Sustainability is providing the needs without compromising the ability of the strategical forming to meet their requirements. The production of warm asphalt mixtures using recycled pavements produces economic and environmentally friendly mixtures, which is the most important advantage of this work. This research aims to determine the effect of recycled asphalt concrete (RAP) on the indirect tensile strength of warm asphalt mixtures and Marshall Properties. Models of warm asphalt mixtures using Aggregate from the Al-Nibaay quarry, Asphalt with a degree of penetration (40-50) from the refinery of the cycle, and obtained Recycled asphalt concrete from Salah Al-Din Road, Al-Ameriya area in Baghdad are prepared. Use five rati

Background: Evaluation and measurement of primary stability could be achieved by several methods, including the resonance frequency analysis (RFA) and implant insertion torque (IT) values. The need for a sufficient primary stability, guaranteed by an adequate insertion torque and implant stability quotient values, increased its importance mainly in one stage implants or in immediate loading protocols. The aims of this study was to find if there is a correlation between the peak insertion torque (PIT) and ISQ values of implants inserted in the jaws of different bone quality which regarded as two important clinical determinant factors for prediction of implant primary stability, and to evaluate and compare whether an experienced clinician cou

The present work aims to investigate approaches, measures and detection of indoor radon level in buildings of the department of physics in college of science of Baghdad University. CR-39 solid state nuclear track detectors were used to measure the radon concentrations inside the rooms, including five laboratories and five workplace rooms in ground and first storey of the department. The average radon concentration at first storey was found to be 43.1±13.2 Bq/m3 and 40.1±13.4 Bq/m3 at the ground storey. The highest level of radon concentration at the first storey in the radioactive sources store was 87.5±29 Bq/m3 while at the ground storey in room(2) was 70.2±24 Bq/m3 which is due to the existence radioactive sources in some selected

The tourism activity is one of the pillars on which the economy of any country is based , the importance of the tourism sector is reflected in its potential to become an effective development alternative in many countries, especially Iraq ,this has a direct impact on the national economy as an important source in attracting hard currency and eliminating unemployment. Adding the Iraqi Marshlands to the list of effects makes it contribute to diversification of sources of income and stimulating rest of the economic sectors, the potentials and qualifications possessed by Iraq in the field of tourism and monuments have a significant impact on the state budget if they were exploited optimally. The research aims at identifying the contr

Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.

 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

The denoising of a natural image corrupted by Gaussian noise is a problem in signal or image processing.  Much work has been done in the field of wavelet thresholding but most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds.  This paper describes a new method for the suppression of noise in image by fusing the stationary wavelet denoising technique with adaptive wiener filter. The wiener filter is applied to the reconstructed image for the approximation coefficients only, while the thresholding technique is applied to the details coefficients of the transform, then get the final denoised image is obtained by combining the two results. The proposed method was applied by usin

The increased size of grayscale images or upscale plays a central role in various fields such as medicine, satellite imagery, and photography. This paper presents a technique for improving upscaling gray images using a new mixing wavelet generation by tensor product. The proposed technique employs a multi-resolution analysis provided by a new mixing wavelet transform algorithm to decompose the input image into different frequency components. After processing, the low-resolution input image is effectively transformed into a higher-resolution representation by adding a zeroes matrix. Discrete wavelets transform (Daubechies wavelet Haar) as a 2D matrix is used but is mixed using tensor product with another wavelet matrix’s size. MATLAB R2021