One of the biomedical image problems is the appearance of the bubbles in the slide that could occur when air passes through the slide during the preparation process. These bubbles may complicate the process of analysing the histopathological images. The objective of this study is to remove the bubble noise from the histopathology images, and then predict the tissues that underlie it using the fuzzy controller in cases of remote pathological diagnosis. Fuzzy logic uses the linguistic definition to recognize the relationship between the input and the activity, rather than using difficult numerical equation. Mainly there are five parts, starting with accepting the image, passing through removing the bubbles, and ending with predict the tissues

The process of digital transformation is considered one of the most influential matters in circulation at the present time, as it seeks to integrate computer-based technologies into the public services provided by companies or institutions. To achieve digital transformation, basics and points must be established, while relying on a set of employee skills and involving customers in developing this process. Today, all governments are seeking electronic transformation by converting all public services into digital, where changes in cybersecurity must be taken into account, which constitutes a large part of the priorities of nations and companies. The vulnerability to cyberspace, the development of technologies and devices, and the use

Unconfined Compressive Strength is considered the most important parameter of rock strength properties affecting the rock failure criteria.  Various research have developed rock strength for specific lithology to estimate high-accuracy value without a core.  Previous analyses did not account for the formation's numerous lithologies and interbedded layers. The main aim of the present study is to select the suitable correlation to predict the UCS for hole depth of formation without separating the lithology. Furthermore, the second aim is to detect an adequate input parameter among set wireline to determine the UCS by using data of three wells along ten formations (Tanuma, Khasib, Mishrif, Rumaila, Ahmady, Maudud, Nahr Um

Background. Nanocoating of biomedical materials may be considered the most essential developing field recently, primarily directed at improving their tribological behaviors that enhance their performance and durability. In orthodontics, as in many medical fields, friction reduction (by nanocoatings) among different orthodontic components is considered a substantial milestone in the development of biomedical technology that reduces orthodontic treatment time. The objective of the current research was to explore the tribological behavior, namely, friction of nanocoated thin layer by tantalum (Ta), niobium (Nb), and vanadium (V) manufactured using plasma sputtering at 1, 2, and 3 hours on substrates made of 316L stainless steel (SS),

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

The present work aimed to study effect of (N749 & N3) dyes on TiO2 optical and electrical properties for optoelectronic application. The TiO2 paste prepared by using a doctor blade method. The samples were UV-VIS specterophometricall analyzes of TiO2 before and after immersed in dyes (N749 & N3). The results showed absorption spectra shift toward the visible region due to the adsorption of dye molecules on the surface of oxide nanoparticles. It is seen that the Eg determined to give a value of 3.3eV for TiO2 before immersing in dyes, and immersing in dyes (N749 & N3) are (1.4 &1.6 eV) respectively. The structural properties (XRD), (FTIR) and (SEM) for the sample prepared were investigated and (J-V) characteristics was stu

Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit

Ultraviolet photodetectors have been widely utilized in several applications, such as advanced communication, ozone sensing, air purification, flame detection, etc. Gallium nitride and its compound semiconductors have been promising candidates in photodetection applications. Unlike polar gallium nitride-based optoelectronics, non-polar gallium nitride-based optoelectronics have gained huge attention due to the piezoelectric and spontaneous polarization effect–induced quantum confined-stark effect being eliminated. In turn, non-polar gallium nitride-based photodetectors portray higher efficiency and faster response compared to the polar growth direction. To date, however, a systematic literature review of non-polar gallium nitride-