Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp

In this paper, a simple fast lossless image compression method is introduced for compressing medical images, it is based on integrates multiresolution coding along with polynomial approximation of linear based to decompose image signal followed by efficient coding. The test results indicate that the suggested method can lead to promising performance due to flexibility in overcoming the limitations or restrictions of the model order length and extra overhead information required compared to traditional predictive coding techniques.

Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

Breast cancer was one of the most common reasons for death among the women in the world. Limited awareness of the seriousness of this disease, shortage number of specialists in hospitals and waiting the diagnostic for a long period time that might increase the probability of expansion the injury cases. Consequently, various machine learning techniques have been formulated to decrease the time taken of decision making for diagnoses the breast cancer and that might minimize the mortality rate. The proposed system consists of two phases. Firstly, data pre-processing (data cleaning, selection) of the data mining are used in the breast cancer dataset taken from the University of California, Irvine machine learning repository in this stage we

The present article delves into the examination of groundwater quality, based on WQI, for drinking purposes in Baghdad City. Further, for carrying out the investigation, the data was collected from the Ministry of Water Resources of Baghdad, which represents water samples drawn from 114 wells in Al-Karkh and Al-Rusafa sides of Baghdad city. With the aim of further determining WQI, four water parameters such as (i) pH, (ii) Chloride (Cl), (iii) Sulfate (SO4), and (iv) Total dissolved solids (TDS), were taken into consideration. According to the computed WQI, the distribution of the groundwater samples, with respect to their quality classes such as excellent, good, poor, very poor and unfit for human drinking purpose, was found to be

Twenty four soil samples were collected from different sites in north sector of East Baghdad oil field, Iraq , and analyzed to assess the impact of urbanization and industrialization essential pollution. The soil samples were analyzed for heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) by using inductively coupled plasma–mass spectrometry (ICP-MS). Mean concentration of heavy metals in soil samples follows this pattern: Zn > Ni > Cr > Cu >Pb > As> Cd> Hg. The results show significant variations (lower and higher) in the concentrations of heavy metals compared with local and world studies, this variation is attributed to the natural anthropogenic sources. The pollution of studied soil was assessed using many soil

Recycling process presents a sustainable pavement by using the old materials that could be milled, mixed with virgin materials and recycling agents to produce recycled mixtures. The objective of this study is to evaluate the impact of water on recycled asphalt concrete mixtures, and the effect of the inclusion of old materials into recycled mixtures on the resistance of water damage. A total of 54 Marshall Specimens and 54 compressive strength specimens of (virgin, recycled, and aged asphalt concrete mixtures) had been prepared, and subjected to Tensile Strength Ratio test, and Index of Retained Strength test. Four types of recycling agents (used oil, oil + crumb rubber, soft grade asphalt cement, and asphalt cement + Su

Background: Assessment of function of the right side of the heart in cases of left ventricular dysfunction has been widely studied but the sensitive and specific echocardiographic parameter to be tested is still a matter of controversy. Right ventricular function is related to left ventricular function by ventricular independence so function of both should be assessed carefully. The objective of this study was to evaluate the effects of left ventricular systolic dysfunction on right ventricular systolic and diastolic functions and pulmonary pressure using conventional and tissue Doppler echocardiography. Patients and Methods: Sixty patients (39 males and 21 females) with heart failure due to left ventricular systolic dysfunction

Polycystic ovary syndrome (PCOS) is a mainly common endocrine disorder. Hyperandrogenism is the major standard in the diagnosisof PCOS development.Eighty women diagnosed with PCOS and twenty healthy women(aged 20-40 years)were enrolled in this study which was conducted at the infertility clinic of Kamal AL-Samaraay Hospital/ Baghdad. The diagnosis of PCOS was made according to the Rotterdam criteria. Body mass index (BMI, Kg/m²)was calculated by a specific formula. History of menstrual irregularity, hirsutism, acne, and alopecia was taken. Hormone levels in serum, namely luteinizing hormone (LH), follicle stimulating hormone (FSH), and testosterone were measured in all patients and control subjects.There was a statistically si

Autonomous motion planning is important area of robotics research. This type of planning relieves human operator from tedious job of motion planning. This reduces the possibility of human error and increase efficiency of whole process.

This research presents a new algorithm to plan path for autonomous mobile robot based on image processing techniques by using wireless camera that provides the desired image for the unknown environment . The proposed algorithm is applied on this image to obtain a optimal path for the robot. It is based on the observation and analysis of the obstacles that lying in the straight path between the start and the goal point by detecting these obstacles, analyzing and studying their shapes, positions and