Algae have been used in different applications in various fields such as the pharmaceutical industry, environmental treatments, and biotechnology. Studies show that the preparation of nanoparticles by a green synthesis method is a promising solution to many medical and environmental issues. In the current study, the green alga Stigeoclonium attenuatum (Hazen) F.S. Collins 1909 was isolated and identified from the Al-Hillah River (Governorate of Babylon) in the middle of Iraq. The green synthesis by the aqueous extract of algae was used to prepare the nanoflakes of ZnO. Nanoflakes of ZnO are characterized by X-Ray diffraction (XRD) and scanning electron microscope (SEM) with flakes shape and dimensions ranging be

   The aim of the research is to use methods based on cost-based activities )ABC) to identify the activities that cause the costs resulting from the environmental impact of the gas filling company and then to manage on the basis of the activities to manage the costs of these activities, which in turn rationalizes the environmental costs by eliminating activities that do not add .The research a number of conclusions, the most important of which is that the management of the company should continuously seek to train and qualify its staff on the accounting systems, especially in the field of accounting of environmental costs, the high environmental costs by the company, bears as a result of its activity.

دور الذكاء الصناعي في تحقيق رضا الزبون وانعكاسه على محاسبة التكاليف بحث تطبيقي في شركة الصناعات الالكترونية

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

Management is considered as most important resource of the society ones in modern era and an exchange
point in societies’ lives in order to achieve its goals and wishes. So far, management behinds the new
electronic society has become different in shape and nature due to the force of the nature of information
technology that shapes the relationships between the world’s individuals at the national level but it goes
beyond the international ones. The study aims at identifying the impact of the electronic management’s
components upon the improvement of the quality of nursing care in Baghdad’s hospitals. The descriptive
design, with a sample-survey approach, is used as appropriate ones for the field study of social

The present study is a qualitative study that aims to investigate the way the Iraqi caricaturist,Dheaa Al-Hajjar uses caricatures to produce a satirical meaning humorously.Producing satire while at the same maintaining humor requires a creative thinking on the part of the caricaturist. Thus, the study examines the production of humorous satire in terms of creativity. The analysis is done from the cognitive linguistic point of view using Arthur Koestler's theory of bisociation as presented in his book The Act of Creation in 1964. The main principle on which the theory is based is that humor is created via linking (or bisociating in Koestler's terms) two habitually incompatible trains of thought in order to come up with a novel me

Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network

Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or

Numeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential a

Mobile-based human emotion recognition is very challenging subject, most of the approaches suggested and built in this field utilized various contexts that can be derived from the external sensors and the smartphone, but these approaches suffer from different obstacles and challenges. The proposed system integrated human speech signal and heart rate, in one system, to leverage the accuracy of the human emotion recognition. The proposed system is designed to recognize four human emotions; angry, happy, sad and normal. In this system, the smartphone is used to   record user speech and send it to a server. The smartwatch, fixed on user wrist, is used to measure user heart rate while the user is speaking and send it, via Bluetooth,