The research aims to determine the role of Entrepreneur decision-making in its dimensions in improving the activities of Ambidexterity performance in its dimensions in the researched company. The importance of the research is also evidenced by assisting the oil products distribution company/session in directing the interest of the researched company because it has a prominent role in the Iraqi industrial community for the Entrepreneur decision-making variable that Contributes to building sustainable competitive advantage. This will happen when the company has an Entrepreneur orientation and a good strategic plan is built by the smart leaders in the researched company The researcher adopted the method of the analyti

            The objective of this study is to measure the impact of financial development on economic growth in Iraq over the period (2004-2018) by applying a fully corrected square model (FMOLS) Whereas, a set of variables represented by (credit-to-private ratio of GDP, the ratio of money supply in the broad sense of GDP, percentage of bank deposits from GDP) were chosen as indicators for measuring financial development and GDP to measure economic growth.

Major tests have been carried out, such as the stability test (Unite Root Test), the integration test (Cointegration). Results of the study showed that there

The concept of Cech fuzzy soft bi-closure space ( ˇ Cfs bi-csp) ( ˇ U, L1, L2, S) is initiated and studied by the authors in [6]. The notion of pairwise fuzzy soft separated sets in Cfs bi-csp is defined in this study, and various features of ˇ this notion are proved. Then, we introduce and investigate the concept of connectedness in both Cfs bi-csps and its ˇ associated fuzzy soft bitopological spaces utilizing the concept of pairwise fuzzy soft separated sets. Furthermore, the concept of pairwise feebly connected is introduced, and the relationship between pairwise connected and pairwise feebly connected is discussed. Finally, we provide various instances to further explain our findings.

The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

The idea of ech fuzzy soft bi-closure space ( bicsp) is a new one, and its basic features are defined and studied in [1]. In this paper, separation axioms, namely pairwise, , pairwise semi-(respectively, pairwise pseudo and pairwise Uryshon) - fs bicsp's are introduced and studied in both ech fuzzy soft bi-closure space and their induced fuzzy soft bitopological spaces. It is shown that hereditary property is satisfied for , with respect to ech fuzzy soft bi-closure space but for other mentioned types of separations axioms, hereditary property satisfies for closed subspaces of ech fuzzy soft bi-closure space.

The Early-Middle Miocene succession in Iraq is represented by the Serikagni, Euphrates and Dhiban formations, which deposited during the Early Miocene. The Jeribe and Fatha successions were deposited during Middle Miocene age. This study includes microfacies analysis, depositional environments, sequence stratigraphy and basin development of Early – middle Miocene in Hamrin and Ajeel oil fields and Mansuriyha Gas Field. The study area includes four boreholes in three oil fields located in central Iraq: Hamrin (Hr-2) and Ajeel (Aj-13, and 19) oil feilds, and Mansuriyha (Ms-2) Gas Field. Five facies associations were distinguished within the studied fields: deep marine, slop, platform-margin, open marine, restricted interior platform

Twitter is becoming an increasingly popular platform used by financial analysts to monitor and forecast financial markets. In this paper we investigate the impact of the sentiments expressed in Twitter on the subsequent market movement, specifically the bitcoin exchange rate. This study is divided into two phases, the first phase is sentiment analysis, and the second phase is correlation and regression. We analyzed tweets associated with the Bitcoin in order to determine if the user’s sentiment contained within those tweets reflects the exchange rate of the currency. The sentiment of users over a 2-month period is classified as having a positive or negative sentiment of the digital currency using the proposed CNN-LSTM