Recently, Image enhancement techniques can be represented as one of the most significant topics in the field of digital image processing. The basic problem in the enhancement method is how to remove noise or improve digital image details. In the current research a method for digital image de-noising and its detail sharpening/highlighted was proposed. The proposed approach uses fuzzy logic technique to process each pixel inside entire image, and then take the decision if it is noisy or need more processing for highlighting. This issue is performed by examining the degree of association with neighboring elements based on fuzzy algorithm. The proposed de-noising approach was evaluated by some standard images after corrupting them with impulse

In the current digitalized world, cloud computing becomes a feasible solution for the virtualization of cloud computing resources.  Though cloud computing has many advantages to outsourcing an organization’s information, but the strong security is the main aspect of cloud computing. Identity authentication theft becomes a vital part of the protection of cloud computing data. In this process, the intruders violate the security protocols and perform attacks on the organizations or user’s data. The situation of cloud data disclosure leads to the cloud user feeling insecure while using the cloud platform. The different traditional cryptographic techniques are not able to stop such kinds of attacks. BB84 protocol is the first quantum cry

Features is the description of the image contents which could be corner, blob or edge. Corners are one of the most important feature to describe image, therefore there are many algorithms to detect corners such as Harris, FAST, SUSAN, etc. Harris is a method for corner detection and it is an efficient and accurate feature detection method. Harris corner detection is rotation invariant but it isn’t scale invariant. This paper presents an efficient harris corner detector invariant to scale, this improvement done by using gaussian function with different scales. The experimental results illustrate that it is very useful to use Gaussian linear equation to deal with harris weakness.

This research aims to clarify the advantages of using the regression method as analytical procedure in the tax audit to reducing the examination cost , time, effort, human and material resources, and represents an applied study in the General Commission of taxes. In order to achieve its objectives the research has used in the theoretical side the descriptive approach (analytical), and in the practical side regression method has been applied to the research sample represented by the soft drinks company that is subject to the tax settlement for the year 2014, where the value of sales has been verified by using the regression method without conductinga comprehensive examination. The most important results of the research indicate that the r

In this research two algorithms are applied, the first is Fuzzy C Means (FCM) algorithm and the second is hard K means (HKM) algorithm to know which of them is better than the others these two algorithms are applied on a set of data collected  from the Ministry of Planning on the water turbidity of five areas in Baghdad to know which of these areas are less turbid in clear water to see which months during the year are less turbid in clear water in the specified area.

The objective of this study was to develop neural network algorithm, (Multilayer Perceptron), based correlations for the prediction overall volumetric mass-transfer coefficient (k_La), in slurry bubble column for gas-liquid-solid systems. The Multilayer Perceptron is a novel technique based on the feature generation approach using back propagation neural network. Measurements of overall volumetric mass transfer coefficient were made with the air - Water, air - Glycerin and air - Alcohol systems as the liquid phase in bubble column of 0.15 m diameter. For operation with gas velocity in the range 0-20 cm/sec, the overall volumetric mass transfer coefficient was found to decrease w

This study was conducted to assess the hydrocarbon degradation abilities of Sphingomonas paucimobilis, Pentoae species, Staphylococcus aureus, and Enterobacter cloacae, which isolated from diesel contaminated soil samples. Single strains and mixed bacterial consortia have been investigated their ability to degrade 1.0 % (v/v) of diesel oil in Bushnell- Haas medium as sole.carbon.and.energy.source. At temperature 30^∘C, the individual.bacterial.isolates exhibited low growth and low degradation.than did the.mixed. bacterial.culture. After 28 days.of incubation the.combination.of four isolates degraded.an upper limit.of diesel  88.4%. This was. continued.by 85.1% by S. paucimobilis, 84 % by Pentoae sp., 79% by S.aureus, and

The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

The apricot plant was washed, dried, and powdered after harvesting to produce a fine powder that was used in water treatment. created an alcoholic extract from the apricot plant using ethanol, which was then analysed using GC-MS, Fourier transform infrared spectroscopy, and ultraviolet-visible spectroscopy to identify the active components. Zinc nanoparticles were created using an alcoholic extract. FTIR, UV-Vis, SEM, EDX, and TEM are used to characterize zinc nanoparticles. Using a continuous processing procedure, zinc nanoparticles with apricot extract and powder were employed to clean polluted water. Firstly, 2 g of zinc nanoparticles were used with 20 ml of polluted water, and the results were Tetra 44% and Levo 32%; after

Manganese sulfate and Punica granatum plant extract were used to create MnO₂ nanoparticles, which were then characterized using techniques like Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, atomic force microscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The crystal's size was calculated to be 30.94nm by employing the Debye Scherrer equation in X-ray diffraction. MnO₂ NPs were shown to be effective in adsorbing M(II) = Co, Ni, and Cu ions, proving that all three metal ions may be removed from water in one go. Ni(II) has a higher adsorption rate throughout the board. Co, Ni, and Cu ion removal efficiencie