are a common issue in both community and personal building programs The problem exists all throughout the world, but it is particularly prevalent in Iraq, where millions of dollars are squandered each time as a outcome. Delays and interruptions may have serious consequences not just for Iraq's construction plans, but also for the country's economic and social status. While numerous studies have been conducted to investigate the factors driving delays and disruption in Iraqi construction projects, slight consideration has been given to by what means project management implements and approaches have affected the occurrence of project delays and disruption. After analyzing the crucial reasons for delays and instability in public and private construction projects in Iraq, this paper aims to improve the recording and recommendations using Project Supervision concepts. A thorough investigation was conducted to identify the critical factors that are causing delays and disruptions in construction projects in Iraq's public and private sectors and present project management application procedures in order to establish recommendations to successfully reduce work disruptions and instability in Iraq This paper identifies the top crucial factors contributing to construction project delays and disruptions in Iraq. It further identifies project management Tools and techniques that, when used appropriately, have the potential to address the major causes of delays and interruptions. Following that, a new set of guidelines for applying Project Management methodologies and strategies to address the identified delay and disruption issues is provided, with the objective of aiding practitioners in minimizing the possibility for construction delays and interruption in Iraqi projects.
This study explores the challenges in Artificial Intelligence (AI) systems in generating image captions, a task that requires effective integration of computer vision and natural language processing techniques. A comparative analysis between traditional approaches such as retrieval- based methods and linguistic templates) and modern approaches based on deep learning such as encoder-decoder models, attention mechanisms, and transformers). Theoretical results show that modern models perform better for the accuracy and the ability to generate more complex descriptions, while traditional methods outperform speed and simplicity. The paper proposes a hybrid framework that combines the advantages of both approaches, where conventional methods prod
... Show MoreAttitude is an important subject that has attracted researchers and thinkers in organizational theory and organizational behavior because of its great importance in various field studies. Field evidence suggests that individuals in their daily lives or careers respond to specific events through a set of internal tendencies Internal tendencies are negative or positive and systematic. These trends tend to be invisible, not limited to certain boundaries, and involve a significant number of individuals within organizations or society.
The research aims to identify the impact of trends in the ethics of public service workers for individuals, through a sample of (72) doctors and (60) administrative staff
... Show MoreThe artistic concepts differ in their expressive and semantic relations, among these concepts are the artistic values, as there are points of view, social concepts and historical values interacted from one generation to another over the time. These values represent symbols and indications reflect reality, which has passed through the time to reach us with environmental forms saved by the history at the Natural History Museum, has an impact on the receives mind with its formal and sensory dimensions and connecting with that history as an environment that lacks to the current reality which has immortal means particularly in the cognitive thinking , and the reflection of that in the Iraqi culture and with the associated concepts of interior
... Show MoreSolid waste is a major issue in today's world. Which can be a contributing factor to pollution and the spread of vector-borne diseases. Because of its complicated nonlinear processes, this problem is difficult to model and optimize using traditional methods. In this study, a mathematical model was developed to optimize the cost of solid waste recycling and management. In the optimization phase, the salp swarm algorithm (SSA) is utilized to determine the level of discarded solid waste and reclaimed solid waste. An optimization technique SSA is a new method of finding the ideal solution for a mathematical relationship based on leaders and followers. It takes a lot of random solutions, as well as their outward or inward fluctuations, t
... Show MoreProduced water is accompanied with the production of oil and gas especially at the fields producing by water drive or water injection. The quantity of these waters is expected to be more complicated problem with an increasing in water cut which is expected to be 3-8 barrels water/produced barrel oil.Produced water may contain many constituents based on what is present in the subsurface at a particular location. Produced water contains dissolved solids and hydrocarbons (dissolved and suspended) and oxygen depletion. The most common dissolved solid is salt with concentrations range between a few parts per thousand to hundreds parts per thousand. In addition to salt, many produced waters also contain high levels of heavy metals like zinc, bari
... Show MoreMedicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea
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