AL ARBA'IN

This study deals with the Supreme Leader\\\\\\\\'s interpretation of the
Arbaeen walk with a qualitative approach from the methodical approach
of the (topical) theory of re-examination and document analysis. From
the point of view of the Supreme Leader, the phenomenon of Arbaeen,
the largest gathering in the world, is one of the movements of faith that
is considered among the positive and joyful points of our country and
for our nation. Romantic behavior is spiritual in the material world and
the movement is love and faith. It is a divine and spiritual phenomenon,
unique and unprecedented, which has not been advertised, but it suddenly
appears, the hand of God is more evident than anywhere else... It is
a spiritual journey. This incident is extremely important. There are
phenomena for which there is no advertising, no effort is made. It really
cannot be described; Like many of these important divine phenomena,
it cannot be properly interpreted; It means that this incident cannot be
analyzed. This march gives greatness to the Islamic world; There are
two groups of active activists, including marchers, hosts and opponents
of the march, and the third group is those who monitor the march and
Islamic issues. Iranian and Iraqi officials should make this march easy
for those who love this work, which is the responsibility of the officials
of different parts of the country. The management of the march and its
survival is in the hands of Almighty God.

In light of the increasing challenges posed by climate change and
environmental crises, there is an urgent need to develop sustainable
strategies that focus on improving the quality of bitumen, the basic
component in the asphalt industry. This study aims to explore the use of
remote sensing and geographic information systems (GIS) techniques
to identify ideal places to set up plastic recycling facilities. Studies
indicate that adding materials such as polyethylene terephthalate
(PET) to bitumen improves its physical, mechanical, and chemical
properties, especially in high-traffic roads such as city entrances and
intersections. The exploitation of plastic waste accumulated during
religious visits in Karbala in general and the Arba’een pilgrimage in
particular for recycling is an example of making use of resources in
a sustainable manner, especially in strengthening infrastructure. This
study is consistent with Iraq’s 2030 vision for sustainable development.
Since 2016, the Iraqi government has adopted the 2030 Sustainable
Development Goals and has taken serious steps to implement them. Key
criteria for site selection include: proximity to sources of plastic waste,
availability of basic infrastructure such as roads and public facilities,
and compliance with local and national laws and regulations, including
labor and raw materials, a deciding factor. The environmental impacts
of the facility and the ability to expand to accommodate the increasing
demand were also taken into account. The project takes advantage of
precise spatial analyzes provided by satellite images and GIS tools, to
study the geographical and environmental influences that may affect
the effectiveness of recycling operations. Environmental indicators are
also used to evaluate the environmental impact of each potential site and
determine the economic benefits of each option. This research represents an important step towards achieving more sustainable use of resources
and improving the quality of materials used in infrastructure, which
supports efforts to preserve the environment and enhance economic
efficiency

An effective Automated Traffic System for crowds is a serious
difficulty in many countries, like the Republic of Iraq, where
millions of tourists from all over the world pay their respects at
the holy monuments. This religious rite necessitates enormous
groups performing the identical behaviors at certain times, making
crowd management vital and difficult. Disasters such as stampedes,
suffocation, and congestion become more possible when crowds
are not properly managed and controlled, as happened in 2019
during Tuwairij’s Ashura run. Nowadays, an intelligent Automated
Traffic System for Crowd represents excellent solutions for crowd
management and control, loss minimization, and the integration of
various smart technologies. Furthermore, an intelligent Automated
Traffic System for Crowd allows strong interaction and diverse
connections between different devices over the Internet, resulting
in big data.
This study proposes a smart approach to an intelligent Automated
Traffic System for Crowd technology to manage crowds while
avoiding congestion at the entry and exit points of the area between
the Two Holy Mosques (Imam Hussein and his brother Imam Abbas,
peace be upon them) in Karbala. The study employs a proposed
mechanism that classifies visitors based on the data collected and
takes advantage of an intelligent Automated Traffic System for
Crowd and cloud infrastructure to monitor crowds within a crowded area, identify
evacuation routes for visitors, and guide visitors to avoid congestion
in real time. In addition, the study aims to provide crowd safety
and security based on actual scenarios by controlling and guiding
visitor movements in accordance with potential hazard features,
visitor behavior, and environmental factors.

Twenty-four groundwater samples were collected at different
depths within the Dammam aquifer and Quaternary deposits. A
detailed hydro-chemical study of water samples was conducted,
including physical properties; Hydrogen number (pH), total
dissolved solids (TDS), and electrical conductivity (EC), while
the chemical analysis included the major anions; SO4-2, Cl-,
HCO3-, and major cations; Ca+2, Mg+2, Na+, and K+, in addition
to the minor element (NO3-). The results indicate a neutral to
slightly alkaline water with pH of 7.17 which characterized by
hard water that is neutral- slightly alkaline water. The TDS exceeds
the permissible limits for drinking, with an average of 2787
ppm, which represents slightly brackish water. Conductivity EC
indicates heavily mineralized water with EC of 4310.8 μs/cm. The
predominant cation was Mg+2, and Na+, while the predominant
anions were SO4-2, and Cl-. The prevalent cation in the aquifer
Na+ of 49%, followed by Ca+2 of 30%, Mg+2 of 17%, and K+
of 4%, while the prevalent anion was SO4-2 of 48%, Cl- of 31%,
and HCO3- of 21%. Groundwater is classified as unsuitable for
drinking, while it is suitable for irrigation. The water type is Na-
SO4 affected by the interaction between aquifer material (Halite,
dolomite, and calcite), and the groundwater in contact.

The purpose of this study is to analyse crowd behaviour using
a deep learning model. This research investigates the effectiveness
of deep learning techniques in estimating crowd levels, aiming to
improve accuracy and efficiency in real-time applications. The
study employs a convolutional neural network (CNN), architecture
trained on a diverse dataset of crowd images. Key steps in the
proposed approach include data preprocessing, model training,
validation, and testing. Major findings indicate that the deep
learning model achieves lower error rates in both the training and
testing phases, demonstrating its robustness and generalisability.
Specifically, the model attained a mean absolute error (MAE) of
55.34 and a root mean squared error (RMSE) of 98.32 during
testing, compared to 56.5 MAE and 99.13 RMSE during training.
These results highlight the model’s capacity to generalise well to
new, unseen data. The study concludes that deep learning models,
when properly trained and validated, can significantly enhance
crowd-level estimation, offering valuable insights for applications
in public safety, event management, and urban planning. Future
work will focus on expanding the dataset and refining the model to
further improve performance and applicability. Overall, our study
presents a promising advancement in crowd counting technology
with practical implications for crowd management at large-scale
events like the Arbaeen Pilgrimage

Iraq annually, specifically in the province of Karbala, a great
millionaire visits with the fortieth anniversary of the martyrdom of
Imam Hussein (peace be upon him), and it is from different parts of the
world, where the number of visitors in recent years has reached about 22
million foreign visitors and in the shadow of all circumstances, even in
the period of the COVID-19 pandemic. It is our responsibility to secure
health care for visitors and manage it in innovative ways in line with
the technological developments of health care that limit and almost
prevent the occurrence of disease cases and fill the potential gaps for
the spread of diseases, especially as we are in the era of technological
development and artificial intelligence, where the use of advanced health
care means would facilitate dealing with such huge numbers, ease of
control, disaster prevention and crisis management.
In this research article, we will discuss the importance of advanced
technological healthcare means and their contribution to facilitating the
management of the health of visitors and the management of crowds
in this major event, how to keep up with them gradually, starting with
the simplest methods, what are the factors that help in their success,
and what are the future visions to improve such a global million visit

Mass gatherings, especially the Arba’in pilgrimage in Karbala, are
a fertile ground for the spread of deepfake videos. These gatherings
rely heavily on visual content circulating on social media and
crowd-sourced platforms. Adversaries can exploit this by creating
fake videos that mislead people and confuse public opinion. Based
on the study’s recommendations, there are some ways to combat
the spread of deepfake videos in the context of mass gatherings.
In this work, we classify deepfake detection methods according
to the applications they are used for: hybrid multimedia detection,
image, audio and video detection. This study aims to provide the
reader with an enhanced understanding of: how deepfakes are
created and identified; the latest developments and discoveries in
this field; the deficiencies in current security measures; and the
four areas that need further research and thinking. According to the
results, the most widely used deep learning technique in research
is traditional neural network (CNN) methodology

The visit known as the Arbaeen happened forty days after
Imam Hussein›s (peace be upon him) martyrdom on the tenth of
Muharram in the year 61 AH. Delegations from various Iraqi cities
and villages travel to Karbala, the home of Al-Hussein (peace be
upon him), and they are accompanied by sizable delegations of Ahl
al-Bayt school adherents from a variety of nations, including Iran,
Bahrain, Kuwait, Lebanon, Pakistan, and others. In this research,
we examine the estimation values for the numbers of visitors by
utilizing time series analysis and A few tests are the mathematical
time period needed to validate our findings. To determine whether
the results are accurate by the sample number of visits from 2017
to 2023 provided by the Holy Imam Hussein Shrine’s General
Secretariat. Because government organizations and the Holy Shrine
need to be able to provide efficient services, including a counter
for food and health services and a comfortable place for visitors
to sleep, it is vital to forecast the number of visitors

Dust storms are considered as one of the important weather
phenomena that have harmful and negative effects on the environment
in various aspects. They arise and occur frequently depending on
multiple topographical and climatic factors. In this study, data from
the Iraqi Meteorological organisation and Seismic Monitoring IMOS
recorded at the Karbala metrological Station was used to test and
examine the statistical behaviour of dust storms for the period from
1980-2022 by dividing those dust storms into severe, moderate,
and light depending on the extent of visibility and the period the
dust storm lasted. Studies compared the frequency of dust storms
with the weather conditions, such as wind, rainfall and max and
min. air temperature. The results showed that there was a decrease
in the tendency for dust storms frequency by 9%, accompanied
by a decrease in the recorded wind speeds to about 2% within the
average speed of about 2.7m/s. As for rain alone, there was also a
decrease in its trend’s quantities by about 0.28 within the annual
average for four decades, which reached 94 millimetres. On the
other hand, max. and min. temperature records increased about
1C0, but this increase is part of global warming and doesn’t affect
dust storm frequency rate alone, but can be worked with other
atmospheric elements. From the current results, we concluded that
the frequency of dust storms in Karbala province is affected by
the boundaries of the local governorate, and there are other factors
which play a role in the statistical behaviour of the frequency in the occurrence of dust storms, which may be regional or global. The
results can be used to give warnings to visitors heading to Karbala
to take necessary precautions and prepare for the occurrence of
dust storms in seasons of drought and lack of rain.

Ziyarat Al-Arbaeen is one of the annual religious and cultural global
events, which involves presence of a large number of visitors from the Middle East region in particular and all around the globe in general. Its importance in terms of appreciating higher human values embodied within this
comprehensive revival project, amidst the intellectual challenges that confront humanity in its various dimensions and inclinations is undeniable. To
this mean benefiting of the modern technologies as a strong and effective tool for well managing and control of this event can play a vital role. It includes space applications technologies and engineering such as GIS and remote sensing, telecommunications, artificial intelligence, medical sciences and
technologies, informatics, mathematics, statistics, and so on. In this presentation, the authors with background in space science and technologies, and telecommunications focus on and highlight effectiveness and importance of these fundamental and infrastructural technologies. Authors believe that the
joint work and cooperation of the organizational and independent experts
from the relevant entities and sharing knowledge and experience can lead to increment of the synergy of work for well managing and control of the event. Authors, who are from Iraq and Iran, worked for long term in their relevant national space technology and communication organizations in both
managerial and specialized levels. They share the feasible and accessible
potentials and possibilities in both countries for well managing and control of the Ziyarat Al-Arbaeen event by giving the related examples that is
available separately in both countries and suggest joining forces by the relevant entities, scientists and experts in this connection. In this presentation,
authors determine the steps of ideas in order of priority and importance,
which inevitably involve creativity. They believe that the idea of ​​experimenting with collaboration and remote work will certainly yield success.

Security cameras and video surveillance systems are crucial
infrastructures for ensuring the safety and security of the general
population. Nevertheless, the identification of high-risk scenarios using
these methods is still predominantly carried out manually in several
places, particularly in Karbala. Insufficient personnel in the security
industry and restricted human capabilities might result in unnoticed
dangers or delays in identifying potential threats, so endangering the
public during crucial events. As a reaction, many entities have created
robotic and automated methods to detect potential dangers by analyzing
CCTV footage. The objective of this project is to create an affordable and
efficient artificial intelligence (AI) system that can accurately recognize
and identify weapons in real-time surveillance films, even in various
situations. The system consists of a training phase for the Convolutional
Neural Networks (CNNs) using a data set containing images of weapons.
The second stage is testing the system, which demonstrated its high
ability to detect weapons with high accuracy compared to previous
research, the accuracy of the proposed method reached 93%