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

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

A roundabout is a highway engineering concept meant to calm traffic, increase safety, reduce stop-and-go travel, reduce accidents and congestion, and decrease traffic delays. It is circular and facilitates one-way traffic flow around a central point. The first part of this study evaluated the principles and methods used to compare the capacity methods of roundabouts with different traffic conditions and geometric configurations. These methods include gap acceptance, empirical, and simulation software methods. Previous studies mentioned in this research used various methods and other new models developed by several researchers. However, this paper's main aim is to compare different roundabout capacity models for acceptabl

This research was designed to study effect of performance appraisal dimensions on organizational confidence.

Asset completion questionnaire was used to collect data of this research from a random simple represent forty employees who works in Iraqi Oil ministry. The main result of this research was positive relations and the effect between performance appraisal and organizational confidence. The research contains some conclusions, the main of it is unimplemented the performance appraisal results in the policies of employees in the ministry and it work in classic methods incentives and training.

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Abstract

The research aims to shed light on the extent to which the practices of performance management in achieving organizational excellence in one of the formations and the Ministry of Finance (GCT). The importance of the selection of these organizations is that they occupies a large and exceptional importance in the national economy through income redistribution add it to cover a large part of the state budget revenues, these organizations possess functionally diverse cadre of them pregnant initial certification and other senior and he fairly stable To meet this target, and on the basis of the data search exploratory researcher built model hypothesis for the search included variable impressionist and

The research aims to investigate the relationship and impact of e-governance as an independent variable in achieving creative performance as a dependent variable. These variables have been studied in the Directorate of Passports Affairs, and seek to come up with a set of recommendations that help in promoting e-governance in the researched organization, and the researcher adopted the descriptive-analytical approach, included The sample (122) of the total (194) individuals distributed in several administrative levels (officers, associates, and administrative staff). By adopting the questionnaire, which included (49) paragraphs as the main tool for the collection of data and information, as well as personal interviews and field obs

Numerical study of separation control on symmetrical airfoil, four digits (NACA

0012) by using rotating cylinder with double steps on its upper surface based on the computation of Reynolds-average Navier- Stokes equations was carried out to find the optimum configuration of unconventional airfoil for best aerodynamics performance. A model based on collocated Finite Volume Method was developed to solve the governing equations on a body-fitted coordinate system. A revised (k-w) model was proposed as a known turbulence model. This model was adapted to simulate the control effects of rotating cylinder. Numerical solutions were performed for flow around unconventional airfoil with cylinder to main stream velocities ratio in the range

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

Background: The mechanical and physical properties of Polymethyl methacrylate (PMMA) don’tfulfill the entire ideal requirements of denture base materials. The purpose of this study was to produce new modified polymer nanocomposite (PMMA /ZrO2-TiO2) andassess itsimpact strength, transverse strength and thermal conductivity in comparison to the conventionalheat polymerized acrylic resin. Materials and Methods: Both ZrO2 and TiO2nano fillers were silanized with TMSPM (trimethoxysilyl propyl methacrylate) silane coupling agent before beingdispersed by ultrasonication with the methylmethacrylate (monomer) and mixed with the polymer by means of 2% by weight in (1:1) ratio, 60 specimens were constructed by conventional water bath processing

Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor