In general, path-planning problem is one of most important task in the field of robotics. This paper describes the path-planning problem of mobile robot based on various metaheuristic algorithms. The suitable collision free path of a robot must satisfies certain optimization criteria such as feasibility, minimum path length, safety and smoothness and so on. In this research, various three approaches namely, PSO, Firefly and proposed hybrid FFCPSO are applied in static, known environment to solve the global path-planning problem in three cases. The first case used single mobile robot, the second case used three independent mobile robots and the third case applied three follow up mobile robot.  Simulation results, whi

      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.       In this research, we pr

Background: Acute idiopathic thrombocytopenic purpura (ITP) is a self – limiting illness, usually occurring after an infectious disease, and it is due to decrease number of circulating platelets manifests as a bleeding tendency, easy bruising (purpura), or extravasations of blood from capillaries into skin and mucous membranes.                                                                   &n

Summary:
Background: Pneumonia is a common form of lower respiratory tract infection (LRTI) in children under five years of age and it is the leading cause of morbidity and mortality in this age group. Early management is important in decreasing its complications and mortality.
Methods: A cross sectional study of 100 patients, their ages ranged from 2 months to 5 years. They were admitted to Children Welfare Teaching Hospital Medical City–Baghdad in a period from 7th of November 2010 to 5th of May 2011, suffering from Lower Respiratory Tract Infections (fever, cough and tachypnea) and classified into two groups according to chest radiograph (CXR) findings, those with a patch (pneumonia) and others with normal or hyper inflated CX

     Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med