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<p>Mega construction projects are extremely large-scale investment projects that typically cost more than one billion dollars, requiring resources that run into millions of man hours, with numerous stakeholders with an extraordinary amount of interlink. Megaprojects take five years or more to complete and generate high public attention, generates multiple social impact and environmental impact, and high investments by governments. These factors introduce complexities and other unclear risks upon execution. Historical data shows very poor performance for megaprojects. In particular they are often over-budgeted and/or behind schedule and, once finished, they deliver less benefits than originally planned. ‘Megaprojects’ is a concept of growing importance in Kuwait’s construction industry nowadays and is a globally connected business environment. This concept requires closer examination as a result of the expansion of global networks, increasing collaboration among numerous partners and the complexity of managing such projects. Despite the existing research in megaprojects, it is still unclear what risks are associated with these types of projects and which project characteristics promote the delivery of successful megaprojects. It is critical to examine the risks associated with implementation and to identify the factors that contribute to success of megaprojects. This research aims to identifying and assessing essential risks variables associated with construction of megaproject in Kuwait and in developing strategies to manage and mitigate them.</p>

-Data mining is a powerful technology for analyzing huge data, it has many techniques such as; classification, clustering, prediction and association rules etc., In this research Association rule will be used for analyzing data, which will help to extract the data related to combinations of items. Numerous customers tends to purchase items regularly, each time they visit supermarket, customer’s need to move around from shelf to shelf for the product of their interest which is time consuming. This research will help to minimize the time consumption for customers by analyzing the customer’s invoices and letting know the supermarket about the patterns of customer's orientations. In this work python tool will be used for data mining, by using association rule to analyze the customer’s purchases and retrieve the relevant information which will help to determine the customer’s pattern and know the association between products. In this rationale, the data of customer’s purchases were collected from Lulu hypermarket for data analysis and the outcomes of the analysis is to know the customer’s patterns and making the shopping easy by reorganizing the related items and the most buying items together on same shelf.

Analysis of morphology of Urdu is a preliminary task to several NLP tasks. Since it is impractical to maintain updated lexicons due to coinage of new words morphological guessing is also used. However guessing depends entirely on affixes and a lot of undesired answers emerge. Our system Urdu Morphological Guesser (UMG) uses morphological guessing on Urdu while utilizing ranking and clues to refine and improve the guesses. It covers open class words and enables guessing ofpart ofspeech, number, gender, causation, cases and language oforigin.