The main reason for the emergence of a deepfake (deep learning and fake) term is the evolution in artificial intelligence techniques, especially deep learning. Deep learning algorithms, which auto-solve problems when giving large sets of data, are used to swap faces in digital media to create fake media with a realistic appearance. To increase the accuracy of distinguishing a real video from fake one, a new model has been developed based on deep learning and noise residuals. By using Steganalysis Rich Model (SRM) filters, we can gather a low-level noise map that is used as input to a light Convolution neural network (CNN) to classify a real face from fake one. The results of our work show that the training accuracy of the CNN model

Genome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id

The aim of the research is to examine the multiple intelligence test item selection based on Howard Gardner's MI model using the Generalized Partial Estimation Form, generalized intelligence. The researcher adopted the scale of multiple intelligences by Kardner, it consists of (102) items with eight sub-scales. The sample consisted of (550) students from Baghdad universities, Technology University, al-Mustansiriyah university, and Iraqi University for the academic year (2019/2020). It was verified assumptions theory response to a single (one-dimensional, local autonomy, the curve of individual characteristics, speed factor and application), and analysis of the data according to specimen partial appreciation of the generalized, and limits

Globally, buildings use about 40% of energy. Many elements, such as the physical properties of the structure, the efficiency of the cooling and heating systems, the activity of the occupants, and the building’s sustainability, affect the energy consumption of a building. It is really difficult to predict how much energy a building will need. To improve the building’s sustainability and create sustainable energy sources to reduce carbon dioxide emissions from fossil fuel combustion, estimating the building's energy use is necessary. This paper explains the energy consumed in the lecture building of the Al-Khwarizmi College of Engineering, University of Baghdad (UOB), Baghdad, Iraq. The weather data and the building construction informati

Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty

Abstract
The use of electronic valves is commonly available. yet, the most
common is the techniques of communications as prod casting transmitter that
are used by these valves in addition to their use in communication tools as far
distance telephone, electronic measuring techniques , and others.
In this study, an attempt is endeavored for improving the efficiency of the
vacuum micro- valves(GI-19b) through activating their internal surfaces by the
use of ionic pumping which is used for treating valves which are out of order
(because of sedimentation some materials and oxide on its poles). The
existence of these materials and oxide increase the sum of current leakage
moving in between. The use of ionic pumpin

In this study, active knife and fixed knife of single-row disc silage machine has three different clearance C1, C2 and C3 (1, 3 and 5 mm) and it is tried in three different working speed V1, V2 and V3 (1.8, 2.5 and 3.7 km / h) and PTO speed (540 min-1) and machine's fuel consumption (l/h), average power consumption (kW), field energy consumption (kW/da), product energy consumption (kW/t), field working capacity (da/h), product working capacity (t/h) and Chopping size distribution characteristics of the fragmented material were determined. It has been found that knife-counter knife clearances smaller than 3 mm (1 mm) and larger (5 mm) have a negative effect on machine performance in general. In terms of fuel and power consumptions, the m

In this study, the harvest of maize silage with the cross double row sowing method were tested with a single row disc silage machine in two different PTO applications (540 and 540E min-1) and at two different working speeds v1, v2 (1.8 and 2.5 km h-1). The possibilities of harvesting with a single row machine were revealed, and performance characteristics such as hourly fuel consumption, field-product fuel consumption and PTO power consumption were determined in the trials. The best results in terms of hourly fuel consumption and PTO power consumption were determined in the 540E PTO application and V1 working speed. When the fuel consumption of the field-product is evaluated, it is obtained with V2 working speed and 540E PTO application. As

 The research has been based on two main variables (information and communication technology) and the quality of blended education (physical and electronic), aiming to reveal the relationship between four dimensions (physical devices, software, databases, communication networks) and the elements of education represented by (the teacher, the student, the teaching process, curriculum).  The methodology and post-analysis-based research were conducted at the Technical College of Management / Baghdad through polling the opinions of a random sample that included (80) teachers out of (86) and the number of students (276) representing a random sample from all departments of the college (for the morning study) out of (3500) stud

Ferritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things. , We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper we introduce a semi- parametric method for prediction by making a combination between NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in design the model; the data were collected from مستشفى دار التمريض الخاص for period 11/7/2021- 23/7/2021, we have 100 person, With COVID 12 Female & 38 Male out of 50, while 26 Female & 24 Male non COVID out of 50. The input variables of the NN m