This study proposed control system that has been presented to control the electron lens resistance in order to obtain a stabilized electron lens power. This study will layout the fundamental challenges, hypothetical plan arrangements and development condition for the Integrable Optics Test Accelerator (IOTA) in progress at Fermilab. Thus, an effective automatic gain  control (AGC) unit has been introduced which prevents fluctuations in the internal resistance of the electronic lens caused by environmental influences to affect the system's current and power values ​​and keep them in stable amounts. Utilizing this unit has obtained level balanced out system un impacted with electronic lens surrounding natural varieties.

This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

Background Due to the intermittent, nonlinear, and uncertain behavior of renewable energy sources (res) such as solar and wind, grid stability and reliability require very high forecasting and optimization skills as widely reported in the literature. Traditional optimization methods work very well in small or static systems but are suffer difficulty on large-scale, dynamic and stochastic renewable environment due to their NP-hard nature. Methods The framework introduces the concept of a Machine Learning-Assisted Hybrid Cuckoo Search (ML-HCS) that combines CS with a hybrid metaheuristic and integrates Long Short-Term Memory (LSTM) networks for forecasting based on both regression models of LSTMs and hybrid optimization algorithm

Delivering therapeutic agents to the brain remains a major challenge due to the restrictive nature of the blood–brain barrier (BBB). Intranasal administration has emerged as a promising, non-invasive approach that bypasses the BBB and facilitates direct nose-to-brain transport via the olfactory and trigeminal pathways. In this study, we developed a nanostructured lipid carrier (NLC) system for the intranasal delivery of dolutegravir sodium, a potent integrase inhibitor, with the goal of enhancing brain bioavailability for the treatment of neuroHIV and related central nervous system (CNS) complications. The NLCs were optimized for particle size, polydispersity index (PDI), and drug incorporation efficiency. The optimized formulation exhibi

The effect of mental and physical health on the feelings of subject welfare is known as health-related quality of life. The chronic obstructive pulmonary disease is a common respiratory diseases. Assessment of health-related quality of life is considered important in such chronic disease. The objective of the current study was to measure health-related quality of life in a sample of chronic obstructive pulmonary  patients in AL- Diwanyia city/Iraq. This study was carried out on 150 already diagnosed COPD patients who attended to the Center of Respiratory Diseases/AL-Diwaniyah Teaching Hospital during September  2019 to January 2020. The Arabic version of St George’s Respiratory Questionnaire was used to asses

Abstract:

 The research concerned the study of the railway transport sector in selected countries that sought to raise the efficiency of the railway network and develop it, after realizing the importance of this vital sector, which is a link between it and the rest of the other economic sectors.

The research sought to explain the methods, methods and procedures adopted by these countries for the development of the railway sector, and to benefit from these experiments to improve the efficiency of the railway transport sector in Iraq.

The railway transport sector in Iraq suffers from the erosion of railway lines and mobile units such as locomotives, pas

For criminal investigations, fingerprints remain the most reliable form of personal identification despite developments in other fields like DNA profiling. The objective of this work is to compare the performance of both commercial charcoal and activated carbon powder derived from the Alhagi plant to reveal latent fingerprints from different non-porous surfaces (cardboard, plain glass, aluminum foil sheet, China Dish, Plastic, and Switch). The effect of three variables on activated carbon production was investigated. These variables were the impregnation ratio (the weight ratio of KOH: dried raw material), the activation temperature, and the activation time. The effect factors were investigated using Central Composite Design