Abstract. Fibrewise micro-topological spaces be a useful tool in various branches of mathematics. These mathematical objects are constructed by assigning a micro-topology to each fibre from a fibre bundle. The fibrewise micro-topological space is then formed by taking the direct limit of these individual micro-topological spaces. It can be adapted to analyze various mathematical structures, from algebraic geometry to differential equations. In this study, we delve into the generalizations of fibrewise micro-topological spaces and explore the applications of these abstract structures in different branches of mathematics. This study aims to define the fibrewise micro topological space through the generalizations that we use in this paper, whi

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

In this paper, a design of the broadband thin metamaterial absorber (MMA) is presented. Compared with the previously reported metamaterial absorbers, the proposed structure provides a wide bandwidth with a compatible overall size. The designed absorber consists of a combination of octagon disk and split octagon resonator to provide a wide bandwidth over the Ku and K bands' frequency range. Cheap FR-4 material is chosen to be a substate of the proposed absorber with 1.6 thicknesses and 6.5×6.5 overall unit cell size. CST Studio Suite was used for the simulation of the proposed absorber. The proposed absorber provides a wide absorption bandwidth of 14.4 GHz over a frequency range of 12.8-27.5 GHz with more than %90 absorp

Abstract
Objectives: this study aims to: (1). Assess self-esteem level and academic achievement for students of nursing colleges in southern Iraq. (2). Determine the relationship between levels of self-esteem and academic achievement of the student in the first semester. (3). Identify differences of self-esteem with gender and different age groups.
Methodology: a sample of (426 students) was purposively selected then collected by using a questionnaire which consisted of: I- Sociodemographic characteristics for assessing some important aspects of students, II- Rosenberg's Self-Esteem Scale (RSES) III- Iraq Grading Scale for assessing student achievement. Finally statistical analysis (SPSS) for data processing.
Results: study resu

The prediction process of time series for some time-related phenomena, in particular, the autoregressive integrated moving average(ARIMA) models is one of the important topics in the theory of time series analysis in the applied statistics. Perhaps its importance lies in the basic stages in analyzing of the structure or modeling and the conditions that must be provided in the stochastic process. This paper deals with two methods of predicting the first was a special case of autoregressive integrated moving average which is ARIMA (0,1,1) if the value of the parameter equal to zero, then it is called Random Walk model, the second was the exponential weighted moving average (EWMA). It was implemented in the data of the monthly traff

Abstract

In the field of construction materials the glass reinforced mortar and Styrene Butadiene mortar are modern composite materials. This study experimentally investigated the effect of addition of randomly dispersed glass fibers and layered glass fibers on density and compressive strength of mortar with and without the presence of Styrene Butadiene Rubber (SBR). Mixtures of 1:2 cement/sand ratio and 0.5 water/cement ratio were prepared for making mortar. The glass fibers were added by two manners, layers and random with weight percentages of (0.54, 0.76, 1.1 and 1.42). The specimens were divided into two series: glass-fiber reinforced mortar without SBR and glass-fiber reinforced mortar with 7% SBR of mixture water. All s

The study relied on data about the health sector in Iraq in 2006 in cooperation with the Ministry of Health and the Central Bureau of Statistics and Information Technology in 2007 Included the estimates of the population distribution of the Baghdad province and the country depending on the population distribution for 1997,evaluate the health sector which included health institutions, and health staff, and other health services. The research Aimis; Measurement an amount and size of the growth of health services (increase and decrease) and the compare of verified in Iraq and Baghdad, and evaluate the effectiveness of the distribution of supplies and health services (physical and human) of the size of the population distribution and

      In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of  specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-