The paper presents a highly accurate power flow solution, reducing the possibility of ending at local minima, by using Real-Coded Genetic Algorithm (RCGA) with system reduction and restoration. The proposed method (RCGA) is modified to reduce the total computing time by reducing the system in size to that of the generator buses, which, for any realistic system, will be smaller in number, and the load buses are eliminated. Then solving the power flow problem for the generator buses only by real-coded GA to calculate the voltage phase angles, whereas the voltage magnitudes are specified resulted in reduced computation time for the solution. Then the system is restored by calculating the voltages of the load buses in terms

This research will deal in a simple way with the concept of urban expansion and taking the decision to sign the spatial signature of residential investment projects in order to reach through them in a real way to the extent of the proportionality of the decision taken, in light of the fulfillment of the conditions that must be met in the matter of making the decision of the spatial signature of the residential investment project and the extent of commitment to them, in which the conditions are: (Ease of access to services and transportation, adequacy of services, commitment to urban land uses) when establishing the investment project represented by the Al-Ayad residential project in the Hittin neighborhood of Al

Image compression is a serious issue in computer storage and transmission,  that simply makes efficient use of redundancy embedded within an image itself; in addition, it may exploit human vision or perception limitations to reduce the imperceivable information Polynomial coding is a modern image compression technique based on modelling concept to remove the spatial redundancy embedded within the image effectively that composed of two parts, the  mathematical model and the residual. In this paper, two stages proposed technqies adopted, that starts by utilizing the lossy predictor model along with multiresolution base and thresholding techniques corresponding to first stage. Latter by incorporating the near lossless com

Water has been acknowledged as one of the key issues of humanity in modern society and worldwide economic advancements, especially with the continuing reductions in fresh-water supply. Solar energy, which is abundant as well as widely available in various fields, has the potential to solve the global challenges of long-term freshwater and energy reduction. Researchers are attempting to address the problem in a variety of methods. Due to the fact that solar energy is the foundation for freshwater, several researches have applied it for improving the effectiveness of solar desalination, evaporation, and wastewater treatment. One of the novel methods used for achieving this is known as “hydrogel,” which comes in a variety of forms. As a un

The clutch system is essential for gently transmitting power from the engine to the gearbox, in addition to other tasks such as absorbing vibration, inertia reducing, and working as a protector against the overload for the motor and the components of power transmission. A new approach is developed for this research paper, to find a dry clutch system’s optimal design and operational parameters to improve performance and thermal behavior. Three design factors were selected to design the numerical tests based on the Taguchi method which are the friction material, the applied pressure function, and the dimensionless radius ratio R. A three-dimensional finite element model was developed, and the numerical cases were designed using the Taguchi

This study examines strategies of cultural domestication in Muravyov and Kistyakovsky’s Russian translation of (The Fellowship of the Ring). It documents transformations of character names, toponyms, dialogues, and cultural references, highlighting systematic Russification and the infusion of Soviet political commentary that reshape the text into cultural rewriting.

Modern machine-learning applications require GPUs, and modern platforms can leverage numerous GPUs on one or more machines to increase performance. Contemporary deep-learning models are too huge for CPU or GPU training. Training these models with many GPUs without performance degradation is necessary to train them rapidly and maximize GPU consumption. Thus, training deep convolutional neural networks (DCNN) with multiple GPUs has become necessary for improving training. Therefore, we presented a parallel design and development of an efficient model for enhancing face mask CNN performance and improving resource efficiency. This DCNN model is a parallel training system over multiple GPUs, a multi-core CPU, and a multi-process GPU platform wit

النظام السياسي اليمني : دراسة في المتغيرات الداخلية

This paper introduces a relationship between the independence of polynomials associated with the links of the network, and the Jacobian determinant of these polynomials. Also, it presents a way to simplify a given communication network through an algorithm that splits the network into subnets and reintegrates them into a network that is a general representation or model of the studied network. This model is also represented through a combination of polynomial equations and uses Groebner bases to reach a new simplified network equivalent to the given network, which may make studying the ability to solve the problem of network coding less expensive and much easier.