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

The research aims to identify the most important concerns that led to the increase of  interest in the topic of corporate governance and specifically highlighting  the role of the audit committees of the Administration  Board in reducing the risk of the auditor and the rationalization of professional judgments، in particular about accepting  the assignment and setting the fees of the audit process by extrapolating  global experience in this area ، and a field study is conducted for a sample of private Iraqi banks to evaluate the role of audit committees constituted currently per with bank law no. (94) of 2004 and to be acknowledged with actual performance of these committees and their role in recommending the n

Big data of different types, such as texts and images, are rapidly generated from the internet and other applications. Dealing with this data using traditional methods is not practical since it is available in various sizes, types, and processing speed requirements. Therefore, data analytics has become an important tool because only meaningful information is analyzed and extracted, which makes it essential for big data applications to analyze and extract useful information. This paper presents several innovative methods that use data analytics techniques to improve the analysis process and data management. Furthermore, this paper discusses how the revolution of data analytics based on artificial intelligence algorithms might provide

Today, problems of spatial data integration have been further complicated by the rapid development in communication technologies and the increasing amount of available data sources on the World Wide Web. Thus, web-based geospatial data sources can be managed by different communities and the data themselves can vary in respect to quality, coverage, and purpose. Integrating such multiple geospatial datasets remains a challenge for geospatial data consumers. This paper concentrates on the integration of geometric and classification schemes for official data, such as Ordnance Survey (OS) national mapping data, with volunteered geographic information (VGI) data, such as the data derived from the OpenStreetMap (OSM) project. Useful descriptions o

In this research, an experimental study was conducted to high light the impact of the exterior shape of a cylindrical body on the forced and free convection heat transfer coefficients when the body is hold in the entrance of an air duct. The impact of changing the body location within the air duct and the air speed are also demonstrated. The cylinders were manufactured with circular, triangular and square sections of copper for its high thermal conductivity with appropriate dimensions, while maintaining the surface area of all shapes to be the same. Each cylinder was heated to a certain temperature and put inside the duct at certain locations. The temperature of the cylinder was then monitored. The heat transfer coefficient were then cal

An Expression for the transition charge density is investigated
where the deformation in nuclear collective modes is taken into
consideration besides the shell model transition density. The
inelastic longitudinal C2 and C4 form factors are calculated using
this transition charge density for the Ne Mg 20 24 , , Si 28 and S 32
nuclei. In this work, the core polarization transition density is
evaluated by adopting the shape of Tassie model togther with the
derived form of the ground state two-body charge density
distributions (2BCDD's). It is noticed that the core polarization
effects which represent the collective modes are essential in
obtaining a remarkable agreement between the calculated inelastic
longi

Inelastic longitudinal electron scattering form factors have been calculated for isoscaler transition
T = 0 of the (0+ ®2+ ) and (0+ ®4+ ) transitions for the 20Ne ,24Mg and 28Si nuclei. Model
space wave function defined by the orbits 1d5 2 ,2s1 2 and 1d3 2 can not give reasonable result for
the form factor. The core-polarization effects are evaluated by adopting the shape of the Tassie-
Model, together with the calculated ground Charge Density Distribution CDD for the low mass 2s-1d
shell nuclei using the occupation number of the states where the sub-shell 2s is included with an
occupation number of protons (a ) .

The study aimed to identify the relationship between the speed and direction of the ball's rotation in the accuracy of the front and rear side longitudinal blow in wheelchair tennis players. The descriptive approach wasused in the manner of correlations to suit the nature of the problem to be studied. The research community identified the 32 players aged18 and over, and the search sample was selected from players with a local classification registered with the 2020 Wheelchair Ground Tennis Federation (2020) in the intentional manner of 8 players, using Smart Tennis Sensor technology to measure the speed and direction of the ball and test the accuracy of the front and rear side longitudinalstraightstrike. She conducted the reconnaissance exp

Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the