This research aims to solve the problem of selection using clustering algorithm, in this research optimal portfolio is formation using the single index model, and the real data are consisting from the stocks Iraqi Stock Exchange in the period 1/1/2007 to 31/12/2019. because the data series have missing values ,we used the two-stage missing value compensation method, the knowledge gap was inability the portfolio models to reduce The estimation error , inaccuracy of the cut-off rate and the Treynor ratio combine stocks into the portfolio that caused to decline in their performance, all these problems required employing clustering technic to data mining and regrouping it within clusters with similar characteristics to outperform the portfolio building models to diagnose those stock that Causing a decrease in portfolio performance ,our conclusion is Clustering technic outperforms the diagnosis of those stocks that meet the condition of opting into the optimal portfolio according to common considerations, but after excluding them, the performance of optimal portfolio is rises
Abstract This study explores the extent to which public relations (PR) departments within Traqj governmental institutions are integrating artificial intelligence (AI) applications into their communication activities. The research adresses the growing importanc of AI in enhancing administrative efficieney, communication transparency, and stakeholder engagement. Adopting a descriptive research design, the study relied on an electtonic questionnaire distributed to PR profesionals across various ministries and government bodies, collecting 100 valid responses. The indings reveal that while younger PR practitioners are actively embracing AI, older employees show limited engagement. Most participants acquired AI-related skills through self- learn
... Show MoreBackground: Suppression of quorum sensing (QS) that regulates many virulence factors, including antimicrobial resistance, in bacteria may subject the pathogenic microbes to the harmful consequences of the antibiotics, increasing their susceptibility to such drugs. Aim: The current study aimed to make an aqueous crude extract from the soil Proteus mirabilis isolate with the use of the gas chromatography-mass spectrometry (GC-MS) technique for its analysis, and then, study the impact of the extract on clinical isolates of Pseudomonas aeruginosa. Methods: Preparation of crude extracts from P. mirabilis (both organic and aqueous), which were then analyzed by GC-MS to detect the bioactive ingredients. Furthermore, the extract’s capability to i
... Show MoreIron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies. In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model coul
... Show MoreIn this paper, three tool paths strategies; iso-planar, helical and adaptive have been implemented to investigates their effect on the mechanical properties of Brass 65-35 formed by single point incremental sheet metal forming process. To response this task, a fully digital integrated system from CAD modeling to finished part (CAD/CAM) for SPIF process has been developed in this paper.
The photo-micrographs shows an identical grain formation due to the plastic deformation of the incremental forming process, change in the grain shape and size was observed. It's found that the adaptive tool path play a significant role to increase the hardness of the formed specimen from (48 to 90 HV) and the grain texture of the formed specimen found a
Increased downscaling of CMOS circuits with respect to feature size and threshold voltage has a result of dramatically increasing in leakage current. So, leakage power reduction is an important design issue for active and standby modes as long as the technology scaling increased. In this paper, a simultaneous active and standby energy optimization methodology is proposed for 22 nm sub-threshold CMOS circuits. In the first phase, we investigate the dual threshold voltage design for active energy per cycle minimization. A slack based genetic algorithm is proposed to find the optimal reverse body bias assignment to set of noncritical paths gates to ensure low active energy per cycle with the maximum allowable frequency at the optimal supply vo
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