Al-Salam Journal for Engineering and Technology

Fake face images is a recent critical issue of artificial intelligent due to it has directly impacts on the
social lives, and may be made to imply threats against privacy, fraud, and other issues. Currently, creating fake
images has become relatively simple due to the powerful yet user-friendly mobile applications that navigate in the
social media world and with the invention of the Generative Adversarial Network (GAN) that provides a good
quality images that might be difficult for humans to differentiate with their eyes and makes image and video
manipulation simple to do, quickly spread and hard to detect, Therefor, image processing and artificial intelligence
are crucial in solving such problems. That is why scientists must create technologies or algorithms to control and to
avoid these various negative impacts by different detection approaches can be applied. The proposed approach is
more robust than current methods when propose a model based on support vector machine as a classifiers to detect
fake human faces created by machines. The first stages includes a preprocessing that start with changing images
from RGB to YCbCr and then applying the gamma correction. finalize the results show that the extracted edges
using Canny filter were useful for detecting fakes in face images. After that, applying two distinct methods of
detection by utilizing \\"Support Vector Machine\\" with \\"Principal Component Analysis\\" and \\"Support Vector
Machine\\" without \\"Principal Component Analysis\\" as a classifiers. The findings show that the highest accuracy
gained is 96.8% when using the SVM with PCA while the accuracy obtained is 72.2% when using the SVM alone.

As the complexity of logic devices increased, it required more time and effort to manually design
and verify tests, it was difficult to estimate test coverage, and the tests ran too slowly. This method is known as
functional testing. Therefore, the industry adopted a design for test (DFT) strategy in which the design was updated
to make testing simpler. In this work, a full scan testability method is going to be implemented to a sequential
circuit (CUT). The CUT consists of at 6 D flip-flops and 10 logic gates. This CUT was designed using quartus
prime software. The following steps are going to be implemented in this work: First, simulate the fault free circuit.
Second, three faults were injected and tested to check if they can be detected or not. Finally, analyze the obtained
results in terms of (what is the test pattern needed, how the fault can be observed at output).

One of the most crucial aspects of dam construction is stability under a seismic load. The breakdown
of the dam could cause a catastrophic effect on downstream areas. For that, the safety of the facilities lies in their
stability. Dams must be stable and withstand the loads placed on them. They are national security facilities. Because
dam collapse causes unbridled humanitarian, economic, and social disasters, its construction must be scrutinized and
strive to reach the best design with the best materials. The researchers sought to conduct several studies to know the
dam’s behaviour during earthquakes, the role of their geometric dimensions, and the technical condition of the soil
on which the dam was founded or formed. The current study provide review on seismic analysis research. The
simulation and the results indicated that the soil liquefaction state should be reduced, and the three-dimensional
results should be analyzed to predict the locations and forms of deformations and the ability to deal with them.

This article is about the symmetrical reflections of profit and loss functions and the functions
obtained from them, which are widely used in applications economicy, business applications and other financial
applications of mathematics. The study is seen that the applications in the literature are calculated according to the
profit and loss accounts alone. Since the occurrence of loss in an economicy activity negatively affects the result of
the profit, as a result of the loss, economicy activity bankruptcy, decisions are finalized. This has irreversible
consequences. The controllability of these two interactive events poses reassuring risks. In short, This situation
enables the manageability of the activity. Applications in life take place on a more real axis. Ensuring the control
of the event and seeing the whole event gives the opportunity to intervene in the activity in a short time. Therefore,
the activity started with linear functions in the plane. Evaluations are made on the graphics here. The system
concepts existing in Mathematical Science, their results in applications, especially in economic activities in the
market are examined and their symmetrical reflections with respect to each other are examined. Starting from the
reflections of the known profit and loss functions, their interactions with each other are investigated. How the
break-even point is reflected according to these reflections, and therefore what they did is examined. The reflection
of profit and loss functions according to another function is discussed. This makes it necessary for the control,
planning and implementation of the situations observed in an economic activity, which are known in market
economies. Therefore, the change in price is important in an economic activity. To determine the timing of the
advertisements and to know their reflection is important for the plan of decreasing or increasing the price. The loss
curve is negatively sloping due to price, reflecting new information on the condition of its slope. The reflections of
the determining factors is emphasized very vary in marketing. Differences according to variables affect the
management of this activity. Reflections determine results. The prices of the products directly concern both the
producer and the consumer in an economic activity.

A blockchain (BC) is merely a decentralized ledger that records each transaction that takes place
inside the network. A block is a unit of data that contains encrypted information about every transaction in the
network's history. Decentralized technology implementation would necessitate increased security, enforce
accountability, and may speed up the transaction from the current hierarchical structure to a decentralized,
cooperative chain of command. By producing fresh offspring of those animals who are identifiable by their
identification tags, a blockchain is used to conserve the data of a special species of endangered animals. This
article presents a decentralized application (SONR DAPPs) by implemented genetic algorithm to forecast a brandnew kind of those animals. The implementation did by solidity framework. Even that the solidity has
disadvantages of memory limitation, but the result shows a possibility of using it to implement complex algorithms
for the smart contract. This experience gives a chance to develop the solidity for a more complex algorithm to
increase the ability o-f choosing better user to be a new block in the chain of this technology.

Region of interest in the world of medical images, there is a region in each image that contains
unique features that distinguish each image from the other or distinguish one group of the image from another
group. This paper proposes a new method for extracting the region of interest for DEXA images via the K-means
and edge detection. firstly, the noise is reduced by the mean filter then segment the image into two clusters by kmeans, followed by edge detection to identify object boundaries and erosion operation to clarify boundaries and get
the correct coordinates of ROI. The results show that the accuracy of the proposed system is 99%. where 174
images cropped correctly out of 176. the dataset used in this work is 'Osteoporosis DEXA Scans Images of Spine
from Pakistan'.

Nowadays, the realm of civil engineering has expanded to encompass Internet of Things (IoT)
technologies, which can contribute to making sustainable, high-performing, and durable buildings. These
innovative techniques allow for monitoring concrete structures and developing inspection and maintenance plans to
ensure their long-term integrity. By leveraging the power of IoT technologies in civil engineering, we can improve
the efficiency and effectiveness of building maintenance, reduce costs, and optimize the use of resources, all while
promoting sustainability and longevity in the built environment. In this article, a technical review will be made of
RFID technology's significance in civil engineering. RFID technology is utilized in inspecting building materials,
especially in reinforced concrete, monitoring cavities in riverbeds, monitoring stress in reinforced concrete
structures, monitoring corrosion of reinforced concrete reinforcements, monitoring excavations at a construction
site and many others. This article concluded that RFID technology has significant benefits in the field of civil
engineering, and using the Internet of Things, it greatly impacts following up on building structures and conducting
inspections and immediate maintenance of them.

Various Cryptography algorithms are used to keep the transmission of data safe from intruder and to
secure the connection between sender and receiver. This article provides an overview of ECC, including the
algorithm process, fundamental protocols, and different ECC systems and applications. EC over fields also represents
by numerous graphical representations of cryptographic processes. Comparison tables are included that list the ratio
of key size between ECC and RSA (the nearest method to ECC), in factors of overhead, power availability and
required storage, which indicates fast running with less bandwidth in case of elliptic curve method. In the other hand
some previous works related to the topic were compared according to the functions of properties, measurement
methods, and type of the data used, results were collected in traceable manner for the purpose of making it available
to researchers and those interested in ECC.

Image segmentation is an effective computer vision method that expands on the concept of object.
Recognition and brings in a whole new era of image data manipulation. This method offers up so many options and
may be performed in several ways. However, in this paper, threshold and channel image separation were employed
to perform two types of segmentation. Thresholding is a regional segmentation in and of itself. However,
thresholding alone is insufficient to properly segment the image, necessitating the employment of additional image
processing techniques, such as the morphological process, to provide sharper segmentation. Depending on the
color diversity of the image's pixels, different segmentation parameters, such as the thresholding value and
structuring element for the morphological process, are required for image segmentation. Overall, the two images
have been successfully segmented via two distinct methods.

Solar energy is a kind of renewable energy source, power production, and stored in a battery for
energy management systems. Fault identification is the Direct Current (DC) side of a PV (photovoltaic) system,
which is difficult to avoid energy loss in such open-circuit and short-circuit-based renewable energy storage
systems. Maximum power point tracking is the existing photovoltaic fault identification technique and it mainly
improves the maximum Value of Photovoltaic Power at the Output Side. The Proposed Deficiency Identification
Algorithm is used to improve the detection rate of fault occurrence in the PV cell. The Deficiency Identification
Algorithm is implemented to detect the fault in the PV arrays. The open circuit fault and short circuit faults are the
two major faults in the PV arrays. Solar irradiance level and the temperature are the two output characteristics
which decide the output of the panel and also force to employ a battery unit that pedals the PV output and is
particularly significant for improving energy conversion, voltage losses and improve efficiency.

This article examines a flow of a boundary layer as well as a temperature exchange of Maxwellfluid in 2D along an expansion sheet using numerical methods. The impacts of magnetohydrodynamics (MHD)
plus stretch on an inflow are taken into account. Methods in which nanoparticles might damage the environment
are also investigated. we present differential transform method that can be applied to transform nonlinear partial
differential equation into connected ODEs. A boundary layer Equations formula. are resolved numerically utilizing
the Maxwell-nanofluid model. Emerging variables constraint that affects concentration and also on temp profile
alone are studied; they include a magnetic constraint M, stretchy constraint K, Prandtl constraint Pr, Mass transfer
restriction Nb, a convective heat flow constraint Nt, and Lewis No. Le. Interesting graphs of a findings are
displayed. There are also correlations between a flow control factors and coefficient of skin friction, a
dimensionless heat exchange amount, and the concentrate amount.

In this study, two different types of op-amps were designed and tested at a lower voltage. These opamps use less power and can be used at a lower voltage than traditional op-amps, which makes them a good option
for certain applications. The designer predicted that the power output would be high when there is a high voltage
supply, and LT Spice software was used to analyze the design. Today, low-powered operational amplifiers are in
high demand for many applications, such as in medical and communication systems. Some of the reasons why opamps are in high demand are because they are versatile and have a wide range of applications. Additionally, they
are often less expensive than more powerful amplifiers, which makes them a good option for certain applications.
This op-amp has a good phase margin, so it can handle large loads with ease. It was created using a 180-
millisecond process and CMOS technology. A 3-pF compensation capacitor and a 10-pF load capacitor are suitable
for it, as the op-amp has a phase margin of 90.84 degrees.

Employability is one of the strongest driving forces of an individual to strive for personal
development and skills improvement continually. Among the job seekers of the municipality of Tuburan, on the
island of Cebu, Philippines, 20 aspiring individuals were purposively chosen to undergo a training series using
contextualized learning modules designed to respond to the required skills by identified prospective employers
directly. Sets of pre-and post-tests were given before and after the conduct of the sessions to measure the effects of
the designed modules on the job application skills of the respondents. After the training sessions, the respondents
were asked to apply for jobs while being monitored by the team. The results demonstrated that using
contextualized learning modules significantly enhanced respondents' abilities in terms of resume writing, interview
preparation, and technical skills like using Microsoft Office and Google productivity tools, basic computer
operations, and using the internet and managing emails. The researchers advise using the learning modules and
maximizing their adaptability to the starting points of job seekers' knowledge.

This paper submits a new tactic known as the integral Rohit transform (RT) for uncovering the
response of a mechanically persistent oscillator supplied with a ramp signal. It let outs that RT is an operative tool
for uncovering the response of a mechanically persistent oscillator supplied with a ramp signal.

ChatGPT is a state-of-the-art language model developed by OpenAI. It is part of the GPT
(Generative Pre-trained Transformer) series, which are designed to generate human-like language output based on
large amounts of input data. ChatGPT is one of the largest and most advanced language models to date, with 175
billion parameters. The article aims to examine the impact of artificial intelligence tools and techniques on
academic research and their potential implications for academic ethics. In particular, this article will focus on the
practices of ChatGPT in generating scientific research within the context of academic ethics. ChatGPT is a
powerful tool that can generate text in different formats, conduct literature searches, and suggest titles for the
created text. However, using ChatGPT to select topics with a low similarity score in similarity checkers may lead to
ethical violations. This article finds that the use of artificial intelligence applications in academic research may raise
concerns about academic ethics, and the limited availability of technologies that can detect such violations poses a
significant challenge to academic writing.

A parallel processing system's most crucial part is a network interconnection that links its
processors. The hypercube topology has exciting features, making it an excellent option for parallel processing
applications. This paper presents two innovative configurations of interconnection networks based on fractal
Sierpinski and a hypercube. These are the Sierpinski Triangle Topology (STT) and Sierpinski Carpet Topology
(SCT). Compared to a hypercube, the Sierpinski Triangle topology (STT) noticed a significant decrease in the
number of nodes and links as large networks grew. Hence, it considers a great way to reduce costs because it uses
fewer nodes and links. The average distance is also shorter, which is better. Despite it has a smaller bisection width
and a more degree than a hypercube by one. The Sierpinski Carpet Topology (SCT) has the advantage of having a
higher bisection width than a hypercube. That is preferable because it places a lower restriction on the difficulty of
parallel algorithms. In contrast, the drawback of this topology is that it has a diameter and average distance more
than a hypercube.

Blockchain is an innovative type of information technology (IT). It has the potential to revolutionize
various sectors. Since its inception, Blockchain technology(BC) has been a novel technique in IT. Blockchains are
public ledger of chronologically-connected transactions or occurrences. Blocks retain their hash code. Due to
distributed consensus, it records cryptographic transactions in a public ledger. Thus, Blockchain may resist fraud
and hacking, and the secure transmission of information has been provided using these cutting-edge encryption
technologies, contributing to Blockchain's rising popularity and demand. Blockchain employs encryption at
multiple points throughout the process. Blockchain technology resists various harmful attacks and eliminates many
associated dangers, but not all.Distributed consensus, cryptography, and anonymity these mechanisims , in some
cases, which may weaken its resilience to various frauds and maliciousness. This research aims to provide a
comprehensive study of Blockchain technology, its architecture definition, its most important components,
elements, and types, and to clarify the technologies that are considered the basis of its work and integration.
Among these techniques is encryption; then, we discuss the most important encryption algorithms (Aes, Des, and
Bluefish) currently used with Blockchain to solve the security problems they are exposed to and provide full
protection for their data.

Anomalies are instances or collections of data that occur very rarely in a dataset and where features
differ significantly from most of the data. In the age of technology, data is widely used in all sectors. Thus,
anomalies in the data may produce problems if they are not detected. Anomaly detection involves examining
specific data points and detecting rare occurrences that seem suspicious because they are different from the
established pattern of behaviors. In this study, an approach to anomaly detection is built using a machine learning
technique. The clustering distance-based method (k_means) is adopted. First, the anomaly existence is tested using
p_value. After that, the anomaly data is detected using the clustering method. The proposed method was tested
using real data collected from Kaggle. The results show the good performance of the k_means algorithm in the
detection of outlier data.

Big data classification is the study of how to classify large amounts of data, which conventional
data mining methods typically find challenging to handle. The most popular data mining technique is the KNearest Neighbor(KNN) classifier because of its efficiency and simplicity. The sequential KNN classifier can\'t
handle a huge amount of data due to its highly required calculation nature, so it is improved by using a parallel
technique supported by Map Reduce. This model enables us to classify the massive amount of data that exceeds
terabytes. Similar to the original KNN model, this parallel implementation offers the same classification rate but
less time complexity. In this paper, parallel KNN with Map Reduce has been proposed using a Hadoop multi-data
node cluster. First, the dataset split into n blocks, and in each node, the mapper and reducer will be executed. The
mapper phase is responsible for calculating the Euclidean distance between the training set and the targeted point,
and the output of the mapper is a set of pairs of that serve as the reducer\'s input. In reducer, the
minimum k distances are determined, and the class with maximum occurrence will represent the predicted class.
The results showed a significant improvement in time complexity for the proposed approach over the traditional
one. A New York criminal data set with a size of 6.5 million records was used in this work. The tuples Latitude
and Longitude were used to determine the nearest neighbors, while the Patrol-BORO was used as class label.

The first step in any image processing process is to remove noise from an image, and this is the aim
of every de-noising technique. The noise removal technique should be used carefully to avoid introducing artifacts
that could cause the image to become blurry. In this paper, five levels of Gaussian noise and Salat & Peppers are
applied to original images to add noise (σ=5, σ=10, σ=15, σ=20, σ=25 σ=50) and also combination Gaussian and
Salt & peepers are used with noise level 25. Removing noising is filtered in mean filter. Performance evaluation of
the mean filter with three methods of noise is provided. After testing all the approaches with Gaussian noise σ =15,
the results revealed that Lena\'s image was superior to the others. The other photos, however, performed better for
the Gaussian levels 20 and 25 than the Lena image. With all types of noise, the mean filter produced good results.

The phenomenon of climate change resulting from the increase of global warming has become one
of the main problems facing the world. Where researchers and specialists have worked for many years to find a
solution that reduces this phenomenon and limits its risks. Clean energy is likely an alternative to fossil fuel sources,
which are the main source of global warming. One of the clean energy sources is ocean wave energy, which is a huge
and untapped energy source, despite the possibility of extracting large amounts of energy from waves. This paper
focuses on the study of deep-sea turbines and their results. A study was conducted on the capture chamber. The
turbines are driven and generate electricity by using a wave energy harvesting system (oscillating water column).
Reaction turbines (impulse and Wells turbines) are tested and evaluated for performance in an oscillating water
column system. Reaction turbines have a narrow operating range, and higher peak efficiencies. In contrast, turbines
that have a greater operating range and lower peak efficiency are impulse turbines. Wells stator turbine has the
highest efficiency while a variable pitch axial impulse turbine has the widest operating range. Better efficiency
possessed by turbines with optimized geometry than other turbines.