This research paper studies the use of an environmentally and not expensive method to degrade Orange G dye (OG) from the aqueous solution, where the extract of ficus leaves has been used to fabricate the green bimetallic iron/copper nanoparticles (G-Fe/Cu-NPs). The fabricated G‑Fe/Cu-NPs were characterized utilizing scanning electron microscopy, BET, atomic force microscopy, energy dispersive spectroscopy, Fourier-transform infrared spectroscopy and zeta potential. The rounded and shaped as like spherical nanoparticles were found for G-Fe/Cu‑NPs with the size ranged 32-59 nm and the surface area was 4.452 m²/g. Then the resultant nanoparticles were utilized as a Fenton-like oxidation catalyst. The degradation efficiency of

The body has the ability to effect the audience in the the theatrical show , since he or she is transmitter , sender , seen and viewer of the humanitarian discourse as well the the images and connotations of the theatrical show, it is a tool of communication that substitutes for millions of spoken words, the modern schools of direction focused on the body language of the actor and gave it prominence in depicting facts by different connotations. The researcher studies the physical performance of the actor throughout focusing on the connotational dimensions of the body within the theatrical show , as well as the positioning of performative body within the modern schools of direction depending on the theatrical show (Rebuke ) of the Iraqi d

Preparation of identical independent photons is the core of many quantum applications such as entanglement swapping and entangling process. In this work, Hong-Ou-Mandel experiment was performed to evaluate the degree of indistinguishability between independent photons generated from two independent weak coherent sources working at 640 nm. The visibility was 46%, close to the theoretical limit of 50%. The implemented setup can be adopted in quantum key distribution experiments carried out with free space as the channel link, as all the devices and components used are operative in the visible range of the electromagnetic spectrum.

ترك السلطان عبدالحميد الثاني بصماتهُ على أخاديد الزمان وعلى خارطة المشرق العربي الخاضع للسيطرة العثمانية أنذاك ، لكونهُ أهم شخصية أسلامية غير عربية واجهت الخطر الصهيوني ومحاولاتهم الإستيطانية في مشرق الوطن العربي ، على الرغم من صعوبة الظروف التي كانت تمر بها الدولة العثمانية داخليا ً وخارجيا ً، بما فيها من أطماع اقتسامها بين الاوربين ولذا سموها بالرجل المريض .

تُعد دراسة أعلام الفكر العربي والإسلامي من أهم الدراسات التاريخية ولا يمكن للأمم المتحضرة أن تنسى علمائها ومفكريها لما لهم من دور كبير في حاضر الأمة ومستقبلها و تاريخنا الإسلامي يحفل بالعديد من العلماء ورجال المعرفة  الذين ساعدوا على تقدم ورقي العرب والمسلمين على الأمم الأخرى0

Polymer composites were prepared using epoxy resin (EP) and unsaturated polyester (UPE) as a blend matrices, which were mixed together in different percentages (starting from 90:10) of (epoxy/polyester) respectively, and ending with (50:50) of (epoxy/polyester). The optimum mixing ratio (OMR) of the components was decided upon the results of the impact strength value of these blending ratio, which showed the highest value of (16.3) KJ/m2 for the blending ratio (80:20) of (EP/UPE) respectively.
The blend with (OMR) was chosen to be reinforced with three different weight fractions of reinforcement; the 1st one was reinforced with nano titanium oxide (TiO2) with a weight fraction (2% wt.), the 2nd one was reinforced with both nano (TiO2)

Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed.  A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing

     This article reviews a decade of research in transforming smartphones into smart measurement tools for science and engineering laboratories. High-precision sensors have been effectively utilized with specific mobile applications to measure physical parameters. Linear, rotational, and vibrational motions can be tracked and studied using built-in accelerometers, magnetometers, gyroscopes, proximity sensors, or ambient light sensors, depending on each experiment design. Water and sound waves were respectively captured for analysis by smartphone cameras and microphones. Various optics experiments were successfully demonstrated by replacing traditional lux meters with built-in ambient light sensors. These smartphone-based measurement

     Due to the spread of “Deepfake” in our society and the impact of this phenomenon on politicians, celebrities, and the privacy of individuals in particular, as well as, on the other hand, its impact on the electoral process as well as financial fraud, all these reasons prompted us to present a research paper dealing with this phenomenon. This paper presents a comprehensive review of Deepfake, how it is created, and who has produced it. This paper can be used as a reference and information source for the methods used to limit deepfake by detecting forgeries and minimizing its impact on society by preventing it. This paper reviews the results of much research in the field of deepfake, as well as the advantages of each method, a

Image classification can be defined as one of the most important tasks in the area of machine learning. Recently, deep neural networks, especially deep convolution networks, have participated greatly in end-to-end learning which reduce need for human designed features in the image recognition like Convolution Neural Network. It is offers the computation models which are made up of several processing layers for learning data representations with several abstraction levels. In this work, a pre-trained deep CNN is utilized according to some parameters like filter size, no of convolution, pooling, fully connected and type of activation function which includes 300 images for training and predict 100 image gender using probability measures. Re