Fractal image compression depends on representing an image using affine transformations. The main concern for researches in the discipline of fractal image compression (FIC) algorithm is to decrease encoding time needed to compress image data. The basic technique is that each portion of the image is similar to other portions of the same image. In this process, there are many models that were developed. The presence of fractals was initially noticed and handled using Iterated Function System (IFS); that is used for encoding images. In this paper, a review of fractal image compression is discussed with its variants along with other techniques. A summarized review of contributions is achieved to determine the fulfillment of fractal ima

In this paper, we will present proposed enhance process of image compression by using RLE algorithm. This proposed yield to decrease the size of compressing image, but the original method used primarily for compressing a binary images [1].Which will yield increasing the size of an original image mostly when used for color images. The test of an enhanced algorithm is performed on sample consists of ten BMP 24-bit true color images, building an application by using visual basic 6.0 to show the size after and before compression process and computing the compression ratio for RLE and for the enhanced RLE algorithm.

A time series analysis can help to observe the behavior of the system and specify the system faults. In addition, it also helps to explain the various energy flows in the system and further aid in reducing the thermodynamic losses. The intelligent supervisory LabVIEW software can monitor the incoming data from the system by using Arduino microcontroller and calculates the important parameters. Energy, exergy, and anergy analysis present in this paper to investigate the system performance as well as its components. To accomplish this, a 4-ton vertical split air conditioner based on vapor compression refrigeration cycle charged with refrigerant R-22 was modified for experimental analysis. The results showed that during 540

The current study suggested a thermal treatment as a necessary proactive step in improving the adsorption capacity of bio-waste for contaminants removal in wastewater. This approach was based on the experimental and histological investigation of biowaste pods shell. This investigation showed that these shells compose of parenchyma cells that store secondary metabolites compounds produced from cells were exhibited in present study. The results also reported that these compounds are extracted directly from the cells as soon as they are exposed to an aqueous solution, hampering their use as an adsorbent material. The increase in the weight of bio-waste adsorbent at unit liquid volume increases the production of secondary metabolites compounds

Through an experimental program of eighteen specimens presented in this paper, the bond strength between reinforcing bar and rubberized concrete was produced by adding waste tire rubber instead of natural aggregate. The fine and coarse aggregate was replaced in 0%, 25%, and 50% with the small pieces of a waste tire. Natural aggregate replacement ratio, rebar size, embedded rebar length, the rebar yield stress of rebar, cover, and concrete compressive strength were studied in this investigation. Ultimate bond stress, bond stress-slip response, and failure modes were presented. The experimental results reported that a reduction of 19% in bond strength was noticed in 50% replaced rubberized concrete compared with convention

As human societies grow, the problem of waste management becomes one of the pressing issues that need to be addressed. Recycling and reuse of waste are effective waste management measures that prevent pollution and conserve natural resources. In this study, the possibility of using glass waste as an alternative was used as a partial weight substitute for fine aggregates with replacement ratios of 10, 20, 30, and 40% by the weight, and formed into test models (15 cm * 15 cm ) cube and (15 cm * 30 cm) cylinder, then matured and tested their strength compression and tensile strength at the age of 7 and 28 days and compared with a reference or conventional concrete with a mixing ratio (1: 1.5: 3) as well as testing its worka

Productivity estimating of ready mixed concrete batch plant is an essential tool for the successful completion of the construction process. It is defined as the output of the system per unit of time. Usually, the actual productivity values of construction equipment in the site are not consistent with the nominal ones. Therefore, it is necessary to make a comprehensive evaluation of the nominal productivity of equipment concerning the effected factors and then re-evaluate them according to the actual values.

In this paper, the forecasting system was employed is an Artificial Intelligence technique (AI). It is represented by Artificial Neural Network (ANN) to establish the predicted model to estimate wet ready mixe

Reinforcing asphalt concrete with polyester fibers considered as an active remedy to alleviate the harmful impact of fatigue deterioration. This study covers the investigation of utilizing two shapes of fibers size, 6.35 mm by 3.00 mm and 12.70 mm by 3.00 mm with mutual concentrations equal to 0.25 %, 0.50 % and 0.75 % by weight of mixture. Composition of asphalt mixture consists of different optimum (40-50) asphalt cement content, 12.50 mm nominal aggregate maximum size with limestone dust as a filler. Following the traditional asphalt cement and aggregate tests, three essential test were carried out on mixtures, namely: Marshall test (105 cylindrical specimens), indirect tensile strength test (21 cylindrical specimens)

Rutting is a crucial concern impacting asphalt concrete pavements’ stability and long-term performance, negatively affecting vehicle drivers’ comfort and safety. This research aims to evaluate the permanent deformation of pavement under different traffic and environmental conditions using an Artificial Neural Network (ANN) prediction model. The model was built based on the outcomes of an experimental uniaxial repeated loading test of 306 cylindrical specimens. Twelve independent variables representing the materials’ properties, mix design parameters, loading settings, and environmental conditions were implemented in the model, resulting in a total of 3214 data points. The network accomplished high prediction accuracy with an R