In this study, Cr−Mo−N thin films with different Mo contents were synthesised via closed field unbalanced magnetron sputtering ion plating. The effects of Mo content on the microstructure, chemical bonding state, and optical properties of the prepared films were investigated by X-ray diffraction spectroscopy (XRD), X-ray photoelectron spectroscopy (XPS), field emission scanning electron microscopy, and ultraviolet-visible spectrophotometry. XRD results determined the face centered cubic (fcc) structure of pure CrN film. The incorporation of molybdenum (Mo) in the CrN matrix was confirmed by both XRD and XPS analyses. The CrMoN coatings demonstrate various polycrystalline phases including CrN, γ-Mo2N, Cr with oxides layers of MoO3, CrO3

This work includes a detailed description of the Leucostoma nigricorpuris sp. nov. from
Iraq. Locality, host plants and data of collection were given.

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

The phenomenon of spatial variation in the economic, social and urban development levels is considered prevalent in most of the economic and social systems,this relates to the concentration of most of those activities in certain regions and because of their rarity in other regions , that led to the emergence of the problem of the sharp contrast between the most developed areas and least developed areas within the same region or within the regions of the same country,
Reduction of this variables , in addition to the development of areas through following up and relying on an effective regional development enabling to reduce unemployment as well as to stop the migration of the unplanned for population,
And the ideal use of available

AA wahid, journal mustansiriyah of sports science, 2023

Abstract:

                The internal control is the tool through which it is possible to verify and ensure the implementation of tasks in accordance with the established plans and programs and to evaluate the level of performance that is implemented within the different companies.

A guarantee from the supplier with the absence of a specialized technical committee that follows up the stages of implementing the contract and disbursing all amounts of financial dues to the supplier before completing the implementation of the contract and overlooking the non-implementation of some clauses of the contract by the committee in charge of

The primary focus of the study factor reverse polymerization styrene polymer kinetics and distribution weight Aljaia in Blma Aldhur free reverse The study was conducted wi Mamahakah and using the Monte Carlo method

This work studied the electrical and thermal surface conductivity enhancement of polymethylmethacrylate (PMMA) clouded by double-walled carbon nanotubes (DWCNTs) and multi-walled carbon nanotube (MWCNTs) by using pulsed Nd:YAG laser. Variable input factors are considered as the laser energy (or the relevant power), pulse duration and pulse repetition rate. Results indicated that the DWCNTs increased the PMMA’s surface electrical conductivity from 10-15 S/m to 0.813×103 S/m while the MWCNTs raised it to 0.14×103 S/m. Hence, the DWCNTs achieved an increase of almost 6 times than that for the MWCNTs. Moreover, the former increased the thermal conductivity of the surface by 8 times and the later by 5 times.