This research aims to present a proposed model for disclosure and documentation when performing the audit according to the joint audit method by using the questions and principles of the collective intelligence system, which leads to improving and enhancing the efficiency of the joint audit, and thus enhancing the confidence of the parties concerned in the outputs of the audit process. As the research problem can be formulated through the following question: “Does the proposed model for disclosure of the role of the collective intelligence system contribute to improving joint auditing?”   

The proposed model is designed for the disclosure of joint auditing and the role

هدف البحث إلى وضع رؤية مستقبلية وبناء أنموذج للجامعة المنتجة ، باستخدام أسلوب دلفاي بواقع جولتين إذ عرضت أداة البحث على 30 خبير واعتمدت نسبة 93 %حد أدنى لقبول الفقرة ، واستنتجت الباحثة إن معظم الجامعات لا تتوافر لديها الموارد الكافية وبالتالي فان تبني مفهوم الجامعة المنتجة يمثل أسلوبا مناسبا لواقع التمويل في تلك الجامعات ، إذ أن هناك حاجة ماسة إلى تدعيم مصادر تمويل التعليم الجامعي بموارد إنتاجية تحصل منها الجا

Abstract

                The research aims to identify the application of corporate governance requirements according to the international standard (ISO 26000:2010) in the National Insurance Company. Strengths and weaknesses were identified to study the current state of this requirement's application in the company under investigation. The descriptive-analytical approach was utilized through a checklist derived from ISO 26000:2010. Several personal interviews and field visits were conducted to understand the extent of application and documentation based on various statistical methods. The results revealed a level of applic

Abstract: Microfluidic devices present unique advantages for the development of efficient drug assay and screening. The microfluidic platforms might offer a more rapid and cost-effective alternative. Fluids are confined in devices that have a significant dimension on the micrometer scale. Due to this extreme confinement, the volumes used for drug assays are tiny (milliliters to femtoliters).

 In this research, a microfluidic chip consists of micro-channels carved on substrate materials built by using Acrylic (Polymethyl Methacrylate, PMMA) chip was designed using a Carbon Dioxide (CO₂) laser machine. The CO2 parameters have influence on the width, depth, roughness of the chip. In order to have regular

Abstract

  In this study, modified organic solvent (organosolv) method was applied to remove high lignin content in the date palm fronds (type Al-Zahdi) which was taken from the Iraqi gardens. In modified organosolv, lignocellulosic material is fractionated into its constituents (lignin, cellulose and hemicellulose). In this process, solvent (organic)-water is brought into contact with the lignocellulosic biomass at high temperature, using stainless steel reactor (digester). Therefor; most of hemicellulose will remove from the biomass, while the solid residue (mainly cellulose) can be used in various industrial fields. Three variables were studied in this process: temperature, ratio of ethano

The techniques of fractional calculus are applied successfully in many branches of science and engineering, one of the techniques is the Elzaki Adomian decomposition method (EADM), which researchers did not study with the fractional derivative of Caputo Fabrizio. This work aims to study the Elzaki Adomian decomposition method (EADM) to solve fractional differential equations with the Caputo-Fabrizio derivative. We presented the algorithm of this method with the CF operator and discussed its convergence by using the method of the Cauchy series then, the method has applied to solve Burger, heat-like, and, couped Burger equations with the Caputo -Fabrizio operator. To conclude the method was convergent and effective for solving this type of

The aim of this research is to use robust technique by trimming, as the analysis of maximum likelihood (ML) often fails in the case of outliers in the studied phenomenon. Where the (MLE) will lose its advantages because of the bad influence caused by the Outliers. In order to address this problem, new statistical methods have been developed so as not to be affected by the outliers. These methods have robustness or resistance. Therefore, maximum trimmed likelihood: (MTL) is a good alternative to achieve more results. Acceptability and analogies, but weights can be used to increase the efficiency of the resulting capacities and to increase the strength of the estimate using the maximum weighted trimmed likelihood (MWTL). In order to perform t

A systematic approach is presented to achieve the stable grasping of objects through a two-finger robotic hand, in which each finger cavity was filled with granular media. The compaction of the latter, controlled by vacuum pressure, was used to adjust the structural and contact stiffness of the finger. The grasping stability was studied under the concurrent effect of an external torque and applied vacuum pressure. Stable grasping was defined as the no slippage condition between the grasped object and the two fingers. Three control schemes were adopted and applied experimentally to ensure the effectiveness of the grasping process. The results showed that stable and unstable grasping regions exist for each combination of applied torqu

Sub-threshold operation has received a lot of attention in limited performance applications.However, energy optimization of sub-threshold circuits should be performed with the concern of the performance limitation of such circuit. In this paper, a dual size design is proposed for energy minimization of sub-threshold CMOS circuits. The optimal downsizing factor is determined and assigned for some gates on the off-critical paths to minimize the energy at the maximum allowable performance. This assignment is performed using the proposed slack based genetic algorithm which is a heuristic-mixed evolutionary algorithm. Some gates are heuristically assigned to the original and the downsized design based on their slack time determined by static tim

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c