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

تم التطرق في هذا البحث الى دور الذكاء الاصطناعي والتكنولوجيا الحديثة في العملية التدريبية بما يخدم أهدافه والاستفادة منه من خلال المخرجات الجيدة، حيث ان توظيف التكنولوجيا في تدريب رياضة المبارزة يسهل العملية التدريبية على المدرب واللاعب ويساهم في تقليل الجهد المبذول والوقت المستغرق ، وهدفت الدراسة الى التعرف على تأثير الجهاز المصنع في ضبط المسافة بين القدمين لدى عينة البحث  ،استخدم المنهج التجريبي بت

In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN),

The environmental problems that have emerged recently as a result of pressure on the environment due to the increase in population size, especially in urban cities, where this increase was accompanied by the need for housing as well as the need for services and activities. This led to the establishment of many vertical residential buildings represented by residential complexes within the urban fabric of the city of Baghdad. As part of following the methodology of urban dictation policies in empty areas, and to accommodate the largest number of residents as a result of the multiplicity of floors and housing, these buildings must be subject to the standards and requirements of sustainability at the level of their spatial location and their

The Ottomans ruled Turkey for nearly six centuries, during which the Ottoman Empire passed through varying periods in terms of strength, influence, and the area of ​​land they ruled.  In the last decade of its rule, the Ottoman Empire was severely weakened in all political, military, administrative and economic aspects. In addition to the internal strife that was stirred up by the leaders of the Association (Union and Progression), that organization that led the coup movement against the Ottoman Empire later.

After the abolition of the Sultanate and the proclamation of the Turkish Republic, the social fabric in Turkey changed, and many customs and traditions alien to it emerged to society. One of the thing

The COVID-19 pandemic has had a huge influence on human lives all around the world. The virus spread quickly and impacted millions of individuals, resulting in a large number of hospitalizations and fatalities. The pandemic has also impacted economics, education, and social connections, among other aspects of life. Coronavirus-generated Computed Tomography (CT) scans have Regions of Interest (ROIs). The use of a modified U-Net model structure to categorize the region of interest at the pixel level is a promising strategy that may increase the accuracy of detecting COVID-19-associated anomalies in CT images. The suggested method seeks to detect and isolate ROIs in CT scans that show the existence of ground-glass opacity, which is fre

     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E

An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th