Internal control system is a safety valve that preserves economic units assets and ensure the accuracy of financial data, as well as to obligation in the laws, regulations, administrative policies ,and improve the efficiency, effectiveness and economic of operation, so it has become imperative for these units attention to internal and developed control system The research problem in exposure the economic units when the exercise of their business to many of the risks to growth or hinder the achievement of its objectives and the risks (financial, operational, strategy, risk) and not it rely on risk Assessment according to modern scientific methods, as in Brown's risk Classification, Which led to the weakness of the internal control identif

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

The aim of this study was to compare the effect of conventional implant site preparation technique and a combination of conventional/piezosurgery preparation on implant stability measured at different time intervals, insertion torque, and preparation time. A randomized controlled study was designed, it included 26 patients who received 54 dental implants randomly assigned to 2 groups; in the control group, implants were installed after conventional preparation with drills whereas the study group received implants after mixed conventional/piezosurgery preparation. The outcome variables included: implant stability measured immediately after implant insertion, at 8 weeks and 16 weeks postoperatively, insertion torque and preparation time. All

A single-blind randomized controlled clinical trial in patients with deep caries and symptoms of reversible pulpitis compared outcomes from a self-limiting excavation protocol using chemomechanical Carisolv gel/operating microscope (self-limiting) versus selective removal to leathery dentin using rotary burs (control). This was followed by pulp protection with mineral trioxide aggregate (MTA) and restoration with glass ionomer cement and resin composite, all in a single visit. The pulp sensibility and periapical health of teeth were assessed after 12 mo, in addition to the differences in bacterial tissue concentration postexcavation. Apical radiolucencies were assessed using cone beam computed tomography/periapical radiographs (CBC

Lead toxicity elicits neurological damage which is a well-known disorder that has been considered to be a major cause for multiple condition such as behavioral defect; mental retardation; and nerve insufficient activity.

This research is designed to estimate potential protective effect of vinpocetine on neurotoxicity stimulated by lead acetate in rats.

Eighteen adult rats of both sexes were randomly enrolled into three groups. Each group includes 6 rats as followings: Group I- Rats were given 0.3ml normal saline solution orally; then intraperitoneal injection of 100μl of the normal saline was given 1h later; this group was considered as control. Group II- Rats were given an intraperitoneal injection of 20mg/kg lead acetate

Permeability determination in Carbonate reservoir is a complex problem, due to their capability to be tight and heterogeneous, also core samples are usually only available for few wells therefore predicting permeability with low cost and reliable accuracy is an important issue, for this reason permeability predictive models become very desirable.

   This paper will try to develop the permeability predictive model for one of  Iraqi carbonate reservoir from core and well log data using the principle of Hydraulic Flow Units (HFUs). HFU is a function of Flow Zone Indicator (FZI) which is a good parameter to determine (HFUs).

   Histogram analysis, probability analysis and Log-Log plot of Reservoir Qua

The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be

Software-Defined Networking (SDN) has evolved network management by detaching the control plane from the data forwarding plane, resulting in unparalleled flexibility and efficiency in network administration. However, the heterogeneity of traffic in SDN presents issues in achieving Quality of Service (QoS) demands and efficiently managing network resources. SDN traffic flows are often divided into elephant flows (EFs) and mice flows (MFs). EFs, which are distinguished by their huge packet sizes and long durations, account for a small amount of total traffic but require disproportionate network resources, thus causing congestion and delays for smaller MFs. MFs, on the other hand, have a short lifetime and are latency-sensitive, but they accou