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

Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

An aircraft's landing stage involves inherent hazards and problems associated with many factors, such as weather, runway conditions, pilot experiences, etc. The pilot is responsible for selecting the proper landing procedure based on information provided by the landing console operator (LCO). Given the likelihood of human decisions due to errors and biases, creating an intelligent system becomes important to predict accurate decisions. This paper proposes the fuzzy logic method, which intends to handle the uncertainty and ambiguity inherent in the landing phase, providing intelligent decision support to the pilot while reducing the workload of the LCO. The fuzzy system, built using the Mamdani approach in MATLAB software, considers critical

The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone

miRNAs regulate protein abundance and control diverse aspects of cellular processes and biological functions in metabolic diseases, such as obesity and diabetes. Lethal-7(Let-7) miRNAs specifically target genes associated with diabetes and have a role in the regulation of peripheral glucose metabolism. The present study aimed to describe the gene expressions of the let-7a gene with the development of diabetes in Iraq and the difference in the expression of this gene in patients with diabetes and healthy individuals. The association between age and gender with the development of diabetes was studied in this study and the results were compared with those of healthy individuals in the group of control. Based on the obtained results, there was

Background: Chronic myelogenous leukemia is a malignant hematological disease of hematopoietic stem cells. It is difficult to adapt treatment to each patient's risk level because there are currently few clinical tests and no molecular diagnostics that may predict a patient's clock for the advancement of CML at the time of chronic phase diagnosis. Biomarkers that can differentiate people based on the outcome at diagnosis are needed for blast crisis prevention and response improvement. Objective: This study is an effort to exploit the SLC25A3 gene as a potential biomarker for CML. Methods: RT-qPCR was applied to assess the expression levels of the SLC25A3 gene. Results: In comparison to the mean ΔCt of the control group, which was found to b

Celiac disease (CD) is an autoimmune disorder characterized by chronic inflammation that essentially affects the small intestine and is caused by eating gluten-containing foods. This study sought to determine gene expression of NLRP3 Inflammasome in peripheral blood of Iraqi CD children using quantitative real-time PCR (qRT-PCR) assay. Thirty children with CD (12 males and 18 females) were enrolled in the study and their age range was 3-15 years. The diagnosis of the disease was confirmed by serological examinations and intestinal endoscopy. A control sample of 20 age-matched healthy children was also included. The children were stratified for age, gender, body max index (BMI), histological findings, and marsh classification. Furthe

Iris research is focused on developing techniques for identifying and locating relevant biometric features, accurate segmentation and efficient computation while lending themselves to compression methods. Most iris segmentation methods are based on complex modelling of traits and characteristics which, in turn, reduce the effectiveness of the system being used as a real time system. This paper introduces a novel parameterized technique for iris segmentation. The method is based on a number of steps starting from converting grayscale eye image to a bit plane representation, selection of the most significant bit planes followed by a parameterization of the iris location resulting in an accurate segmentation of the iris from the origin