Autorías: Abdulsahıb Mohammed Muneer, Habeeb Sabhan Maytham, Kazim Abed Emad. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 1, 2021. Artículo de Revista en Psyke.

The practice by the  administration of human resources  on effectiveness of organization  crisis as two knowledge fields , it were be until now as center for many studies, but the collect it, study of relation between them ,and The role of practices  by the  administration of human resources  on effectiveness of organization  crisis administration  were considered a new study and first according to the available and showing  studies at this field .

The problem of this research was specified by answer for the question that deal for size of consciousness at the ministry of interior for import of&nbs

The objective of the study: To diagnose the reality of the relationship between the fluctuations in world oil prices and their reflection on the trends of government spending on the various economic sectors.

The research found: that public expenditures contribute to the increase of national consumption through the purchase of consumer goods by the state for the performance of the state's duties or the payment of wages to employees in the public sector and thus have a direct impact on national consumption

The results of the standard tests showed that there is no common integration between the oil price fluctuations and the government expenditure on the security sector through the A

Abstract The goal of current study was to identify the relationship between addiction of self-images (Selfie) and personality disorder of narcissus, and the difference of significance the relationship between addiction self-images (selfie) and personality disorder narcissus at students of Mustansiriya university, addiction self- images (selfie) defined: a photograph that one has taken of oneself, typically one taken with a smartphone or webcam and shared via social media, edit and down lowed to social networking sites, and over time, the replacement of normal life virtual world, which is accompanied by a lack of a sense of time, and the formation of repeated patterns increase the risk of social and personal problems. To achieve the goals

The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co

Kidney tumors are of different types having different characteristics and also remain challenging in the field of biomedicine. It becomes very important to detect the tumor and classify it at the early stage so that appropriate treatment can be planned. Accurate estimation of kidney tumor volume is essential for clinical diagnoses and therapeutic decisions related to renal diseases. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors that addresses the challenges of accurate kidney tumor volume estimation caused by extensive variations in kidney shape, size and orientation across subjects.
In this paper, have tried to implement an automated segmentati

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