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When laser light incident on biological tissue, it is either reflected from the
surface of the tissue (e.g. the skin) or scattered inside the tissue or absorbed .The laser light will be
absorbed by water, hemoglobin and melanin. Absorption is also highly dependent on wave-length of
laser radiation. The absorbed light is converted into kinetic energy leading to laser effect that when
appropriately applied can produce reaction ranging from incision, vaporization to coagulation. Aim of
the study: To evaluate the efficiency of diode Laser 810 ± 20nm in treatment of oral lesions. Methods:
6 patients (2 females and 4 males) with different oral lesions were treated in the hospital of specialized
surgeries by the use of dio

Soil stabilization with stone powder is a good solution for the construction of subgrade for road way and railway lines, especially under the platforms and mostly in transition zones between embankments and rigid structures, where the mechanical properties of supporting soils are very influential. Stone powder often has a unique composition which justifies the need for research to study the feasibility of using this stone powder type for ground improvement applications. This paper presents results from a comprehensive laboratory study carried out to investigate the feasibility of using stone powder for improvement of engineering properties of clays.

The stone powder contains bassanite (CaSO₄. ½ H

With the increasing rate of unauthorized access and attacks, security of confidential data is of utmost importance. While Cryptography only encrypts the data, but as the communication takes place in presence of third parties, so the encrypted text can be decrypted and can easily be destroyed. Steganography, on the other hand, hides the confidential data in some cover source such that the existence of the data is also hidden which do not arouse suspicion regarding the communication taking place between two parties. This paper presents to provide the transfer of secret data embedded into master file (cover-image) to obtain new image (stego-image), which is practically indistinguishable from the original image, so that other than the indeed us

Large quantities of contaminated carwash wastewater are produced per day from carwash places. Extensively it contains large quantities of chemicals from detergents, oil, grease, heavy metals, suspended solids, types of hydrocarbons, and biological contents. A novel electrocoagulation treatment by foil electrodes was conducted to remove COD, turbidity, Total Dissolved Solids (TDS) from contaminated carwash wastewater and decrease its Electrical Conductivity (EC). A thin layer of aluminum foil is used as an electrode in this treatment process. The effects of different voltage and treatment times were studied. The best result was found at a voltage of 30 volts and treatment time 90 minute where the removal efficiency of COD

Copper nanoparticles (CuNPs) were prepared with different diameters by sonoelectrodeposition technique using Electrodeposition process coupled with high-power ultrasound horn (Sonoelectrodeposition). The particle diameter of the CuNPs was adjusted by varying CuSO4 solution acidity (pH) and current density. The morphology and structure of the CuNPs were examined by X-ray diffraction (XRD) and Scanning Electron Microscopy (SEM). It was found that the size of the produced copper nanoparticles ranged between 22 to 77 nm, where the diameter of CuNPs increases with reduction the solution acidity from 0.5 to 1.5 pH and increasing the current density of the deposition from 100 to 400 nm. Finally the produced CuNPs were pressed to fabricate disc

In this paper the behavior of the quality of the gradient that implemented on an image as a function of noise error is presented. The cross correlation coefficient (ccc) between the derivative of the original image before and after introducing noise error shows dramatic decline compared with the corresponding images before taking derivatives. Mathematical equations have been constructed to control the relation between (ccc) and the noise parameter.

Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w