The contemporary business environment is witnessing increasing calls for modifications to the traditional cost system, and a trend towards adopting cost management techniques to provide appropriate financial and non-financial information for senior and executive departments, including the Resource Consumption Accounting (RCA) technique in question, which classifies costs into fixed and variable to support the decision-making process. Moreover, (RCA) combines two approaches to cost estimation, the first based on activity-based cost accounting (ABC) and the second on the German cost accounting method (GPK). The research aims to provide a conceptual vision for resource consumption accounting, after Considering it as an accounting technique for cost management, working on the optimal exploitation of available resources and employment of idle energy to contribute to reducing the cost of products and enhancing competitiveness between units, as well as explaining its concepts, components, features and determinants of their application. Between the unit's resources and outputs, in order to support senior management financially and materially. b Resisting change, which is attributed to lack of knowledge of application rules and policies on the one hand, and fear of failure to adopt cost management techniques. The researchers recommend the adoption of the proposed vision of technology in the Iraqi units to know the homogeneous resource pools, which will clarify the interconnected relationships between them and indicate the extent to which each resource directly benefits from the other, with the aim of knowing the path of the flow of energy costs, in order to reach the cost measurement as much as the resources used.
The lower respiratory tract of sheep was studied to determine the torsion and branching of the bronchial tree. The respiratory system of ruminants and all living organisms is one of the most important organs in the body that controls the amount of gas exchange between the heart and lungs through the airways, it is clear that in sheep it consists of a narrow bronchial tube that reaches the extent of lung tissue repercussions. He used silicon, water, acid, and at room temperature, and the substance was injected with an injection gun through the trachea and was pushed gently to spread and distribute in all parts of the lungs with moderate manual pressure. The results showed that the mold shape in the lung and the bronchial branches of
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Objective: The study aimed to screen the prepubertal children for idiopathic scoliosis at earlier stages, and find
out the relationship between idiopathic scoliosis and demographic data such as age, sex, body mass index,
heavy backpacks, and heart & lung diseases.
Methodology: A descriptive study was conducted on screening program for prepubertal children in primary
schools at Baghdad city, starting from 24th of February to the end of October 2010. Non- probability
(purposive) sample of 510 prepubertal children were chosen from primary schools of both sides of Al-Karkh
and Al-Russafa sectors. Data was collected through a specially constructed questionnaire format include (24)
items multiple choice questions, and
This research attempts to find the association between single nucleotide polymorphism (SNP) of IL2+166 gene (rs2069763) and type 2 diabetes mellitus (T2DM) in a sample of Iraqi patients. A total of 44 patients and 55 apparently healthy volunteers were genotyped for the SNP using polymerase chain reaction test. Three genotypes (GG, GT, and TT) corresponding to two alleles (G and T) were found to have SNP. Both study groups’ genotypes had a good agreement for the analysis of Hardy-Weinberg Equilibrium. The results revealed increased frequencies between the observed and expected GG and TT genotypes and IL2+166 SNP T allele in T2DM patients (40.9 vs. 40.0 %; OR = 1.04; 95% CI, 0.47 - 2.31), whereas the values in the control group were
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A new two-way nesting technique is presented for a multiple nested-grid ocean modelling system. The new technique uses explicit center finite difference and leapfrog schemes to exchange information between the different subcomponents of the nested-grid system. The performance of the different nesting techniques is compared, using two independent nested-grid modelling systems. In this paper, a new nesting algorithm is described and some preliminary results are demonstrated. The validity of the nesting method is shown in some problems for the depth averaged of 2D linear shallow water equation.
Landforms on the earth surface are so expensive to map or monitor. Remote Sensing observations from space platforms provide a synoptic view of terrain on images. Satellite multispectral data have an advantage in that the image data in various bands can be subjected to digital enhancement techniques for highlighting contrasts in objects for improving image interpretability. Geomorphological mapping involves the partitioning of the terrain into conceptual spatial entities based upon criteria. This paper illustrates how geomorphometry and mapping approaches can be used to produce geomorphological information related to the land surface, landforms and geomorphic systems. Remote Sensing application at Razzaza–Habbaria area southwest of Razz
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High-resolution imaging of celestial bodies, especially the sun, is essential for understanding dynamic phenomena and surface details. However, the Earth's atmospheric turbulence distorts the incoming light wavefront, which poses a challenge for accurate solar imaging. Solar granulation, the formation of granules and intergranular lanes on the sun's surface, is important for studying solar activity. This paper investigates the impact of atmospheric turbulence-induced wavefront distortions on solar granule imaging and evaluates, both visually and statistically, the effectiveness of Zonal Adaptive Optics (AO) systems in correcting these distortions. Utilizing cellular automata for granulation modelling and Zonal AO correction methods,
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Deep Learning Techniques For Skull Stripping of Brain MR Images
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p
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