AUIQ Technical Engineering Science

Autism spectrum disorder (ASD) is a prevalent condition in childhood, affecting around 1 in 44 individuals. Approximately 53% of children with ASD exhibit one or more challenging behaviors (CBs), which include aggression, self-injury,
property destruction, elopement, and more. This percentage is significantly higher compared to their typically developing
peers or those with other developmental disorders. Cognitive-behavioral therapy (CB) has numerous detrimental effects
on the individual, all of which are linked to an unfavorable long-term result. When it comes to caregivers of children
with ASD, the presence of Challenging Behaviors (CB) is a more dependable indicator of stress than the intensity of the
child’s primary ASD symptoms. This study examines the use of fixed facial traits extracted from photographs of autistic
children as a biomarker for distinguishing them from healthy children.
This research extracts characteristics from the power spectrum density (PSD) got using t-f (SDFT) analysis of each
autism face image. The acquired characteristics are then input into a convolution neural network (CNN) to classify the
face image as autistic (happy, angry,..etc.) or not. The accuracy of this study’s given result that used the SDFT of the
image is 52%, and that of t

With the increase in internet usage, data exchange happens at a higher pace, but with this comes the risk of security
breaches. Hackers often target data exchange, making security a top priority. To address this issue, steganography has
proven to be an effective solution. It involves concealing confidential data behind seemingly innocuous cover files,
making it less likely to be detected. In a recent paper, the use of Sine chaotic map was proposed as a way to enhance
security. Chaotic maps are sensitive to initial values, non-linear, and non-periodic, making them ideal for encryption. The
proposed method involves using a video as the cover file and an image as the secret data. The video is split into frames
in YUV form, and the position of pixels is changed using the sine chaotic map. The hamming code is used to encrypt and
embed the secret information in the frames, after applying the cycle shift. Using multiple encryption techniques before
embedding secret data in the video increases the level of security and ensures that the information can be extracted
from the stego video without any losses. The results of this method show that it is highly effective, as evidenced by the
PSNR value of 78.23dB for the stego video with high value of hiding capacity and the SSIM of 0.99 between the cover
video and stego video.

The establishment of check dams is considered an essential component of watershed management and sustainability,
as these structures have many purposes. This review study provides an overview of check dams uses using field-based
data from all around the world. As a result of more than two decades of research work, check dams are built to manage
sediment accumulation and soil erosion, lower upstream reach slopes, stabilize torrents, and control floods in a successful
and efficient way. The review revealed that properly constructed check dams can reduce soil erosion by up to 60%
and increase groundwater recharge by 30% in arid regions. However, some researches showed that some projects had
unsatisfactory outcomes. The failure of the projects was for many reasons including poor building quality, unproper
site selection, and finally fail to meet design requirements. The future recommendations include the need to conduct
research on enhancing design and implementation processes, examining the possibilities of applying new materials and
technologies and adopting the check dam projects that are suitable for every area. Policymakers can use this survey can
ensure future projects efficiency and sustainability by comparing them into the literature worldwide, through planning,
continuous maintenance.

The watershed dams water harvesting establishment is a complex decision-making process due to the existence of
several critical factors on which the project is based adopted. Such complexity renders consideration for the priority
scale of development, especially when the project considers several possible sites against a plethora of criteria. These
criteria may be of a technical, economic, social, cultural, environmental, legal, and political nature, thereby increasing
the complexity of the framework under which the decision has to be made. Appropriate solutions for the challenge
have to consider Multi-Criteria Decision-Making (MCDM) approaches. MCDM is defined as an organized approach to
decision-making designed to help in site selection from amongst alternative feasible sites based on a range of criteria.
Most of the prominent MCDM methods used over the literature are including Analytic Hierarchy Process (AHP), Weighted
Linear Combination (WLC), Fuzzy logic (FL), Boolean Methods, Technique for Order Preference by Similarity to Ideal
Solution (TOPSIS). The MCDM methods represent a different strategy of integration and analysis of multi-dimensional
criteria that influence the choice of the dam site. The advantages of the MCDM methods are not only help to undertake
a detailed study of priorities for the construction of the dam; however, they devise a methodological approach to the
selection of the most appropriate location of dams for their construction. The present survey exhibited and evaluated
all the conducted researches to rank the dam construction projects using the MCDM methods. This review provides an
comprehensive assessment and evaluation for the literature and recognizes the opportunities for the improvement of the
MCDM methods effectiveness under complex dam site selection problems. The survey is expected to contribute toward
refining strategic decision-making processes required for sustainable infrastructure development.

The goal of our investigation is to create a way of directing a robotic limb that is based on an adaptive optimum fuzzy
algorithm, as is clear from the study’s title. To create an adaptive fuzzy controller for a robotic limb is the goal of this
project. By joining the robotic leg to the human foot, it is possible to increase load-bearing capacity and make up for
limitations brought on by injury, ageing, etc. Consider a 3R planar open chain for the leg. Rotating actuators supplied by
a fundamental control system are used to regulate the robot joints’ motion in order to counteract external stresses and
provide the required torque for steady motion. The control system generates control commands using fuzzy logic and
fuzzy rules. The fuzzy rules parameters must be modified based on the external loads and conditions that are perturbing
in order to achieve the best energy consumption performance. As a result, fuzzy rules are variable-parameter adaptive
functions. A method based on the honey bee algorithm (BA) is used to change the settings. The stated control system
should activate joint actuators in the presence of disturbance loads to maintain steady and accurate motion.

Filters are essential tools in the field of signal processing, they have been employed to control the signals and reduce or
eliminate the noise associated with the signal. In this article, we will show the importance of filters in signal processing,
especially in the field of biomedical engineering. As these filters will be applied to filter and remove noise from the
electrocardiogram (ECG) signal, we will learn about some of the filters in this article

The overabundance of suburbs planned and built on greenfield grounds formerly classified as green-belt property is the
consequence of ineffective urban development limits. It would be unnecessary to further intrude onto precious greenfield
property, which is vital for future recreational, biodiversity, forestry, agricultural, and food supply needs. Controlling
the growth of developed land, prohibiting the construction of tall buildings close to the shore, and establishing green
open spaces with an emphasis on areas with elevated surface temperatures are the adaptation strategies for reducing
Jakarta’s urban heat island phenomenon. Urban population growth contributes to increased carbon dioxide emissions,
which exacerbates climate change. Cities are growing as a result of this expansion and require more facilities and
infrastructure. Due to heat trapped by urban buildings, part of the energy and CO2 emissions from this growth are lost.
Because of their impermeable surfaces and increased solar radiation, urban heat islands (UHI) impair thermal comfort
and have a significant impact on climate-related disasters in modern cities. Threats to infrastructure, human health,
and urban ecosystems arise from rising outside temperatures, particularly in lower-altitude cities. These initiatives
concentrate mostly on Jakarta, Indonesia, and address UHI mitigation and sustainable building practices. Architecture
must fundamentally alter the underlying principles of cities and structures to be considered truly sustainable

Sedimentation in reservoirs is a critical concern of the 21st century which has affected the sustainability and functionality of water retaining structures. This technical review paper on reservoir sedimentation provides a comprehensive
analysis of their causes, mechanisms, and their mitigation/control techniques. The paper starts with sedimentation
in the reservoir at a global scale focusing on natural (Soil Erosion) and anthropogenic (man-made) factors such as
deforestation, land clearing for agricultural purposes, and urbanization contributing to sedimentation in the reservoir.
The origin of sediment is heavily influenced by topographical features, with origins located far-reach, mid-reach and
near the reservoir. The sedimentation in reservoir had significant impacts which includes storage loss of reservoirs,
degradation of aquatic habitat and soil pollution. A different physical process that is involved in reservoir sedimentation
such as turbidity current, delta migration, climate change, and flow circulation are discussed in detail. Various mitigation
strategies such as sediment yield reduction, routing of sediment through/ by reservoir, and removal of sediment by
mechanical means are used in different parts of the world are presented. Case studies from different regions are
selected to show the effectiveness of these strategies in real-world situations The success of sedimentation management
strategies is dependent on site-specific factors such as topographical features, vegetative cover, climatic conditions,
sediment properties and reservoir geometry. Among all the sedimentation management strategies discussed in the paper
special attention is given to Flushing and Sluicing process while the growing implementation of bypass tunnels has
also been observed in countries like China, Japan, and Switzerland. In later section paper also highlight the limitation
of those strategy among which the efficiency of flushing process requires further investigation as future research.
In addition, numerical modelling such as with RESCON 2 software can be used to understand the sediment flow
behaviour near dams. In a later section, the paper also highlights the significance of integrated sediment management
plans which involves collaboration between policymakers, engineers, scientists and local people. Sustainable land use
practice like no till farming, vegetative cover to control soil erosion, routine monitoring of sediment deposition are
main components of this approach. However, challenges always remains such as funding constraints, conflict among
stakeholders, and uncertainties in due to climate change. Considering the scientific knowledge, engineering experts,
stakeholder engagement, and effective and sustainable solutions are necessary to ensure the functionality, durability,
and sustainability of reservoirs.

The area of computer science is flourishing, as shown by the rising number of academic works published and the rising
number of scholars adding to the existing body of knowledge. This has made it difficult to find previously unrecognized
links between publications and those studying them. Using machine learning techniques to foresee missing links and
unveil hidden connections, complex network-based link prediction has emerged as a helpful resource in addressing this
difficulty. This study aims to solve the problem of finding links between authors’ publications by exploring the use of
network-based complex link prediction approaches. A large-scale bibliographic database collected from various reliable
sources, including but not limited to Google Scholar, was used. A Support Vector Machine (SVM) classifier was used
to predict the possibility of a new link between an author and his publication. Accuracy was one of the several criteria
used to evaluate the performance of the SVM classifier, which was relatively high at 96.66%

The urgent need to mitigate environmental impacts in the construction industry drives the exploration of sustainable
practices, such as the use of recycled materials in concrete production. The primary objective of this study was
to enhance the predictability of compressive strength in the concrete through the application of advanced machine
learning (ML) techniques, specifically Gradient Boosting Regression (GBR) and Random Forest Regression (RFR). Using
a comprehensive dataset of 353 eco-friendly concrete samples, the study carefully developed and validated these models
to evaluate their performance. The findings exposed that the GBR model outperformed the RFR model, obtained
an R2 of 0.97 in training phase and 0.96 in testing phase, the findings supported further with root mean squared
error (RMSE) of 1.99 and 3.06, and by mean absolute error (MAE) of 1.44 and 2.38 for training and testing phases
respectively, where indicating high predictive accuracy. Conclusively, the broader adoption of GBR model for similar
applications recommended by the study and points towards future research directions to integrate more diverse datasets
and investigate more predictive models to improve sustainable construction practices.