The UN organization is considered one of the most important organizations at the international level. It has accomplished multiple tasks and roles of many different issues and events that hit the developing and advanced world countries. It has performed a series of procedures and laws that have had an impact on ending the wars and conflicts that plagued some countries and continued for a period of time in the past. Moreover, it has improved the level of the international relations between a number of countries due to the problems and incidents took place between them. It has relied on finding solutions and treatments for humanitarian problems such as the preservation of the environment, preventing the spread of epidemics and diseases Thi

The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

In humans, Pseudomonas aeruginosa is the second most frequent gram negative nosocomial pathogen in hospitals and has the highest case-fatality rate of all hospital-acquired bacteremia because of the hardy resistance of these bacteria to mechanical cleansing as well as to disinfectant, and many antibiotics. The susceptibility of bacteria against the antibiotics is modulated by several local factors such as temperature which modified drug efficacy, so this study was carried out to evaluate the effect of different temperature (20,42,45)Ċon the susceptibility of Pseudomonas aeruginosa to the minimum inhibitory concentrations (MIC) of the antimicrobial agents before and after irradiation. The samples collected from 150 persons suffering from

Background and purpose: Animal model helps researchers to evaluate new treatment plan for human and understand pathological mechanism involved in a development of disease. The use of rats as an animal model for Alzheimer's research has become a favorite among researchers. Rats are capable in mimicking Alzheimer disease due to their intelligence and quick adaptation to nature. At present there are several methods that can be used to induce Alzheimer's animals, but each method has advantages and disadvantages. We need to learn other methods that can provide many advantages and few disadvantages. The Amyloid-beta 42 (Aβ-42) and Reactive Oxygen Species (ROS) are thought to play an important role in the pathology of Alzheimer’s disease. Th

       The study aimed to reach the best rating for the views and variables in the totals characterized by qualities and characteristics common within each group and distinguish them from aggregates other for the purpose of distinguishing between Iraqi provinces which suffer from deprivation, for the purpose of identifying the status of those provinces in the early allowing interested parties and regulators to intervene to take appropriate corrective action in a timely manner. Style has been used cluster analysis Cluster analysis to reach the best rating to those totals from the provinces that suffer from problems, where the provinces were classified, based on the variables (Edu

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

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a