Purpose: aims the study to show How to be can to enhance measurement management by incorporating a risk-based approach and the six sigma method into a more thorough assessment of metrological performance.   Theoretical framework: Recent literature has recorded good results in analyzing the impact of Six Sigma and risk management on the energy sector (Barrera García et al., 2022) (D'Emilia et al. 2015). However, this research came to validate and emphasize the most comprehensive assessment of metrological performance by integrating Risk management based approach and Six Sigma analysis.   Design/methodology/approach: This study was conducted in Iraqi petroleum refining companies. System quality is measured in terms of sigmas, and t

Purpose: aims the study to show How to be can to enhance measurement management by incorporating a risk-based approach and the six sigma method into a more thorough assessment of metrological performance.   Theoretical framework: Recent literature has recorded good results in analyzing the impact of Six Sigma and risk management on the energy sector (Barrera García et al., 2022) (D'Emilia et al. 2015). However, this research came to validate and emphasize the most comprehensive assessment of metrological performance by integrating Risk management based approach and Six Sigma analysis.   Design/methodology/approach: This study was conducted in Iraqi petroleum refining companies. System quality is measured in terms of sigmas, and t

Two Prototypes of Transversely Excited at atmospheric pressure (TEA) Nitrogen laser systems (One Stage Blumlein Circuit and Two Stage Blumlein Circuit) were fabricated and operated. High voltage power supply with variable operating voltage (0-20 kv) and operating current (1-3A) was built and tested successfully. The gas flow rate of 15 L/ min and 10 L/ min for OSBC and TSBC was used. The performance of the fabricated systems was studied extensively reaching to the optimum operating conditions. The obtained laser output energy for the first system has linear relationship with the applied voltage. The maximum output energy was about (1.14 mJ) with (10.40) ns pulse duration and the half-wave divergence angle was about (0.1455 m rad). In the

The magnetic properties of a pure Nickel metal and Nickel-Zinc-Manganese ferrites having the chemical formula Ni_0.1(Zn_0.4Mn_0.6)_0.9Fe₂O₄ were studied. The phase formation and crystal structure was studied by using x-ray diffraction which confirmed the formation of pure single spinel cubic phase with space group (Fd3m) in the ferrite. The samples microstructure was studied with scanning electron microstructure and EDX. The magnetic properties of the ferrite and nickel metal were characterized by using a laboratory setup with a magnetic field in the range from 0-500 G. The ferrite showed perfect soft spinel phase behavior while the nickel sample showed higher magnetic loss an

study aimed to recognize The relationship between Intrinsic Motivation Academy and Time Management among University students and measure Intrinsic Motivation Academy And Time Management for sample and Balancing Degrees of Basic Research on the two scales According to the Variable genders and Specialization, The sample consisted (350) students by (230) female (120) male , and the sample  responded scales of Intrinsic Motivation Academy for (Alwan & Attaat2009) and Time Management (Building tool), The Results of this study show that: There are statistically significant differences according to gender variable in Intrinsic Motivation Academy and Time Management in favor of the male, and there are statistica

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c