The research amid to find out the extent of Iraqi oil companies commitment to implement internal control procedures in accordance with the updated COSO framework. As the research problem was represented in the fact that many of the internal control procedures applied in the Iraqi oil companies are incompatible with most modern international frameworks for internal control, including the integrated COSO framework, issued by the Committee of Sponsoring Organizations of the Tradeway Committee. The research followed the quantitative approach to handling and analysing data by designing a checklist to represent the research tool for collecting data. The study population was represented in the Iraqi oil companies, while the study sample

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

Nowad ays, with the development of internet communication that provides many facilities to the user leads in turn to growing unauthorized access. As a result, intrusion detection system (IDS) becomes necessary to provide a high level of security for huge amount of information transferred in the network to protect them from threats. One of the main challenges for IDS is the high dimensionality of the feature space and how the relevant features to distinguish the normal network traffic from attack network are selected. In this paper, multi-objective evolutionary algorithm with decomposition (MOEA/D) and MOEA/D with the injection of a proposed local search operator are adopted to solve the Multi-objective optimization (MOO) followed by Naï

Due to advancements in computer science and technology, impersonation has become more common. Today, biometrics technology is widely used in various aspects of people's lives. Iris recognition, known for its high accuracy and speed, is a significant and challenging field of study. As a result, iris recognition technology and biometric systems are utilized for security in numerous applications, including human-computer interaction and surveillance systems. It is crucial to develop advanced models to combat impersonation crimes. This study proposes sophisticated artificial intelligence models with high accuracy and speed to eliminate these crimes. The models use linear discriminant analysis (LDA) for feature extraction and mutual info

     Feature selection, a method of dimensionality reduction, is nothing but collecting a range of appropriate feature subsets from the total number of features. In this paper, a point by point explanation review about the feature selection in this segment preferred affairs and its appraisal techniques are discussed. I will initiate my conversation with a straightforward approach so that we consider taking care of features and preferred issues depending upon meta-heuristic strategy. These techniques help in obtaining the best highlight subsets. Thereafter, this paper discusses some system models that drive naturally from the environment are discussed and calculations are performed so that we can take care of the prefe

            Eye Detection is used in many applications like pattern recognition, biometric, surveillance system and many other systems. In this paper, a new method is presented to detect and extract the overall shape of one eye from image depending on two principles Helmholtz & Gestalt. According to the principle of perception by Helmholz, any observed geometric shape is perceptually "meaningful" if its repetition number is very small in image with random distribution. To achieve this goal, Gestalt Principle states that humans see things either through grouping its similar elements or recognize patterns. In general, according to Gestalt Principle, humans see things through genera

Objectives: To determine the effectiveness of the instructional program on patients’ knowledge about home safety while receiving anti-cancer treatment at  Al- Karama Teaching Hospital in Al-Kut City.

Methodology:   A quasi-experimental design is conducted through the application of a pre-test and post-test approach for the study and control groups from February 5^th, 2020 to April 25^th, 2020. A non–probability (purposive) sample of (50) patients treated at the Blood Disease and Oncology Center is selected and divided into two groups. Each group contains (25) patients as control and study groups. An instrument is constructed that is comprised of two parts; t

Objective: The aims of present study to detect the effectiveness of instruction program of non-pharmacological guideline on blood pressure and laboratory test.

Methodology: A pre-experimental study was conducted in Al-Sader Teaching Hospital   from 8^th of September 2019 to 25^th of May 2020, in order to find out the effectiveness of instruction program concerning non-pharmacological guideline on controlling essential hypertension among patients. A non- probability (purposive sample) of 50 patients with essential hypertension is selected. Those patients are already diagnosed with Essential Hypertension