Abstract:

The aim of the research is to highlight the role of electronic human resources management practices in the sustainability of knowledge capital as one of its success factors, as well as the diagnosis and interpretation of the relationship between research variables and their dimensions. The research problem is that the University of Babil implements some electronic human resources management practices not in a complete way, The level of its application and the problems it faces, as well as the extent to which these practices reflect the knowledge capital and sustainability in the university, and highlights the importance of research as it is concerned with the electronic aspects and achieve the competitive advant

Purpose: Determining and identifying the relationships of smart strategic education systems and their potential effects on sustainable success in managing clouding electronic business networks according to green, economic and environmental logic based on vigilance and awareness of the strategic mind.

Design: Designing a hypothetical model that reveals the role and investigating audit and cloud electronic governance according to a philosophy that highlights smart strategic learning processes, identifying its assumptions in cloud spaces, choosing its tools, what it costs to devise expert minds, and strategic intelligence.

Methodology:

Time-domain spectral matching commonly used to define seismic inputs to dynamic analysis in terms of acceleration time history compatible with a specific target response spectrum is used in this study to investigate the second-order geometric effect of P-delta on the seismic response of base-isolated high-rise buildings. A synthetic time series is generated by adjusting reference time series that consist of available readings from a past earthquake of the 1940 El Centro earthquake adopted as an initial time series. The superstructure of a 20-story base isolated building is represented by a 3-D finite element model using ETABS software. The results of the base isolated building show that base isolation technique significantly reduces inter-s

To reduce solar radiation transmittance into buildings through windows facing east or west during summer, a window inclination from vertical position is suggested. The inclination of the window glazing and the rate of unwanted solar radiation during summer can be calculated knowing the dialy inclination of the sun rays. The inclination of window glazing depends on the latitude of the position required. For instance in Baghdad which is at about 33o north latitude a slope of 15o for window glazing is sufficient to prevent about 419 MJ/m2 of total solar radiation energy from penetration during summer for clear glazing of window facing east. This value drops to about 96 MJ/m2 during winter. Therefore the ratio between the energy saved for co

The selection of proper field survey parameters of electrical resistivity can significantly provide efficient results within a reasonable time and cost. Four electrode arrays of 2D Electric Resistivity Imaging (ERI) surveys were applied to characterize and detect subsurface archaeological bodies and to determine the appropriate array type that should be applied in the field survey. This research is to identify the subsurface features of the Borsippa archaeological site, Babylon Governorate, Middle Iraq. Synthetic modeling studies were conducted to determine the proper array and parameters for imaging the shallow subsurface features or targets. The efficiency of many array types has been tested for the detection the buried archaeolog

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet