In this research, an enhancement in lubricating, rheological, and filtration properties of unweighted water-based mud is fundamentally investigated using XC polymer NPs with 0.2gm, 0.5gm, 1gm, 2gm, and 4gm concentrations. Bentonite, that had been used in the preparation of unweighted water-based mud, was characterized using XRF-1800 Sequential X-ray Fluorescence Spectrometer, XRD-6100/7000 X-ray Diffractometer, and Malvern Mastersizer 2000 particle size analyzer, respectively. Lubricating, rheology and filtration properties of unweighted water-based mud were measured at room temperature (35°C) using OFITE EP and Lubricity Tester, OFITE Model 900 Viscometer, and OFITE Low-Pressure Filter Press, respectively. XC Polymer N

Enhancing asphalt binder performance against anticipated distresses is a critical focus in pavement engineering. This study investigates the synergistic influence of nano titanium dioxide (NT) and nano zinc oxide (NZ) on asphalt binder performance. Nine NT:NZ combinations (1:1 to 3:3) were prepared with 1–3% by binder weight, in addition to a reference binder (RB). The performance test program included; conventional tests (penetration, softening point, viscosity, and ductility), Dynamic Shear Rheometer (DSR) for performance grading, Multiple Stress Creep Recovery (MSCR) for rutting evaluation, and Linear Amplitude Sweep (LAS) for fatigue resistance. Furthermore, Statistical analysis (ANOVA) was performed to determine the significa

Wars represent one of the most serious threats to the world order; It is considered a violation of international laws and norms, and humanitarian principles. From this point comes the study of the importance of the topic entitled (The Future of the Russian-Ukrainian war and the extent of its Reflection on the security of Eastern European countries after the year 2022). This study is based on reviewing future possibilities (scenarios) of war. The Russian-Ukrainian war, which was launched by the Russian government led by Russian President Vladimir Putin in February 2022, is still ongoing at the time of writing this research. This chapter includes three possibilities (scenarios). The first possibility deals with the development of the war t

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.

In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.

In this paper, a fast lossless image compression method is introduced for compressing medical images, it is based on splitting the image blocks according to its nature along with using the polynomial approximation to decompose image signal followed by applying run length coding on the residue part of the image, which represents the error caused by applying polynomial approximation. Then, Huffman coding is applied as a last stage to encode the polynomial coefficients and run length coding. The test results indicate that the suggested method can lead to promising performance.

This research worked on identifying the effect of increasing the volume of indebtedness by companies listed on the Iraq Stock Exchange on the trading volume of those companies, and this research included some theoretical concepts related to both debt financing and trading volume, and it represents the research community of the joint-stock companies listed in The Iraq Stock Exchange (the banking sector). As for the research sample, it was deliberately chosen represented by companies with continuous trading without stopping, which reached 10 joint-stock companies, and the period of research was extended during the period 2011-2015, and a set of indicators and financial methods were used In measuring research v

Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt