There are many problems facing the economic entities  as a result of its mass production &variation of its products  , the matter which had  increased the need & importance of cost accounting which is regarded a main tool for the managerial control.

The actual costing system is unable to meet the contemporary management needs ,so the Standard costing system appear to provide the management  with required information to perform its functions by the best use& way.

This research aims to determine  the standard cost for the  direct material for oil extraction activity by applying it in the north oil company.

      Bidentate Schiff base ligand 3-(3,4-Dihydroxy-phenyl)-2-[(4-dimethylamino-benzylidene)-amino]-2-methyl-propionic acid was prepared and characterized by spectroscopic techniques studies and elemental analysis. The Cd(II), Ni(II), Cu(II), Co(II), Cr(III),and Fe(III) of mixed-ligand complexes were structural explicate through moler conductance , [FT-IR, UV-Vis & AAS], chloride contents, , and magnetic susceptibility measurements. Octahedral geometries have been suggested for all complexes. The Schiff base and its  complexes were  tested against various bacterial species, two of {gram(G+) and gram(G-)} were shown weak to good activity against all bacteria.

Bidentate Schiff base ligand 3-(3,4-Dihydroxy-phenyl)-2-[(4-dimethylamino-benzylidene)-amino]-2-methyl-propionic acid was prepared and characterized by spectroscopic techniques studies and elemental analysis. The Cd(II), Ni(II), Cu(II), Co(II), Cr(III),and Fe(III) of mixed-ligand complexes were structural explicate through Moler conductance , [FT-IR, UV-Vis & AAS], chloride contents, , and magnetic susceptibility measurements. Octahedral geometries have been suggested for all complexes. The Schiff base and its complexes were tested against various bacterial species, two of {gram(G+) and gram(G-)} were shown weak to good activity against all bacteria.

Hypothesis CO2 geological storage (CGS) involves different mechanisms which can store millions of tonnes of CO2 per year in depleted hydrocarbon reservoirs and deep saline aquifers. But their storage capacity is influenced by the presence of different carboxylic compounds in the reservoir. These molecules strongly affect the water wetness of the rock, which has a dramatic impact on storage capacities and containment security. However, precise understanding of how these carboxylic acids influence the rock’s CO2-wettability is lacking. Experiments We thus systematically analysed these relationships as a function of pressure, temperature, storage depth and organic acid concentrations. A particular focus was on identifying organic acid conce

Synthesis of new ligand, namely [bis(2-(2-methyl-5-nitro-1H-imidazol-1-yl)ethyl) hydrogen borate] (BIB), utilizing the reaction of metronidazole with boric acid in mole ratio (2:1), as well as the metal complexes with [Ni(II) and Cu(II)], were synthesized. All synthesized compounds were characterized by utilizing spectroscopic techniques such as FTIR, 1H-NMR, thermal analysis (T.G., UV-Vis), and atomic absorption (A.A.S.), as well as micro elemental analysis (C.H.N.), melting point (m.p), magnetic susceptibility, molar conductivity, and chloride content measurements. All complexes were paramagnetic, and the electrolyte and the suggested geometries were tetrahedral for nickel and octahedral for copper. In addition, all the transition meta

Electrochemical Grinding (ECG) process is a mechanically assisted electrochemical process for material processing. The process is able to successfully machine electrically conducting harder materials at faster rate with improved surface finish and dimensional control. This research studies the effect of applied current, electrolyte concentration, spindle speed and the gap between workpiece and tool on hardness and material removal rate during electrochemical grinding for stainless steel 316. The characteristic features of the electrochemical grinding process are explored through Taguchi-design-based experimental studies. The better hardness can be obtained at 10 A of the current, 150 g/l of the electrolyte concentration, 0.3 mm of gap an

Micro metal forming has an application potential in different industrial fields. Flexible tool-assisted sheet metal forming at micro scale is among the forming techniques that have increasingly attracted wide attention of researchers. This forming process is a suitable technique for producing micro components because of its inexpensive process, high quality products and relatively high production rate. This study presents a novel micro deep drawing technique through using floating ring as an assistant die with flexible pad as a main die. The floating ring designed with specified geometry is located between the process workpiece and the rubber pad. The function of the floating ring in this work is to produce SS304 micro cups with profile

Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr