Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

This study discussed a biased estimator of the Negative Binomial Regression model known as (Liu Estimator), This estimate was used to reduce variance and overcome the problem Multicollinearity between explanatory variables, Some estimates were used such as Ridge Regression and Maximum Likelihood Estimators, This research aims at the theoretical comparisons between the new estimator (Liu Estimator) and the estimators

study aims to examine education and the challenges of globalization in light of Corona pandemic. The examination involves surveying a randomly selected sample from the University of Baghdad’s professors, particularly from the colleges of Education for Women, Arts, and Sciences. The purpose of this examination is to learn about the dimensions of globalization, its effects on the educational process, and the importance of distance education during the spread of Corona virus quarantine. To achieve this, the researcher followed a descriptive and analytical approach by applying a questionnaire to a sample of 70 teachers who were randomly selected electronically. Results have shown that 78.6% emphasized the contribution of globalization duri

Although the events of September 2001 marked the United States' employment of solid forces in its direct comprehensive strategy to counter terrorist organizations and any other challenges to US national security, the United States did not lose sight of the importance of the cultural variable. The cultural variable is the United States' most important instrument of soft power in ensuring its dominance of the international system and promoting its global project. France viewed US soft power as a threat to its own civilizational pattern. Therefore, France considers culture to be an inherent component of its national personality and a cornerstone of its international standing as a major force. Additionally, the US-French political and economic

Preserving the independence and sovereignty of the countries of the South Caucasus region, establishing political and economic stability in the region, and supporting regional cooperation are the main elements of Turkish foreign policy towards the region. The South Caucasus region, which has historical and cultural ties between it and Turkey, is a bridge that links Turkey to Central Asia.                     

     Turkey later developed advanced relations with Azerbaijan and Georgia. However, the same momentum was not achieved in terms of relations with Armenia because of the conflict over Nagorny Karabakh

  The current research aims to identify the effect of the learning mastery strategy using interactive learning as a therapeutic method on the achievement of secondary school students in mathematics. To achieve the research objective, the researcher selected second-grade middle school students at Al-Haybah Intermediate School for Boys and determined his research sample, which consisted of (77) students distributed into two sections: Section (A) the experimental group, with (38) students, and Section (B) the control group, with (39) students. The statistical equivalence of the two research sample groups was confirmed in the variables (intelligence test, previous achievement, and previous knowledge test). The researchers chose the par

Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o