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

'Steganography is the science of hiding information in the cover media', a force in the context of information sec, IJSR, Call for Papers, Online Journal

Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre

In this paper, a random transistor-transistor logic signal generator and a synchronization circuit are designed and implemented in lab-scale measurement device independent–quantum key distribution systems. The random operation of the weak coherent sources and the system’s synchronization signals were tested by a time to digital convertor.

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

Incivility in nursing education can negatively affect the academic achievement. As there is no tool in Arabic to assess incivility among nursing students, there is a need for a valid and reliable tool.

The current research aims at extracting the standard characteristics of the emotional balance of the university students according to the response theory. This was accomplished by following accredited scientific steps, to achieve this goal, the researcher followed scientific steps in the procedures of the analysis of the scale. She translated the scale from English to Arabic and then made a reverse translation. it was presented to a committee of experts in English to ensure and verify the validity of the paragraphs logically and prove the face validity of the scale, which consists of (30) paragraphs, it was presented to (6) experts who are specialists in the educational and psychological sciences and in the light of their observations ha