The concept of sustainability is one of the modern concepts that influenced the quality of the urban plans for the cities, through the interest in the environmental and social aspects as well as the economic aspect and the need to balance to achieve sustainable development.

The research aims to identify the most prominent methods of sustainable urban land use planning and the strategies developed within these approaches to achieve sustainable development. The research started from the problem of a knowledge gap in adopting sustainable approaches and strategies when planning urban land uses for the holy city of Karbala.

In the theoretical aspect, the concepts of sustainable development, sustainable planning methodologies a

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

L-arabinose isomerase from Escherichia coli O157:H7 Was immobilized with activated Bentonite from local markets of Baghdad, Iraq by 10% 3-APTES and treated with 10% aqueous glutaraldehyde, the results refer that the yield of immobilization was 89%, and pH profile of free and immobilized L-arabinose isomerase was 7 and 7.5 and it is stable at 6-8 for 60 min respectively, while, the optimum temperature was 30 and 35°C and it was stable at 35 and 40°C for 60 min but it loses more than 60 and 30% from its original activity at 50°C for free and immobilized L-arabinose isomerase respectively. Immobilized enzyme retained its full activity for 32 day, but it retained 73.58% of its original activity after storage for 60 d

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

Abstract
A two electrode immersion electrostatic lens used in the design
of an electron gun, with small aberration, has been designed using
the finite element method (FEM). By choosing the appropriate
geometrical shape of there electrodes the potential V(r,z) and the
axial potential distribution have been computed using the FEM to
solve Laplace's equation.
The trajectory of the electron beam and the optical properties of
this lens combination of electrodes have been computed under
different magnification conditions (Zero and infinite magnification
conditions) from studying the properties of the designed electron
gun can be supplied with Abeam current of 5.7*10-6 A , electron
gun with half acceptance

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

Big developments in technology have led to upset the balance of ideas, given of its own post new properties for products not provided by traditional technology, especially economic units operating within the industrial sector, and therefore it is important to develop the Iraqi industrial sector and interest to do its vital role in light Of progress technological, and the cost accounting has benefited from this technology to development its goals in the regulatory process through the use of non-destructive evaluation perspective in carrying out its functions and to provide appropriate assistance for the use of the products, which were traditional accounting does not take them into consideration. The research aims to a statement that the u

This article proposes a new technique for determining the rate of contamination. First, a generative adversarial neural network (ANN) parallel processing technique is constructed and trained using real and secret images. Then, after the model is stabilized, the real image is passed to the generator. Finally, the generator creates an image that is visually similar to the secret image, thus achieving the same effect as the secret image transmission. Experimental results show that this technique has a good effect on the security of secret information transmission and increases the capacity of information hiding. The metric signal of noise, a structural similarity index measure, was used to determine the success of colour image-hiding t