Assessment of the in service behavior of asphalt stabilized subgrade soil under environmental impact has got little attention by the research workers. However, the sustainability of the roadway depends mainly on the welfare of its subgrade soil condition. In this work, Gypseous soil was stabilized with asphalt emulsion for subgrade usage, the durability of the mixture has been assessed in term of its ability to maintain the compressive strength when practicing the environmental impacts. Specimens of 38 mm in diameter , and 76 mm in height have been prepared with various water-asphalt percentages, and subjected to 30 cycles of (freezing-thawing), (heating-cooling) and (wetting-drying) processes. Specimens have been tested for unconfined comp

Porous asphalt paving is a modern design method that differs from the usual asphalt pavements' traditional designs. The difference is that the design structure of porous pavements allows the free passage of fluids through their layers, which controls or reduces the amount of runoff or water accumulated in the area by allowing the flow of rain and surface runoff.  The cross-structure of this type of paving works as a suitable method for managing rainwater and representing groundwater recharge. The overall benefits of porous asphalt pavements include environmental services and safety features, including controlling the build-up of contaminated metals on the road surface, rainwater management, resistance to slipping ac

     The research tagged (Perceived Organizational Support in High Performance) deals with identifying the extent of the impact of perceived organizational support as an explanatory variable on high performance as a response variable for the purpose of reaching appropriate mechanisms that enable colleges of the University of Baghdad to exploit the perceived organizational support in achieving the required high performance and pursuit of its goals. The researcher relied on the descriptive and analytical approach in carrying out the research. An intentional sample was selected and reached (70) persons from the higher leadership of the colleges represented by (deans, assistants deans, heads of departments) that r

In this paper, Nordhaus-Gaddum type relations on open support independence number of some derived graphs of path related graphs under addition and multiplication are studied.

In this study, the response and behavior of machine foundations resting on dry and saturated sand was investigated experimentally. In order to investigate the response of soil and footing to steady state dynamic loading, a physical model was manufactured. The manufactured physical model could be used to simulate steady state harmonic load at different operating frequencies. Total of (84) physical models were performed. The parameters that were taken into considerations include loading frequency, size of footing and different soil conditions. The footing parameters were related to the size of the rectangular footing and depth of embedment. Two sizes of rectangular steel model footing were used (100 200 12.5 mm) and (200 400 5.0 mm).

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

 Data Driven Requirement Engineering (DDRE) represents a vision for a shift from the static traditional methods of doing requirements engineering to dynamic data-driven user-centered methods. Data available and the increasingly complex requirements of system software whose functions can adapt to changing needs to gain the trust of its users, an approach is needed in a continuous software engineering process. This need drives the emergence of new challenges in the discipline of requirements engineering to meet the required changes. The problem in this study was the method in data discrepancies which resulted in the needs elicitation process being hampered and in the end software development found discrepancies and could not meet the need

In this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.

In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.

Three-dimensional (3D) image and medical image processing, which are considered big data analysis, have attracted significant attention during the last few years. To this end, efficient 3D object recognition techniques could be beneficial to such image and medical image processing. However, to date, most of the proposed methods for 3D object recognition experience major challenges in terms of high computational complexity. This is attributed to the fact that the computational complexity and execution time are increased when the dimensions of the object are increased, which is the case in 3D object recognition. Therefore, finding an efficient method for obtaining high recognition accuracy with low computational complexity is essentia