Journal Of AL-Turath University College

In this paper, we discuss the integration of Power Line Communications (PLC) with the Internet of Things (IoT) to enhance the efficiency and stability of the smart grid. This study aims to improve data transmission between smart grid devices, including renewable energy sources such as solar and wind. The proposed algorithm is based on dynamic demand-driven pricing and real-time data analysis, which contributes to improving the efficiency and stability of the system. The results show that this approach outperforms existing technologies such as ZigBee and LoRaWAN, achieving a high accuracy of up to 98.87%.

As the Internet of Things (IoT) expands, the need for efficient and secure data processing at the
network edge has surged. Fog computing, which exte nds cloud services to the network’s edge,
addresses these needs. This paper introduces a mechanism that ens ures trustworthy data
forwarding within the MQTT protocol, widely used in IoT. The mechanism integrates fog
computing resources into MQTT, improving data reliability and security. It uses trust models to
assess the credibility of devices and nodes involved in forwarding, and incorporates secure
communication protocols (TLS/SSL, MQTTS, PKI) and data integrity methods (MAC, digital
signatures). These fea tures ensure secure and trustworthy IoT data transmission, while
maintaining low latency and efficient reso urce use.

Cloud computing service provides an important and effective element, as it has
become a radical change in the field of data analysis, as it provides a powerful and flexible
platform at the same time for storing, processing, as well as analyzing huge amounts of data in
various fields, especially with the development taking place in the automation of devices and
an inspiring source in analyzing or controlling it. Or even collect data from it for deeper
insights, and make decisions based on that data more quickly, especially with the development
taking place in the field of technology. Cloud computing was used to design a program to
collect data, analyze it, and retain the information provided through it, and this works on the
principle of the Internet of Things. This information can be published through a website that
enables the data to be displayed on the interface of the program, and this information can also
be updated and viewed via the website and from a distance through the website. In addition,
users registered within the program can access this information. The goal of this proposed
project is to ensure data updating and transfer of information to any device connected to the
Internet that has access to it and can be displayed within seconds.

The delicate balance between human development and environmental conservation is a
pressing concern globally, particularly in regions undergoing rapid urbanization like Iraq. The
impact of sewage on ecosystems poses a significant threat to biodiversity. This study, titled
"WasteFlow Ecology," delves into Iraq's sewage management challenges, aiming to propose
sustainable solutions for mitigating its impact on ecosystems. Drawing upon multidisciplinary
approaches, the study synthesizes existing literature, evaluates sewage system status, and
assesses biodiversity impacts. Through the WasteFlow Ecology framework, it offers innovative
strategies for sewage management, emphasizing water recycling and biological treatment. The
study's objectives include evaluating current sewage systems, synthesizing literature, assessing
policies, conducting biodiversity impact assessments, and proposing solutions. By integrating
ecological principles with waste management strategies, this study aims to guide policy and
inspire sustainable development initiatives in Iraq and beyond.

Skeletal muscles are the biggest cells in the human body, the chief purpose of skeletal
muscles are drive motion. Renewal is procedure that depend on skeletal basement membrane,
are precursors to skeletal muscle cells and are responsible for the ability of
Sample of 50 mature male rabbits ere used in this study, the
muscle tissue to regenerate.
).
body weight range between (2 .5 -3 ) kg . Animals were separated randomly into three sets (
operative
rd
set 1 control group contain of 10 animal , set 2 contain of 20 animal at 3
operative week ). Evaluation the morphological
post
week , set3 contain of 20 animal at 6
th
post--
changes that happen in regeneration and degeneration were selected the extensor digitorum
renewal of skeletal
longus muscle and examination after 21days and 42 days post
operative .
muscle characterizes an vital homeostatic process of skeletal muscle in adult.In development,
the capability of skeletal muscle to regenerate is response to different injured stimuli,
restoring damaged myofibers. Repair of muscle fibers is dynamic process include
regeneration and degeneration , in the case of degeneration the muscle fibers not It is not
complete recovery but in the regeneration the myoblast . The skeletal muscle consist of
myofibers formed by myoblasts( mononucleated )the myoblast has the principle role in
growth of muscle fibers and development

The present study was conducted on Tigris River at Salah –Aldin governate, Iraq , selected
five site distributed along the river during November 2012 to June 2013. The first site located
close to satiation for refinery drinking water at aldour city, while the last site was at Abo-Dalf
area. The level of fourteen compounds of Polycyclic Aromatic Hydrocarbon (PAHs) used in
this study listed below as organic pollutants; Naphthalene, Acenaphthalene, Fluorene,
Phenanthren Anthracene, Pyrene, Benzo(a) anthracene, Chrycene , Benzo (b) Fluoranthene,
Benzo(k) Fuoranthene , Benzo(a) pyrene, Dibenzo (a,h) anthracene , Benzo (ghi) Perylene
and Indeno(1,2,3-cd) pyrene. The lowest level of PAHs in water was B(a)P(0.0005µg/L) in
summer term at site No.(2) while the highest value of the same compound in the site No.(1)
(1.510 µg/L) at autumn term also. The lowest level of PAHs in sediment was B(a)Fand
Pyr(0.001 ng/g) at winter term in site No.(5) ,while the highest value of Acpy (98.981 ng/g) at
autum term at site No.(3)

The COVID-19 pandemic has a serious impact on education and cultures across the world,
especially in the developing countries such as Iraq and Qatar. Millions of students in those
countries are at risk of educational exclusion and inadequacy unless an urgent compensatory
action is taken to curb or at least mitigate the impact of COVID-19 to ensure sustained adequate
learning whether online, in person or hybrid. In mass communication and educational field,
the COVID-19 pandemic has arisen as a multicultural threat. The pandemic made global mass
schooling unexampled in the year 2020. This has therefore called for various changes in the
modes of communication and translation during this raging pandemic. The paper first takes a
glance at the influence of communication across cultures during the pandemic. In this case the
Arabic cultures and language have been selected. The major base is through an outright survey
of secondary published information. The survey conducted is extensively presented. In the
selected articles such as having difficulties in translation among other changes in language
during the time may have posed challenges. This, among other challenges in cross cultural
communication, can provide instantaneous opposition to the flow of information. In either case,
the study closes by recommending the constant update of individuals and citizens of Arab
countries, Iraq in particular, through qualified translators and interpreters. In this case, the study
draws fine communication to advocate for the differential changes in the manner and discussion
of various communication techniques during the drastic time of the pandemic. This serves to
paint the picture of how mass communication and translation have been affected overtime.

A poet, a story teller, or a novelist has ever to rely on his experience in life, making use of all
the contexts underlying most of those significant representations, whether abstract or concrete,
which surround him during the course of his life. All kinds of literature, drama, poetry, and
fiction witness the presence of their creators in almost all their manifestations and minute
details of the literary work. Literary authors always rely on their personal experience, to a
greater or lesser extent, and the most successful writer is the one who manages to create out of
his own particulars something objective, general, and universal.
Both poets, T. S. Eliot and Robert Lowell, deal with and display their own personal experiences
in their poetry; that is, both confess their personal touches in their poetry in one way or another--throughout symbols, allegories, direct and indirect descriptions, etc--yet the former manages
to appeal to the readers and critics much more than the latter does; that is, Eliot presents his
personal experience in such a way that it looks objective; it can be understood alone per se
without resorting to the account of his own personal life because it has been made part of a
larger structure that gives clues to their explanations. Whereas Lowell's personal remarks can
by no means be understood without full awareness of his own personal life, a trait of his poetry
that makes it defective.
This paper is an attempt to make a comparison between Eliot’s and Lowell’s poetic experience,
solving the question whether Eliot is, Like Lowell, a confessional poet or not, and how their
personal experiences serve their poetic process. Besides, this study makes some touches upon
the importance of their personal experience to their poetry as to whether it contributes to their
greatness as two modern poets.

Point cloud noise filtering is a critical step in the preprocessing of three-dimensional data, such
as those obtained through LiDAR or photogrammetry. This abstract provides a concise
summary of the key aspects discussed above. Point clouds, comprised of discrete points in
space, often suffer from noise stemming from various sources, including sensor inaccuracies,
atmospheric conditions, and collection artifacts. Such noise can degrade the quality and
reliability of point cloud data, making effective filtering imperative. This survey covers the
theoretical background, highlighting the diverse noise types—random and systematic, and the
significance of noise reduction. It explores previous works in the field, discussing the strengths,
methods, and performance of various noise filtering techniques. Notable approaches include
spatial-domain and frequency-domain methods, machine learning, multi-sensor fusion, and
graph-based filtering. Combining techniques and methods proves promising for enhancing
point cloud noise filtering. Adaptive filters, multi-resolution analysis, and integration of
feature-based and spectral methods present unique opportunities. The proposed sequence of
steps for optimal noise filtering encompasses data preprocessing, feature extraction, the
merging of spatial and frequency-domain techniques, adaptive filtering, multi-sensor data
fusion, feature preservation, edge detection, and time-series filtering. Evaluating results,
validation, documentation, and continued research are essential components of the process. In
conclusion, point cloud noise filtering is a dynamic field, offering diverse tools for handling
noise in point cloud data. By following a structured workflow and selecting methods that align
with specific application requirements, practitioners can achieve noise reduction while
preserving critical features. This survey provides valuable insights into the multifaceted world
of point cloud noise filtering, guiding researchers and practitioners towards robust data
preprocessing.

Artificially intelligent technology (AI) is becoming a transformative force in the healthcare
industry, changing many aspects of medical practice. This paper looks at the significant impact
of AI on medical diagnosis and treatment planning, paying particular focus to how AI impacts
patients., healthcare providers, and the larger healthcare ecosystem. The paper first provides
an overview of the state of artificial intelligence (AI) applications in medical diagnostics and
then focuses on machine learning developments., computer vision, and machine learning to
process natural languages. By observing implementation and case studies, current research
assesses how well AI diagnoses medical diseases, from image processing to pathological
interpretation. This study also looks into the application of AI to treatment planning and the
ways in which Treatment strategies can be optimized and customized with the assistance of
machine learning models. To enhance treatment outcomes, research is examining the
integration of genomes, real-time monitoring, and patient data. In order to provide ethical
patient-centered care, we also go over the issues surrounding AI-driven treatment choices.
Additionally, this paper evaluates the difficulties and impediments to the broad use of AI in
healthcare. We will go over issues like data security, interoperability, and the requirement for
legal frameworks to give a thorough grasp of the barriers to the smooth incorporation of AI
technologies. Research methods include things like speaking with health experts, carefully
evaluating the literature, and looking at real-world situations. The purpose of this research is
to offer a unique viewpoint on the revolutionary possibilities of artificial intelligence (AI) in
medical treatment and diagnosis planning. by combining information from various sources. In
the end, this study emphasizes the promise, challenges, and ethical quandaries related to AI
integration and provides relevant information about the ongoing paradigm shift taking place in
the medical field. As healthcare changes continue, it is imperative to comprehend how artificial
intelligence (AI) affects medical diagnosis and treatment planning in order to ensure effective,
accurate, and patient-centered care. Keywords: healthcare, planning treatments, medical
diagnostics, artificial intelligence.

Due to successive international financial crises, finance stability became increasingly
important amid high inflation during the current decade along with different economic and
financial fluctuations and reductions in rate of growth coincided with the absence of economic
stability as a result of political instability. This research aims to highlight the instability of the
financial and economic indicators in the Arab finance as well as analyzing related data using
the Minitab statistical program to measure the trend of these indicators.

The effect of atmospheric temperature on stress corrosion cracking susceptibility of low carbon
steel which immersed in 0.1M of sulfuric acid solution during 14 days was studied using U
bend test. Two testing were carried out, the first in January and the second in July in the weather
conditions of Iraq. The variance of atmospheric temperature between them was equal to 40oC.
Corrosion rate was calculated using weight loss method. The increasing in temperature will
increase the chemical reaction average, so the corrosion rate and weight loss of the used
specimens in the second test was greater than the first. An invisible deep cracks was generated
in the second specimen at the eleventh day and it’s propagate gradually until fractured into two
pieces at the last day as a result of high corrosion reaction besides the propagation of
microcracks which accelerates the specimen’s failure, but the first specimen was not fractured.
The corrosion process was affected the convex regions of the U-shape specimen because the
stress which affected it was concentrated in it much more than the others. The temperature
increasing decrease stress corrosion life of the second specimen.

East Baghdad's heavy oil is difficult to transport in the pipeline system due to its high viscosity.
This work involved studying the viscosity reduction in the east Baghdad crude oil (EBCO)
using surface-modified silica particles. Different operating variables were investigated, such as
average particle sizes of (5, 10, and 15µm), particle loading of (0, 200, 400, and 500 ppm), and
temperatures (10, 30, and 50 oC), for their effect on viscosity reduction. FTIR and contact angle
(WCA) techniques were utilized to identify the particle's surface morphology and degree of
wettability before and after surface modification, respectively, while the Brookfield viscometer
was used to evaluate variation in the oil viscosity. Experimental results showed that
hydrophobic particles were more feasible for use in viscosity reduction, hydrophobic silica
particle loading of 400 ppm has the optimum reduction of viscosity of 31% at 30 oC; increasing
the loading beyond the optimum particle size has a negative effect on the viscosity reduction.
The ambient temperature has a positive impact on the level of viscosity reduction in the
existence of hydrophobic silica particles. A power law equation was developed with a
correlation factor of 0.995 to evaluate the crude oil viscosity as a function of hydrophobic
particle loading and temperature.

In this study, the efficiencies of two photo-catalysts in a hybrid process composed of electro
Fenton and photo-catalytic process used for treating petroleum refinery wastewater (PRW)
were evaluated and compered. Effects of current density (5 and 10 mA/cm2), photo-catalyst
dosage (0.1 and 0.3 g/L), and Fe2+ concentration (0.1 and 0.2 mM) were considered. Results
revealed that increasing current density has a positive effect on the removal of COD for both
catalysts with higher removal obtained using ZnO catalyst. Increasing the dosage of catalyst
has also a progressive effect on the removal of COD for both catalysts while increasing Fe2+
concentration has a positive effect on the removal of COD in case of using TiO2 and a negative
impact in case of using ZnO. The best removal efficiency (87.68%) corresponding to a final
COD of 50 ppm can be obtained at a dosage of ZnO of 0.3g/ L, pH of 3, current density of 10
mA/cm2 and Fe2+ concentration of 0.1 mM during 40 min in which an energy consumption of
20.88 kWh/m3was required. In case of TiO2 catalyst, removal of 83.99% can be obtained at
TiO2 dosage of 0.3g/ L, pH of 3, current density of 10 mA/cm2 , and Fe2+ concentration of 0.2
mM during 40 min in which an energy consumption of 25.5kWh/m3was required. This is an
indication that ZnO has better photo-catalytic efficiency than TiO2. However, both of catalysts
have the ability to reduce the COD level below the limiting value (100 ppm) for discharging to
environment.

Images with fine imperfections introduced by malicious optimization techniques to deceive
classifiers are examples of attacks in computer vision. Machine learning models have proved
their susceptibility to attacks from the adversary, despite displaying excellent capability in
completing complex cognitive tasks, particularly those linked to computer vision, such as
classification and picture recognition. This shortcoming compromises the deployment of these
learning algorithms, which could be detrimental to future progress in this area. Initially
promising, the various defenses proposed proved brittle and ineffective against powerful and
adaptable attacks. Numerous solutions have been proposed in the literature to address these
vulnerabilities. However, developing an effective defense mechanism is challenging, as several
methods have previously been shown to be ineffective against attackers. That is, a similar task
of research in this area is relevant. The purpose of the work: to study the performance of the
digit recognition system with noisy images. To solve this problem, you will need first develop
the system for recognizing digits in images using one of the machine learning methods; achieve
sufficiently high accuracy of this system; noise the images from the training sample and
evaluate the final accuracy of the recognition results without retraining the system; process the
obtained results and draw conclusions.

The industrial sector is considered one of the main sectors in the development of the national
economy and contributes effectively to the gross domestic product and national income, and
the manufacturing process plays its role in the transition of the national economy to a developed
economy that achieves sustainable development. The manufacturing sector is the most
important sector in industrial production, has an active and influential role in the development
and revitalization of the local economy of the state, and contributes effectively to building an
independent economy. The research aims to shed light on this vital industrial sector and analyze
its data for the period 2015–2020. According to the availability of data from the source, the
analysis was done using the statistical program Minitab, and the research included conclusions,
which indicate that the manufacturing industry in Iraq from 2015 to 2021 were not at the
required level and were fluctuating from year to year. We recommended that the developing
future visions for the development of the manufacturing industry, acquiring knowledge, relying
on available resources, building an industrial development model, and harnessing the available
workforce.

The study aimed to identify the attitudes of melon farmers towards the use of agricultural
techniques related to crop service operations in Tikrit district / Salah al-Din Governorate in
general For the agricultural year 2023 , and the descending order of the fields of study
according to the percentage weight, and the identification of the matrix of correlations between
the fields of study. The research community included all melon farmers in the Tikrit district /
Salah al-Din governorate, who are officially registered in the Tikrit Agriculture division, and
their number is (654) farmers distributed among the districts of the district. A random sample
of 23% was elected in a proportional manner, so that the number of respondents who underwent
research procedures was (150) farmers. The results showed that the general level of attitude for
melon farmers was negative, tending to the neutral attitude and their percentage is 71.3%. We
conclude from this the weak level of the respondents' attitude towards the use of agricultural
techniques related to serving the melon crop, which is an indication of the respondents' need
for information about the importance of using agricultural techniques through the
implementation of various extension activities . In the light of the results and conclusions, the
researcher recommended that it is necessary to focus when implementing the indicative device
on the extension activities that aim to make a behavioral change on the groups of farmers who
have a negative or neutral attitude who appeared in the study.

In the present study, copper sulphate pentahydrate (CuSO4.5H2O) has been utilized as the (Cu)
source and coffee powder extract to create copper oxide nanoparticles (CuONPs) using the sol
gel method at room temperature. CuO NPs was Synthesized with a spherical particle shape
(SEM) were examined using (FT-IR) spectroscopy, x-ray diffraction (XRD), ultraviolet-visible
spectroscopy (UV-Vis), transmission electron microscopy (TEM), and scanning electron
microscopy. The UV-Vis absorption spectrum exhibits an absorption band at 281 nm. By using
XRD, it was determined that the finished product was highly crystalline CuO with diameters
ranging from 15 to 30 nm. A network of CuO NPs with an average size of 20 nm and a thickness
of roughly 8 nm can be seen in the SEM pictures. Studies on weight loss and polarization
curves were used to examine the corrosion-inhibiting capability of carbon steel in molar
hydrochloric acid solutions. The results showed that as CuONP concentration increased, the
effectiveness of prevention also increased. Depending on the isotherm models, the anti
corrosion adsorption process on the surface of carbon steel exhibits Langmuir's behavior as
opposed to Freundlich's. According to thermodynamic characteristics, the adsorption
mechanism has already been determined to involve exothermic, mixed, and spontaneous
adsorption. CuONPs appear to be good carbon steel corrosion inhibitors in acidic settings, and
per the research. CuONPs developed a good protective coating on the steel surface of,
according to scanning electron microscopy (SEM) photographs.

Malware that uses the Internet to commit exploits is becoming more and more commonplace.
Due to the widespread occurrence of malware, manual malware identification is no longer
reliable or efficient. Therefore, it appears that autonomous behavior-based malware detection
through machine learning approaches is a good way forward. Numerous research has
demonstrated how well machine learning works to identify and categorize malware files.
Several machine learning techniques have been studied in this study to identify malicious
software applications such as Random Forest, SVM, KNN, Decision Tree, and Logistic
Regression. Adware, Benign, Ransomware, SMS Malware, and Scareware are the five classes
that have been used for classification. The trials' results demonstrated the value and efficacy of
machine learning techniques in identifying malware, with these algorithms achieving 71%
accuracy. Keywords: Machine learning, ensemble learning, static and dynamic analysis,
multiple classifier systems, Android malware, and malware for the Android attack.

Many recent applications demand image transmission through the net in the same time trying
to keep the integrity and authenticity of these images till they reach destination. In this paper,
image verification is applied using lossless compression technique “Huffman” and
steganography methods and cryptographic technique “Rabin” are used to boost security. The
verification process includes encrypting specific text, compressing it then hiding the result in
selected places within the image. The system was tested based on PSNR with respect to the
size of images, and compression ratio.

In the light of committed efficacy of selenium nanoparticles in biomedical implementation, this
study used Selenium oxide nanoparticles(SeO2NPs) to report their antibacterial activity. The
synthesis of SeO2NPs is assured by characterization with XRD, and morphological characters
that were observed using SEM and TEM analysis. The crystalline nature of SeO2NPs is assured
by XRD analysis. SEM and TEM images show that SeO2 NPs are uniform and in spherical
shape of size 20-40 nm. SeO2NPs play a critical role in growth inhibition of Escherichia coli
and Staphylococcus epidermidis. Antibacterial activity of SeO2NPs showed by agar well
diffusion and minimum inhibitory concentration (MIC) tests. SeO2 NPs showed inhibition
zone about (23mm ) against E.coli and about (18) against Staphylococcus epidermidis.
SeO2NPs showed a MIC value 31.25 μg/mL against both isolates. In briefly, these results
suggest that SeO2NP can be candidates for supplements and antibacterial substitutes against
bacteria for topical use like dressing.

This research work explores the application of DuPont analysis as a powerful tool for
evaluating the financial performance of companies. DuPont analysis deconstructs return on
equity (ROI) into its constituent parts, namely, profitability, efficiency, and leverage, providing
a comprehensive understanding of what drives a company's performance. By dissecting ROI,
investors and analysts can identify strengths, weaknesses, and areas for improvement within a
company's financial structure and operations. The objective of this research is to examine the
methodology of DuPont analysis, its significance in financial analysis, and practical
applications in assessing the performance of three listed companies in the sewing industry. A
case study approach was implemented in this work, and data were acquired from the financial
sheets of the companies studied for seven years (2016-2022). The data were analyzed using
financial ratios embedded in DuPont approach and by descriptive statistical methods. The
financial analysis revealed that ICFC company generated the highest ROI compared to the
other companies studied.

This study was conducted in the Agriculture nursery in AlKhalis town from
September 2022 to April 2023, to estimated plant height, number of leaves, fresh and dry
weight of vegetative plant. Whereas the chlorophyll content of leaves were in labs of Science
College, University of Diyala, Baquba. The aim of this study was to conducted the effect of
spraying with water extract of hibiscus plant Hibiscus sabdariffa L. on chrysanthemum plant
Calendula officinalis L, in concentrations 0, 50 and 100 mg/L. by taking 50 grams of powder
of the calyx of hibiscus plant, and dissolving it in 500 ml of distilled water, then in a shaking
device for 30 minute, and then left for another 30 minute to settle, then filtered with gauze to
remove suspended materials, then centrifuge it at 300 cycles/minute for 15 minutes, then filtrate
was taken and concentrated using a rotary evaporator. The results show that the treatment of
100 mg/L gave insignificant values for plant length (10.7, 18.0, and 27.7 respectively).
Whereas the number of leaves were (4.3, 7.0, 27.7), and chlorophyll content, which reached
(15.8, 27.5, and 36.1) ml/L significant values. The fresh weight of plant (8.8, 19.7, and 27.7)
g/L, and the dry weight were (5.5, 10.6 and 16.3) were significant. This study addressed an
important topic in biological applications in the process of stimulating the growth and
productivity of medicinal economic and ornamental plants by using environmentally friendly
plant extracts available in local environment, which reduced dependence on the use of chemical
fertilizers and other manufactured materials.

This research aims at evaluating heavy metals concentrations in petroleum products. The heavy
metals, present in petroleum products sold in Anbar Governorate specifically Ramadi, were
analyzed. Motor Oil and diesel were obtained from the Anbar branch of the Petroleum Products
Distribution Company, while Gasoline and Kerosene were obtained from the old Ramadi Gas
Station. The samples were digested by using a mixture of sulfuric acid as well as nitric acid
and analyzed using an Atomic Absorption Spectrometer(AAS). The results showed that the
lead concentration values in all the petroleum products were higher than the permissible value,
with the highest value in kerosene reaching 2.6 mg/L and the lowest value in diesel fuel
reaching 1.153 mg/L. The zinc concentration values in motor fuel also exceeds the permissible
limits, reaching 6.585 mg/L. The nickel concentration values also slightly exceeds the
permissible limits, reaching 1.010 mg/L. In addition, the high levels of lead can be attributed
to two sources: anthropogenic like additives used during refining, absorption of metals from
storage tanks as well as supply vessels and natural like the existence of metals in the rocks of
the crude oil. In addition, such high level of pollution poses a serious environmental threat in
the vicinity where these products are used.

This work presents the design and modeling of a ZigBee transceiver system operating at a
frequency of 2.4 GHz. In addition, the system employs offset quadrature phase shift keying
(OQPSK) modulation to modify the pulses, employing a half-sine wave. This modifies the
range of the broadcast signal to align with the channel's bandwidth. This study aims to address
the issue of inter-symbol interference (ISI) and multipath disruption. The ZigBee wireless
sensor network is designed to meet the requirements of IEEE 802.15.4 standards, focusing on
facilitating short-range communications. This optimization aims to minimize costs, power
consumption, and data rate. The aspects listed above provide significant challenges for
technical progress aiming to achieve sufficient performance in real-time scenarios while
effectively managing a cost-effective bit error rate (BER). By utilizing DSSS as a
dissemination technique, the proposed system reduces the impact of noise while
simultaneously increasing the signal frequency and energy. The input signal is converted to
binary, enabling a maximum data rate of 250 kbps. The evaluation of the ratio between the Bit
Error Rate (BER) and Signal-to-Noise Ratio (SNR) for three distinct wireless channel models,
specifically Rician, AWGN, and Rayleigh, while considering the presence of multipath
received signals, offers significant insights on the system's performance during transmission
modes. The statistic known as the bit error rate (BER) holds significant importance in the
assessment of data security inside a digital communication system.. According to the findings,
AWGN has the lowest BER, whereas Rayleigh and Rician have the highest. A modest output
delay of 0.4 µs is associated with Rician, and its BER is reduced compared to AWGN and
Rayleigh.

COVID-19 is the infection cause by a corona virus called SARS – CoV -2. The WHO
documented first infection on 31 December 2019, in city of Wuhan in Hubei Province, China.
This disease affected a large number of people around the world. A lot of researchers study the
correlation among COVID-19 and many factors have been conduct since the start of the corona
including ABO blood groups.
This study included affected people with COVID-19 recorded in Baghdad to know the
relationships between COVID-19 infection and types of ABO groups. Methods, the presented
study collected (250) patient documented with COVID-19 in Al-Forat Hospital in Baghdad /
Iraq. The methods of Covid-19 testing done by using CT scans and RT-PCR, after that
detecting the type of ABO groups by making ABO test, also recorded the result of Rh factor.
Conclusion, Several groups taking in this study according to the type of ABO groups and
recorded a highest percentage of corona virus infection in type (A) blood groups and the
minimum percentages recorded in type (AB) of ABO groups. Also the ABO group's types (B)
and (O) showed variations in our investigations.

The unbalanced magnetic pull UMP is the resultant global magnetic force that acts on the rotor
due to an asymmetric magnetic field distribution in the air gap as broken rotor bars condition.
It can be computed by normally found during finite element analysis using Maxwell’s stress
method. In this paper, influence of the broken bars location upon the amplitudes of current
waveform is investigated. The stator current frequency spectrum, waveform flux density,
variations of torque for a faulted induction motor are obtained for all cases in which four broken
bars are distributed over poles of the motor. The torque frequency spectrum of faulted motor
has been obtained for various cases of bars breakage location.

The western desert in Iraq was classified as an arid area, with very little precipitation ranges
from 50 to 120 mm. Additionally, this area is characterized by a high evaporation rate ranging
from 1700 to 1900 mm/year. The Iraqi Western Desert is characterized by the abundance of
valleys that form a large streams for water movement during rainstorms. With an area of 16,550
Km2, Wadi Houran is considered the largest valleys not only in Anbar Governorate, but overall
Iraqi area. The annual water flow in this valley is about 200,000,000 m3/year. This research
aims to Study the validity of sustainable development of Wadi Horan by constructing a small
dams-series to harvest rainwater in reservoirs and to recharge groundwater to improve its
quality and quantity. Sustainable development aims can be defined as an environmental balance
of natural resources such as groundwater. This system creates eco-friendly oases and parks that
contributes to enhancing the local security in this border area. This research concludes the
possibility of cultivating many millions of drought-resistant trees within a sustainable nature
reserve park extending over an area of about 4000 km2 irrigated with rainwater harvesting and
groundwater pumped by renewable energy.

This article is part of the federal literature that examines the revival of the federalism and new
federal models’ formation and operation and their theoretical implication on classic federal
theory. This type of literature aims to update the classic federal theory in the sections of origin
of the federal states and the re-assessment of the prerequisites for successful operation. To do
so the new federal models rose after 1990 are the focal point. This article focuses on Iraq, and
provides an in-depth examination on one of its federalisation’s challenges. The operation of
the Iraqi federation has been very complicated due to constitutional and institutional
deficiencies. However, the federalisation of Iraq is further complicated by a different category
of challenges: “the operational challenges”. The internal displacement and forced migration is
one of the operational challenges that Iraqi federation is confronting, which this article seeks
to examine its implications on federalisation in the light of the Iraqi federal experiment.
Examining this challenge will contribute to the analytical reappraisal of the classic conditions
of success and failure in federal experiments. This implies that this challenge would add to
refine our understanding on the “pathologies” within the new federal models and the prospect
of adopting the federal example of governing in other countries.
This articles explain that development of the federal process is critically linked to trust building
process of the Iraqi citizens in the local and federal governments no in militia or tribal forces.
Trust is the essential component to more effective relationship among Iraqis and their
authorities.