This study aimed at identifying the trend to applying the Joint Audit as an approach to improve the financial reports quality with all their characteristics (Relevance, Reliability, Comparability, Consistency), as well as enclose the difficulties that faced the auditors in the Gaza Strip in implementing the Joint Audit. In order to achieve the study aims, a measure was used to identify the trend to apply the Joint Audit and it was distributed to the study sample which is consisting of (119) individuals and retrieved thereof (99) valid for analysis, approximately (83.2%), (69) of them are Auditors, (30) financial managers and accountants. The researcher used the analytical descriptive method, and after analyzing the results, the s

This paper proposes a neuro-fuzzy system to model β-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for β-glucosidase. Second, each input’s optimized membership functions from the ANF

      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.       In this research, we pr

      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.

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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

A specific, sensitive and new simple method was used for the determination of methyldopa in pure and pharmaceutical formulations by using continuous flow injection analysis. This method is based on formation of ion pair compound between methyldopa and potassium hexacyanoferrate in acidic medium to obtain a yellow precipitate complex using long distance chasing photometer (NAG-ADF-300-2). The linear range for calibration graph was 0.05-35 mmol/L for cell A and 0.05-25 mmol/L for cell B, and LOD 1.4292 µg /200 µL for both cells with correlation coefficient (r) 0.9981 for cell A and 0.9994 for cell B, RSD% was lower than 0.5 % for n=8 for. The results were compared with classical method UV-Spectrophotometric at λ max=280 nm and turbi

Solid dispersion (SD) is one of the most widely used methods to resolve issues accompanied by poorly soluble drugs. The present study was carried out to enhance the solubility and dissolution rate of Aceclofenac (ACE), a BCS class II drug with pH-dependent solubility, by the SD method. Effervescent assisted fusion technique (EFSD) using different hydrophilic carriers (mannitol, urea, Soluplus®, poloxamer 188, and poloxamer 407) in the presence of an effervescent base (sodium bicarbonate and citric acid) in different drug: carrier: effervescent base ratio and the conventional fusion technique (FSD) were used to prepare ACE SD. Solubility, dissolution rate, Fourier transformation infrared spectroscopy (FTIR), PowderX-ray diffraction

     In this article, the lattice Boltzmann method with two relaxation time  (TRT)  for the  D2Q9 model is used to investigate numerical results for 2D flow. The problem is performed to show the dissipation of the kinetic energy rate and its relationship with the enstrophy growth for 2D dipole wall collision. The investigation is carried out for normal collision and oblique incidents at an angle of . We prove the accuracy of moment -based boundary conditions with slip and Navier-Maxwell slip conditions to simulate this flow. These conditions are under the effect of Burnett-order stress conditions that are consistent with the discrete Boltzmann equation. Stable results are found by using this kind of boundary condition where d

This study describes how fuzzy logic control FLC can be applied to sonars of mobile robot. The fuzzy logic approach has effects on the navigation of mobile robots in a partially known environment that are used in different industrial and society applications. The fuzzy logic provides a mechanism for combining sensor data from all sonar sensors which present different information. The FLC approach is achieved by means of Fuzzy Decision Making method type of fuzzy logic controller. The proposed controller is responsible for the obstacle avoidance of the mobile robot while traveling through a map from a home point to a goal point. The FLC is built as a subprogram based on the intelligent architecture (IA). The software program  uses th