Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

   Addressed this research the impact of intelligence emotional dimensions of the main(self awareness, and self-management, and social awareness, and relationship management) in the performance excellence the university(performance optimization, and strategic development) this is by middling the styles decision making which are (rational and intuitive, and dependent, and spontaneous, and avoidant), and Go search of an intellectual dilemma raise fundamental questions revolve around the search was to answer those questions through a theoretical framework for search variables first and test models of the relationship and second through the impact six hypotheses President.The objective of the research to make sure the contr

Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a

The construction of highly safe and durable buildings that can bear accident damage risks including fire, earthquake, impact, and more, can be considered to be the most important goal in civil engineering technology. An experimental investigation was prepared to study the influence of adding various percentages 0%, 1.0%, and 1.5% of micro steel fiber volume fraction (Vf) to reactive powder concrete (RPC)—whose properties are compressive strength, splitting tensile strength, flexural strength, and absorbed energy—after the exposure to fire flame of various burning temperatures 300, 400, and 500 °C using gradual-, foam-, and sudden-cooling methods. The outcomes of this research proved that the maximum reduction in mechanical prop

In this research, we dealt with the study of the Non-Homogeneous Poisson process, which is one of the most important statistical issues that have a role in scientific development as it is related to accidents that occur in reality, which are modeled according to Poisson’s operations, because the occurrence of this accident is related to time, whether with the change of time or its stability. In our research, this clarifies the Non-Homogeneous hemispheric process and the use of one of these models of processes, which is an exponentiated - Weibull model that contains three parameters (α, β, σ) as a function to estimate the time rate of occurrence of earthquakes in Erbil Governorate, as the governorate is adjacent to two countr

The study aims detection teaching modalities adopted relationship in Jerash University exactly the classroom, and to achieve the goal of the study was to develop a questionnaire consisting of (39) items, and was achieving validity and reliability have, then sent to a sample of professors made up the university from (122) university professor of the total (172) professor, and they study population.

     Study found a relationship between the teaching methods of the four their strategies with classroom management, and as a result the overall average level, while Hspt critical thinking at the highest correlation with classroom discipline management relationship strategy, while the relatio

Radiation therapy plays an important role in improving breast cancer cases, in order to obtain an appropriateestimate of radiation doses number given to the patient after tumor removal; some methods of nonparametric regression werecompared. The Kernel method was used by Nadaraya-Watson estimator to find the estimation regression function forsmoothing data based on the smoothing parameter h according to the Normal scale method (NSM), Least Squared CrossValidation method (LSCV) and Golden Rate Method (GRM). These methods were compared by simulation for samples ofthree sizes, the method (NSM) proved to be the best according to average of Mean Squares Error criterion and the method(LSCV) proved to be the best according to Average of Mean Absolu

In this paper, a literature survey was introduced to study of enhancing the hazy images , because most of the images captured in outdoor images have low contrast, color distortion, and limited visual because the weather conditions such as haze and that leads to decrease the quality of images capture. This study is of great importance in many applications such as surveillance, detection, remote sensing, aerial image, recognition, radar, etc. The published researches on haze removal are divided into several divisions, some of which depend on enhancement the image, some of which depend on the physical model of deformation, and some of them depend on the number of images used and are divided into single-image and multiple images dehazing model

Enhanced Thematic Mapper Plus (ETM+) onboard the Landsat-7 remotely sensor satellite was launched on 15 April 1999. On May 31, 2003, image acquisition via the ETM+ was greatly impacted by the failure of the system’s Scan Line Corrector (SLC). Consequently, the ETM+ has lost approximately 22% of the data due to the increased scan gap. In this work, several gap-filling methods will be proposed to restore the ETM+ image malfunctions. Some of the proposed methods will be carried by estimating the missed pixel’s values from the same image pixel’s neighborhood, while others will utilize the pixel values extracted from different temporal scene acquired in different time. Mean average filter, median filter, midpoint filter, and several int