ZnS nanoparticles were prepared by a simple microwave irradiation method under mild condition. The starting materials for the synthesis of ZnS quantum dots were zinc acetate (R & M Chemical) as zinc source, thioacetamide as a sulfur source and ethylene glycol as a solvent. All chemicals were analytical grade products and used without further purification. The quantum dots of ZnS with cubic structure were characterized by X-ray powder diffraction (XRD), the morphology of the film is seen by scanning electron microscopy (SEM). The particle size is determined by field effect scanning electron microscopy (FESEM), UV-Visible absorption spectroscopy and XRD. UV-Visible absorption spectroscopy analysis shows that the absorption peak of the as-prep

Segmented regression consists of several sections separated by different points of membership, showing the heterogeneity arising from the process of separating the segments within the research sample. This research is concerned with estimating the location of the change point between segments and estimating model parameters, and proposing a robust estimation method and compare it with some other methods that used in the segmented regression. One of the traditional methods (Muggeo method) has been used to find the maximum likelihood estimator in an iterative approach for the model and the change point as well. Moreover, a robust estimation method (IRW method) has used which depends on the use of the robust M-estimator technique in

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

Autorías: Wafaa Sabah Mohammed Al-Khafaji, Fatimah Hameed Kzar Al-Masoodi, Suadad Ibrahim Suhail Al-Kinani. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 3, 2023. Artículo de Revista en Dialnet.

With the great development in the field of the Internet, the talk about the new media and its implications began, And its interactive services have made the future of media material sometimes participating in it and manufacturing it at other times,
the public is seeking information and choosing the appropriate ones, as well as exchanging messages with the sender after what the role of the receiver is just receiving information only.
This study aims to demonstrate the effects of using digital media in various forms and types to construct the value system of Iraqi society through the identification of the following aims:
Identify the most popular digital media for the Iraqi public in their daily lives on the Internet.
Identify

In this work, the effect of ceramic coating on performance, exhaust gas temperature and gases emissions of diesel engine operated on diesel fuel and biodiesel blends was investigated. A conventional four stroke, direct injected, single cylinder, diesel engine was tested at constant speed and at different load conditions using diesel fuel and biodiesel blends. The inlet and exhaust valves, the head of piston and cylinder head of the engine were coated by ceramic materials. Ceramic layers were made of (210-240) μm of Al2O3 and (30-60) μm of 4NiCr5Al as a bond coat for inlet and exhaust valves and (350-400) μm of YSZ and (50-100) μm of 4NiCr5Al as a bond coat for head of piston and (280-320) μm of Sic and (40-80) μm of 4NiCr5Al as a b