Iraqi Journal of Science

Streptococcus pluranimalium was first isolated in 1999. Recently, several case
reports have been published that have revealed that S. pluranimalium can infect
humans as well. The pathogenicity and pathophysiology of this pathogen is poorly
studied and its characteristics are not well known. In this study, S. pluranimalium
was first isolated and then identified from infants and children who suffered from
upper respiratory infections. 90 samples were collected from nasopharyngeal cavity.
Among them, 83 Streptococcus spp. isolates were identified. 3 out of which were
biochemically and molecularly identified as S. pluranimalium. 16S rRNA
sequencing based identification revealed that all isolates showed a very close
identity match (92%) with subjected S. pluranimalium when blasted with gene bank
database. Furthermore, the antibiotic susceptibility of S. pluranimalium towards ten
antibiotics was conducted using Kirby-Bauer disk diffusion test. The results
revealed that S. pluranimalium was 100% susceptible to penicillin, levofloxacin, and
ofloxacin. However, other antibiotics showed diverse effects on S. pluranimalium.

Coronavirus 2 is the cause of coronavirus disease 2019 (COVID-19), which
leads to severe acute respiratory illness. Matrix metalloproteinases (MMPs) have
been linked to leukocyte infiltration and chemokine activation during inflammatory
responses. Tissue inhibitors of metalloproteinase (TIMP) family are thought to
dampen the proinflammatory effects of these MMPs. The molecular pathways of
lung fibrosis are mediated by MMPs and TIMPs. In this study, we sought to
investigate the probable link between MMPs, specifically MMP-3, TIMP-2, and
COVID-19. The study included 58 COVID-19 patients and 30 apparently healthy
individuals matched in terms of age and sex. Multiplex real- time PCR was used to
detect the ORF1ab, E, and N genes of SARS-Cov-2, ELISA was used to evaluate
the quantities of soluble MMP-3, TIMP-2, and C reactive protein in serum. The
results showed that the serum levels of MMP-3 and TIMP-2 were noticeably higher
in COVID-19 patients than healthy controls; which and was statistically significant
(p <0.001). Estimation of serum MMP-3 and the inhibitor TIMP-2 may have a
useful indication for COVID-19 diagnosis.

Methicillin resistant Staphylococcus aureus (MRSA) is the most common
pathogenic bacteria in the hospitals and communities, the ability to form biofilm is
considered the main cause of Staphylococcus pathogenicity since it provides
resistance to both antibiotics and host immune response, so this study was aimed to
evaluate the biofilms formation and its association with antibiotic resistance in
clinical isolates of MRSA, in order to achieve this aim, 237 samples were collected
from different patients with wounds infections after surgeries and samples from
operations galleries from varies hospitals in Baghdad ,68 isolates out of 237 were
subjected to Staphylococcus aureus according to conventional methods
Additionally, the S. aureus isolates were re-identified by molecular method. The
results for Susceptibility of 68 S.aureus isolates against 22 antimicrobial agents
revealed all isolates were resistant (100%) to Cefotaxime, and showed resistance to
Ceftriaxone, Oxacillin, Cefipime, Cefoxitin, ampicillin, Penicillin, Nalidixicacid,
erythromycin in percentage (99, 97,97,87, 87, 79, 75, 65 )% respectively while
other isolates showed variety in their resistant to other antimicrobial agents. while
all 68 isolates were sensitive to Nitrofurantoin which is considered the most
effective agent against the isolates. All 68 isolates were identified as MRSA on
HiCromeMeReSa Agar Base medium, but 66 among 68 isolates were methicillin
resistant in antibiotic sensitivity test, while 67 isolates had a positive reaction when
detecting mecA gene using Polymerase Chain Reaction (PCR) technique. The
finding of biofilm detection by microtiter plate method (MTPs) showed that 56 of 68
isolates produced biofilm in different degrees, while 66 (97%) among 68 isolates
possessed the icaAD gene using PCR.

The current study is an attempt to assess the cytogenotoxic potential of the
ethanolic extract from the leaves of Borago officinalis on Swiss albino male mice.
Young Swiss albino mice were orally administered with leaf ethanolic extract of
Borago officinalis. Three mice groups were used using different doses of plant
extract (T1: 100, T2: 200, and T3:400 mg\kg) in addition to the control negative
group (untreated mice) for 7 days to assess mitotic index or 28 days to assess
meiotic index. The results revealed that the extract significantly induced the
division of disruptive chromosomal changes in the bone marrow and the mean of
abnormality was (3.5±0.47, 4.43±0.83, and 5.83±0.96%) for T1, T2, and T3
respectively, as well as in primary spermatocytes. It is planned that the extract
might have interfered with the spindle protein or protein packing.

The creation and characterization of laser-generated plasma are affected by laser
irradiance, representing significant phenomena in many applications. The present
work studied the spectroscopy diagnostic of laser irradiance effect on Zn plasma
features created in the air by a Q-switched Nd: YAG laser at the fundamental
wavelength (1064nm). The major plasma parameters (electron temperature and
electron density) have been measured using the Boltzmann plot and the Stark
broadening methods. The value of electrons temperature ranged from 6138–6067 K,
and the electron density in the range of 1.4×1018 to 2×1018 cm-3, for laser irradiance
range from 2.1 to 4.8×108 (W/cm2). The McWhirter criterion for preserving a local
thermodynamic equilibrium (LTE) condition is confirmed in this study.
Furthermore, other fundamental plasma parameters, such as Debye length (λD),
number of particles in Debye sphere (ND), and plasma frequency (ωp), were
measured. We found that all plasma parameters are affected by laser intensity.

In this work, polyvinylpyrrolidone (PVP), multi-walled carbon nanotubes
(MWCNTs) nanocomposite was prepared and hybridized with Graphene (Gr) by the
solution casting method. The morphological and electrical properties were
investigated by field effect scanning electron microscopy (FESEM) images,
portraying a uniform dispersion of graphene within the PVP-MWCNT
nanocomposite. The AC conductivity increased from (1.45552) to (2.34812) (Ω cm)-
1 with the use of nanocomposite. The increasing continues for the AC conductivity
after hybridized with graphene up to (7.20641) (Ω cm)-1. In addition, the
performances of the prepared samples for gas sensor application have been
investigated. It was seen that the sensitivity analysis portrayed higher value for the
nanocomposite hybridized with Gr (S=2.2 and 5.4%) as compared to the pure
sample (MWCNTs). Finally, the recovery and response times were increased when
the temperature increased due to the increment of the adsorption of the gas that
resulted from the free electrons.

This research evaluates the optical properties of an inhomogeneous and nonparaxial
system using a solar ball lens (SBL) as a new thermal solar concentrated
collector. This evaluation is based on detecting a diacaustic curve in a
straightforward and accurate manner, with the diagnostic relying on image
processing as a computational tool using the MATLAB program rather than a
complicated numerical analytic procedure. The circle of least confusion (CLC) of
the (SBL), (Fluorinated ethylene propylene (FEP) polymer – water core), was
calculated. Furthermore, the study evaluated the maximum geometrical
concentration ratio (G C) of refracted solar radiation that can be captured by a
receiver of the (SBL). Without energy losses due to spherical aberration, the (G C)
ratio was (14.10) at (h/r) ratio, circular aperture radius to ball radius, around (0.6).
The investigation also revealed an aplanatic point for preventing the development of
optical envelope inside the solar ball lens at (h/r) equal to 0.8638, as well as a
maximum (h/r) value of 0.7351 for collecting solar radiation.

The bound radial wave functions of Cosh potential which are the solutions to the
radial part of Schrodinger equation are solved numerically and used to compute the
size radii; i.e., the root-mean square proton, neutron, charge and matter radii, ground
density distributions and elastic electron scattering charge form factors for nitrogen
isotopes 14,16,18,20,22N. The parameters of such potential for the isotopes under study
have been opted so as to regenerate the experimental last single nucleon binding
energies on Fermi's level and available experimental size radii as well.
PACS number(s): 21.10.Ft, 21.60.Cs, 21.10.Gv, 25.30.Bf

The reservoir characteristics of the Pre-Santonian Eze-Aku sandstone were
assessed using an integrated thin section petrography and SEM Back-Scattered
Electron (BSE) imaging methods. Fresh outcrop data were collected in the Afikpo
area (SE Nigeria). Twenty-eight representative samples from the different localities
were analysed to obtain mineralogical and petrographical datasets germane for
reservoir characterisation. Thin section petrography indicates that the sandstones are
medium-grained, have an average Q90F10L0 modal composition, and are classified as
mainly sub-arkose. The sandstones on SEM reveal the presence of cement in the
form of quartz overgrowths, authigenic clays and feldspar. From epoxy-stained thin
sections and/or SEM BSE image analysis, primary, secondary (inferred from partial
to total feldspar dissolution/alteration), and micro- (in authigenic clays) porosity
types were identified. Although the development of quartz overgrowths, authigenic
clay precipitation, and feldspar dissolution often affect reservoir properties of
sandstone negatively, the Eze-Aku sandstones still retained very good reservoir
properties (porosity, average 22.7 %; permeability, average 745.43 mD). This can be
attributed to the abundance of framework grains that have been stabilized by quartz
cement and relatively limited feldspar dissolution. The stabilized framework grains
help preserve reservoir characteristics and resist further compaction beyond
eogenetic depths. The feldspar dissolution produced silica and aluminium that was
precipitated to form the quartz overgrowths and the authigenic clays (e.g., kaolinite),
respectively. The relatively concurrent precipitation of silica and aluminium from
dissolution products reduces the quartz overgrowth quantity and authigenic clays that
could have adversely affected the reservoir characteristics.

Most marshes in Iraq face several challenges as aquatic environments, including
pollution by various chemical agents and heavy metals. The current study deal with
an analysis of the water quality of Dalmaj marsh as one of the closed aquatic
environments in the middle parts of Iraq located between latitudes 32ᵒ 05′ to 32ᵒ
23′N and longitudes 45ᵒ 10′ to 45ᵒ 38′ E. The marsh is suffering from a shortage in
water supply, especially during the summer. It will lead to a concentration of heavy
metals that are washed and transported to the marsh from the surrounding watersheds
through surface runoff. This work aims to analyze water and fish samples to assess
heavy metals and their accumulated risk in fish tissues based on many indices. The
16 samples of water and nine samples of fish are collected and analyzed for
concentration of heavy metals, i.e., Lead (Pb), Chromium (Cr), Nickel (Ni),
Cadmium (Cd), Copper (Cu), Zinc (Zn). The water analysis results indicate that
Chromium (Cr) only comes below the permissible limit in water. At the same time,
the composite heavy metals pollution index (HPI) identified that the water samples
are varied from light pollution to malignant pollution. Regarding fish samples, three
indices, i.e., BAF, EDI, and HI, are used to test the accumulated concentration of
heavy metals in fish tissues and to point out their risk to consumers. The results
indicate that Pb and Ni are the more hazardous metals accumulated in many fish
samples with increasing fish weight, while hazard index (HI) is an additive index of
all tested heavy metals, indicating concern risk from most fish samples. The study
recommends testing the marsh water pollution periodically.

The assignment of suitable sites for water harvesting techniques is a promoted
strategy to be introduced to the community, for handling the water scarcity and risk
due to floods. In the eastern part of Missan, water is always hampered due to the
limited availability during the drought, while floods frequently and intensely occur
in the wet season. This study aimed to choose the potential and suitable sites for
applied water harvesting system using remote sensing techniques and analytic
hierarchy process (AHP). Ali Al-Garbi city is divided into three watersheds (site1,
site2, and site3), which have been characterized by flash floods that produce high
quantities of runoff. The six parameters: slope, lineament density, drainage density,
soil texture, rainfall, and runoff. These factors are selected based on previous studies
to detect the potential zones of water harvesting system in the study area.Pairwise
comparison method consistency index, consistency ratio, and parametersweight is
evaluated. The result discovers that the highly probable zone is situated in the north
and north-eastern portions in watershed no.1 and watershed no.2, while watershed
no.3 located in the south portions. In contrast, the low to medium WH is situated in
the center and south portion in watershed no.1 and watershed no.2, whereas in
watershed no.3 located in the north.

Zubair Formation is the most productive reservoir in southern Iraq, which is
comprised of sandstones, interbedded with shale sequences and sometimes
carbonate rock. It is an important formation in the lower Cretaceous cycle in Iraq.
Rumaila oil field is the largest oil field in Iraq and the 6th in the world. Two wells
were studied for three depths, one in the southern Rumaila and the other in the north.
The study focused on light and heavy minerals in sand fractions and their
relationship with hydrocarbon assemblages. For the survey to be complete, the
sedimentological study of the cores was also conducted. This research aims to
determine the effect of the amount of heavy and light minerals on the generation and
production of oil in the reservoir layers. The sedimentological results were the
prevalence of sand for all depths, especially in Southern Rumaila. The sand ratio
ranged from 62% to 98%. The rate of heavy minerals in southern Rumaila was
greater than in Northern on average at 1.17%. Light minerals were the most in
Northern Rumaila up to 99.3% represented in quartz with a high percentage and a
little part of feldspar represented in orthoclase. Heavy minerals were represented in
Opaque (24%), zircon (27.6%), tourmaline (18%), rutile (11%), biotite (3%),
chlorite (3.6%), muscovite (3.6%), staurolite (2%) and hornblende (3.6%). The
proportion of quartz was the most in light minerals. The average of minerals is ultrastable,
and Opaque is the most dominant over the other minerals. Ultra-stable
minerals in the sand that contain hydrocarbon assemblage are an index to
mineralogical maturity for sandstone rocks. The SEM images showed deformations
in quartz grains due to the high energy; on the other hand, the roundness and
sphericity of the grains were evident, especially in Southern Rumaila sands.

The sequence in the upper part of the Balambo Formation is composed mainly of
limestone alternating with marly limestones and dark grey shale in the Bosheen
section (eastern Sulaymaniyah, northeastern Iraq) and has been studied in terms of
its rare earth element (REE) content. The REEs are very low compared to modern
marine sediments. They are depletion in LREEs, and enrichment in HREEs and
(La/Yb)N in the studied rocks, indicating that these sediments retained the REEs
pattern of marine waters. The negative Ce anomaly reflects direct sedimentation
from marine waters under anoxic conditions with the contribution of terrigenous
clays. The positive correlation of ΣREEs with Al, Ti, and Y, and the negative
correlation of ΣREEs with CaO, in addition to the variation in Y/Ho ratio, all may
indicate the presence of terrigenous fractions as the main source for REEs in the
studied strata. The REEs pattern of the upper part of the Balambo Formation mostly
shows original characteristics, some of which were modified by detrital input.
According to (La/Yb)N ratios, the sedimentation rate varied during the deposition of
the Balambo Formation in the function of its position along the continental margin.

Air pollution means the release of pollutants into the atmosphere, which are
harmful to human health and the planet as a whole. Almost all air pollutants come
from production and energy use. In the present work, an assessment of some heavy
metals, natural radioactivity and the quantity of dust fallen in three sites (Tessen,
Rahemawa, and Laylan) in Kirkuk Governorate, northern Iraq. Three dust samples
were collected from three locations (residential, commercial and industrial areas).
The collected samples were analyzed for Cd, Cr, Cu, Ni, Pb, Zn, and radioactivity
(Gamma rays). The studied heavy metals (Fe, Ni, Pb, and Zn) exceeded their limits
in the atmosphere due to the increase in the number of automobiles, which added
pollutants to the atmosphere through the fuel combustion in automobiles. The
industrial processes, especially the petroleum industry considered the most dominant
in Kirkuk Governorate, and anthropogenic activities also participated. Chromium
Cr, Cu and gamma-ray were within the acceptable limits according to the World
Nuclear Association (WNA).

Twenty sand samples were collected from the sand dunes of Missan fields,
Southeastern Iraq. Grain size distribution, mineralogical and chemical composition
were studied for the total, medium, and fine-size sand fractions. The grain size
analysis shows that the sand is the main component, followed by silt and trace of
clay. The predominant grain size of sand is 0.250 to 0.500 mm, which forms more
than 57.28 %, which indicates that these dunes were formed under the influence of
relatively strong winds and the sedimentary material is close to the source. The light
components are quartz, feldspar, and different rock fragments, while the heavy
mineral assemblages are composed of opaque minerals, chlorite, mica, and
amphiboles. Pyroxene and epidote are the common minerals, while zircon, garnet,
tourmaline, rutile, kyanite, and staurolite are in minor amounts. X-ray diffraction
(XRD) data reveals that the predominant non-clay minerals are quartz, calcite,
feldspar, and gypsum. While the dominant clay minerals are palygorskite and illite,
followed by kaolinite and the mixed layer of montmorillonite – chlorite. There is a
negative relationship between the percentage of heavy minerals and the grain size of
sand. Dunes are distinguished by a relatively high percentage of minerals derived
from intermediate and basic igneous rocks located in the Zagros belt, northern Iraq.
They also may be derived from local source formations, Injana and Mukdadiya in
the surrounding areas. The average geochemical components of sand as indicated by
X-ray fluorescence (XRF) are; SiO2 (61.36%), which is mainly represented by
quartz, CaO (14.08%) related to the presence of carbonate, SO3 (0.05%) is
represented by gypsum, Al2O3 (6.76 %) and alkalis (2.30%) reflect the presence of
the K-feldspar and clay minerals, Fe2O3 (3.2%) is attributed to the presence of
hematite, magnetite and limonite minerals. SiO2 is concentrated in a medium sand
size fraction, while the other oxides are concentrated in a fine sand size fraction.

The Euphrates River Basin in Iraq suffers from climate changes represented by
the scarcity of precipitation and the increase in temperatures, which is directly
reflected ce the discharge rates and the increase in total dissolved solids, and
consequently, the increase in the dissolved loads in the river. Four measurement
stations (Haditha, Ramadi, Fallujah, and Al-Hindiya) in the upper reach of the
Euphrates River were investigated. Available data were analyzed from 1970 to
2020 related to precipitation (mm) and temperatures (°C). The results showed a
clear decrease in precipitation rates over the years, while a clear increase in air
temperature rates was observed. The discharge rates decreased temporally and
spatially downstream as follows: 502, 383.7, 382.1, and 211.8 m³/s in Haditha,
Ramadi, Fallujah, and Al-Hindiya, respectively. The average total dissolved solids
(ppm) from 2005 to 2020 shows a gradual increase downstream, 698.8, 764.8, 833,
and 922.3 ppm. The dissolution load classification curves for 2005 to 2020 show an
increase in the downstream dissolved loads of 0.781, 0.786, 0.927, and 0.944
million tons/month in Haditha, Ramadi, Fallujah, and Al-Hindiya, respectively. It
reflects the increase in the dissolution process of basin materials cumulatively
downstream. It is recommended that careful management of the transmission of
pollutants of agricultural and anthropogenic activities outputs into the river without
any treatments for the downstream reaches will be required.

Recently, new generalizations have been presented for the hyponormal operators,
which are (N, k)-hyponormal operators and (h, M)-hyponormal operators. Some
properties of these concepts have also been proved, one of these properties is that the
product of two (N, k)-hyponormal operator is also (N, k)- hyponormal operator and
the product of two (h, M)-hyponormal operators is (h, M)-hyponormal operator. In
our research, we will reprove these properties by using the (,)-commuting operator
equations, in addition to that we will solve the (, )-commuting operator equations
for (N, k)-hyponormal operators and (h, M)-hyponormal operators.

In this research, we study the classical continuous Mixed optimal control vector
problem dominated by couple nonlinear elliptic PDEs. The existence theorem for the
unique state vector solution of the considered couple nonlinear elliptic PDEs for a
given continuous classical mixed control vector is stated and proved by applying the
Minty-Browder theorem under suitable conditions. Under suitable conditions, the
existence theorem of a classical continuous mixed optimal control vector associated
with the considered couple nonlinear elliptic PDEs is stated and proved.

The main goal of this paper is to introduce the higher derivatives multivalent
harmonic function class, which is defined by the general linear operator. As a result,
geometric properties such as coefficient estimation, convex combination, extreme
point, distortion theorem and convolution property are obtained. Finally, we show
that this class is invariant under the Bernandi-Libera-Livingston integral for
harmonic functions.

HIV is a leading cause of death, in particular, in Sub-Saharan Africa. In this paper,
a fractional differential system in vivo deterministic models for HIV dynamics is
presented and analyzed. The main roles played by different HIV treatment methods
are investigated using fractional optimal control theory. We use three treatment
regimens as system control variables to determine the best strategies for controlling
the infection. The optimality system is numerically solved using the fractional
Adams-Bashforth technique.

This paper presents an alternative method for developing effective embedded
optimized Runge-Kutta (RK) algorithms to solve oscillatory problems numerically.
The embedded scheme approach has algebraic orders of 5 and 4. By transforming
second-order ordinary differential equations (ODEs) into their first-order
counterpart, the suggested approach solves first-order ODEs. The amplification
error, phase-lag, and first derivative of the phase-lag are all nil in the embedded pair.
The alternative method’s absolute stability is demonstrated. The numerical tests are
conducted to demonstrate the effectiveness of the developed approach in comparison
to other RK approaches. The alternative approach outperforms the current RK
methods.

This paper proves the existence of face antimagic labeling for ( ( ))
( ) ( ( ) and ( )

In this article, the existence of thermal radiation with Copper- water nanofluid,
the effect of heat transfer in unsteady magnetohydrodynamics (MHD) squeezing
and suction-injection on the flow between parallel plates( porous medium) are
studied. Rosseland approximation and the radiation of heat flux are used to depict
the energy equation. The set of ordinary differential equations with boundary
conditions are analytically resolved by applying a new approach method (NAM).
The influences of thermal field and physical parameters on dimensionless flow field
have been displayed in tabular and graphs form. The presented results show that the
heat transfer coefficient is reduced by the thermal radiation coefficient increases and
the absolute values of the skin friction coefficients are enhanced with the magnetic
amplification parameter. Regularly, the present outcomes discern that the parameters
of the injection-suction coefficient are both the temperature and velocity profiles
decline.

In this paper, we define a new subclass of multivalent functions defined by
the generalized integral operator with negative coefficients in the open unit disk U.
We also give and study some interesting properties such as coefficient estimates,
subordination theorems and integral means inequalities by using the famous
Littlewood's subordination theorem. Finally, we conclude a type of inequalities that
is upper bound and lower bound for topology multivalent functions of all analytic
functions.

The main aim of this work is to investigate the existence and approximate
controllability of mild solutions of impulsive fractional nonlinear control system
with a nonsingular kernel in infinite dimensional space. Firstly, we set sufficient
conditions to demonstrate the existence and uniqueness of the mild solution of the
control system using the Banach fixed point theorem. Further, we prove the
approximate controllability of the control system using the sequence method

Diagnosing heart disease is one of the most challenging tasks that require highly
experienced cardiologists. However, in developing nations such as Ethiopia, there
are few cardiologists, and heart disease diagnosis is challenging. As an alternative
solution to cardiologists, this study proposed a more effective model for heart
disease detection by employing random forest and feature ranking (FR). FR
improves the performance of the random forest model on heart disease diagnosis.
FR ranks features based on their relative importance to the heart disease diagnosis
improving the performance of the random forest model on heart disease diagnosis.
This study investigates the effectiveness of the FR approach for feature selection on
a real-world clinical heart disease diagnosis dataset collected from the University of
California at Irvine (UCI) data repository. The simulation on the validation set
reveals that the FR is an effective approach for feature selection. The result shows
the random forest model as an effective method for heart disease diagnosis giving
98.53% accuracy.

The increasing amount of educational data has rapidly in the latest few years. The
Educational Data Mining (EDM) techniques are utilized to detect the valuable
pattern so that improves the educational process and to obtain high performance of
all educational elements. The proposed work contains three stages: preprocessing,
features selection, and an active classification stage. The dataset was collected using
EDM that had a lack in the label data, it contained 2050 records collected by using
questionnaires and by using the students’ academic records. There are twenty-five
features that were combined from the following five factors: (curriculum, teacher,
student, the environment of education, and the family). Active learning had been
utilized in the classification. Four techniques had been applied for classifying the
features: Random Forest (RF) algorithm, Label Propagation (LP), Logistic
Regression (LR), and Multilayer Perceptron (MLP). The accuracies of prediction
were 95.121%, 92.195%, 92.292%, and 93.951% respectively. Also, the RF
algorithm has been utilized for assorting the features depending on their importance.

In recent years, predicting heart disease has become one of the most demanding
tasks in medicine. In modern times, one person dies from heart disease every
minute. Within the field of healthcare, data science is critical for analyzing large
amounts of data. Because predicting heart disease is such a difficult task, it is
necessary to automate the process in order to prevent the dangers connected with it
and to assist health professionals in accurately and rapidly diagnosing heart disease.
In this article, an efficient machine learning-based diagnosis system has been
developed for the diagnosis of heart disease. The system is designed using machine
learning classifiers such as Support Vector Machine (SVM), Nave Bayes (NB), and
K-Nearest Neighbor (KNN). The proposed work depends on the UCI database from
the University of California, Irvine for the diagnosis of heart diseases. This dataset is
preprocessed before running the machine learning model to get better accuracy in
the classification of heart diseases. Furthermore, a 5-fold cross-validation operator
was employed to avoid identical values being selected throughout the model
learning and testing phase. The experimental results show that the Naive Bayes
algorithm has achieved the highest accuracy of 97% compared to other ML
algorithms implemented.

Intelligent systems can be used to build systems that simulate human behavior.
One such system is lip reading. Hence, lip reading is considered one of the hardest
problems in image analysis , and thus machine learning is used to solve this problem,
which achieves remarkable results, especially when using a deep neural network, in
which it dives deeply into the texture of any input. Microlearning is the new trend in
E-learning. It is based on small pieces of information to make the learning process
easier and more productive. In this paper, a proposed system for multi-layer lip
reading is presented. The proposed system is based on micro content (letters) to
achieve the lip reading process using deep learning and auto-correction models for
error detection and correction of the accumulated words s pelled by the lip reading
system.The proposed system was implemented on a proposed dataset gathered using
02 persons of different ages and genders. The model achieved 98% accuracy in
micro content recognition and 73.6% accuracy in accumulated word lip reading.

With the freedom offered by the Deep Web, people have the opportunity to
express themselves freely and discretely, and sadly, this is one of the reasons why
people carry out illicit activities there. In this work, a novel dataset for Dark Web
active domains known as crawler-DB is presented. To build the crawler-DB, the
Onion Routing Network (Tor) was sampled, and then a web crawler capable of
crawling into links was built. The link addresses that are gathered by the crawler are
then classified automatically into five classes. The algorithm built in this study
demonstrated good performance as it achieved an accuracy of 85%. A popular text
representation method was used with the proposed crawler-DB crossed by two
different supervised classifiers to facilitate the categorization of the Tor concealed
services. The results of the experiments conducted in this study show that using the
Term Frequency-Inverse Document Frequency (TF-IDF) word representation with a
linear support vector classifier achieves 91% of 5 folds cross-validation accuracy
when classifying a subset of illegal activities from crawler-DB, while the accuracy
of Naïve Bayes was 80.6%. The good performance of the linear SVC might support
potential tools to help the authorities in the detection of these activities. Moreover,
outcomes are expected to be significant in both practical and theoretical aspects, and
they may pave the way for further research.

A signature is a special identifier that confirms a person's identity and
distinguishes him or her from others. The main goal of this paper is to present a deep
study of the spatial density distribution method and the effect of a mass-based
segmentation algorithm on its performance while it is being used to recognize
handwritten signatures in an offline mode. The methodology of the algorithm is
based on dividing the image of the signature into tiles that reflect the shape and
geometry of the signature, and then extracting five spatial features from each of
these tiles. Features include the mass of each tile, the relative mean, and the relative
standard deviation for the vertical and horizontal projections of that tile. In the
classification stage, four measurements of the Euclidean distance were used. While
the accuracy rates for 4854 samples drawn from five different evaluated standard
datasets ranged from 92.24% to 100%.

Glaucoma is one of the most dangerous eye diseases. It occurs as a result of an
imbalance in the drainage and flow of the retinal fluid. Consequently, intraocular
pressure is generated, which is a significant risk factor for glaucoma. Intraocular
pressure causes progressive damage to the optic nerve head, thus leading to vision
loss in the advanced stages. Glaucoma does not give any signs of disease in the early
stages, so it is called "the Silent Thief of Sight". Therefore, early diagnosis and
treatment of retinal eye disease is extremely important to prevent vision loss. Many
articles aim to analyze fundus retinal images and diagnose glaucoma. This review
can be used as a guideline to help diagnose glaucoma. It presents 63 articles related
to the applications of fundus retinal analysis. Applications of the glaucomatous
image classification are improving fundus images by locating and segmenting the
optic disc, optic cup, fovea, and blood vessels. The study also presents datasets,
metrics, and parameters that indicate the changes in retina structure and the steps
and results for each paper.

Classification of network traffic is an important topic for network management,
traffic routing, safe traffic discrimination, and better service delivery. Traffic
examination is the entire process of examining traffic data, from intercepting traffic
data to discovering patterns, relationships, misconfigurations, and anomalies in a
network. Between them, traffic classification is a sub-domain of this field, the
purpose of which is to classify network traffic into predefined classes such as usual
or abnormal traffic and application type. Most Internet applications encrypt data
during traffic, and classifying encrypted data during traffic is not possible with
traditional methods. Statistical and intelligence methods can find and model traffic
patterns that can be categorized based on statistical characteristics. These methods
help determine the type of traffic and protect user privacy at the same time. To
classify encrypted traffic from end to end, this paper proposes using (XGboost)
algorithms, finding the highest parameters using Bayesian optimization, and
comparing the proposed model with machine learning algorithms (Nearest
Neighbor, Logistic Regression, Decision Trees, Naive Bayes, Multilayer Neural
Networks) to classify traffic from end to end. Network traffic has two
classifications: whether the traffic is encrypted or not, and the target application. The
research results showed the possibility of classifying dual and multiple traffic with
high accuracy. The proposed model has a higher classification accuracy than the
other models, and finding the optimal parameters increases the model accuracy.

E-learning has recently become of great importance, especially after the
emergence of the Corona pandemic, but e-learning has many disadvantages. In order
to preserve education, some universities have resorted to using blended learning.
Currently, the Ministry of Higher Education and Scientific Research in Iraq has
adopted e-learning in universities and schools, especially in scientific disciplines
that need laboratories and a spatial presence. In this work, we collected a dataset
based on 27 features and presented a model utilizing a support vector machine with
regression that was enhanced with the KNN method, which identifies factors that
have a substantial influence on the model for the type of education, whether blended
or traditional.
Furthermore, the dataset used was primarily focused on three key factors: personal
information, the impact of e-Learning platforms, and the influence of the Corona
virus. The attributes that were measured revealed that social status, computer skills,
and the basic platform gave the user enough tools to continue the learning process.
The size of the classrooms and laboratories that meet the health safety conditions is
the most significant. The goal of our work is to discover a model that predicts how
blended learning will be used during and after the coronavirus pandemic and to
produce a model with minimal errors.

The traveling salesman problem is addressed in this paper by introducing a
distributed multi-ant colony algorithm that is implemented on a Raspberry Pi cluster.
The implementation of a master and eight workers, each running on Raspberry Pi
nodes, is the central component of this novel technique. Each worker is responsible
for managing their own colony of ants, while the master coordinates
communications among workers’ nodes and assesses the most optimal approach. To
put the newly built cluster through its paces, several datasets of traveling salesman
problem are used to test the created cluster. The findings of the experiment indicate
that a single board computer cluster, which makes use of multi-ant colony algorithm,
is a viable alternative for distributed computing. This approach's extensibility
options are extensively discussed as well.

The Internet of Things (IoT) technology and smart systems are playing a major
role in the advanced developments in the world that take place nowadays, especially
in multiple privilege systems. There are many smart systems used in daily human
life to serve them and facilitate their tasks, such as alarm systems that work to
prevent unwanted events or face detection and recognition systems. The main idea
of this work is to capture live video using a connected Pi camera, save it, and unlock
the electric strike door in several ways; either automatically by displaying a live
video connected via USB webcam using a deep learning algorithm of facial
recognition and OpenCV or by RFID technology, as well as by detecting abnormal
entrance with a ringing buzzer. In addition, this system is made in Python language
and based on the Raspberry pi 4 B model that can be viewed and controlled by
connecting to a screen or Wi-Fi locally or publicly over the Internet from any other
smart device, such as a laptop or mobile phone, by installing the VNC application or
the remote desktop connection application. The results obtained showed the
efficiency and performance of this system through remote control to display, detect,
and identify the persons who are authorized to permit the electronic lock/unlock
door (E-Door) at a relatively low cost with the implementation of many functions in
real-time.

The entry time of the prayer in Islam is a prerequisite condition for performing
obligatory prayers, and prayer times to be performed in Islam coincides with the
time changes of the position of the sun. The elliptical and equatorial coordinates of
the sun were calculated for different latitudes. The prayer times for the city of
Baghdad were calculated at (latitude = 33.34º N, longitude = 44.43 E) with high
accuracy for the year 2021 AD. The results showed that all prayer times are affected
by latitude according to each region except (Dhuhr prayer( , it changes with the
change of the equation of time, because the equation of time does not depend on
latitude, but rather on the sun’s declination, which depends on date. We also made
improvements to the accuracy of calculating prayer times, where the disappearance
of evening twilight (Isha prayer) was calculated when the sun was below the western
horizon at an angle of (170 ) and for )Fajr prayer( at an angle of (180) below the
eastern horizon. Minutes were added to enable entering the time for )Dhuhr prayer(
(5 minutes) and )Asr prayer( (3 minutes).
The results show that the shadow of the meridian varies every day of the year from
one point to another on the surface of the globe, so it is non-existent if the sun is
perpendicular to the earth at the time of the meridian, and it has a specific length if
the latitude of the place exceeds the value (23.50) the Tropic of Cancer or the Tropic
of Capricorn), and its length increases as we move towards higher latitudes.
In addition, the results of our program were compared with the program of the
Islamic project for all prayer times for the cities of Baghdad and Mosul for one year,
and it showed a good match for the results, with a difference in some times and days
of no more than one minute due to the modifications we added to calculate the effect
of altitude above sea level. Practical observation was also conducted to check the
times of the Dhuhr, Asr and Maghrib prayers for several days during the year 2021
AD, and the results were identical with our theoretical results.

Analyses are the power point of GIS because GIS can process and analyze
different spatial and attribute data, leading to new results for supporting decision
makers. The research aims to study advanced hydrologic analyses for the western
part of Karbala province, Iraq. The hydrologic analysis is done based on where that
DEM creates from the field survey method. This analysis gives digital maps and
tables showing the region's main and minor hydrological properties, such as flow
direction, flow accumulation, stream order, stream to feature, basin, and watershed
maps. Also, it can be calculated as area, perimeter, lengths of streams, and numbers
of stream orders for the main watersheds that are effective in the study area. These
analyses are very important for making decisions in studying the hydrologic
properties of any region in Iraq, and the GIS technique saves time, cost, and effort.

Bilinear interpolation and use of perceptual color spaces (HSL, HSV, LAB, and
LUV) fusion techniques are presented to improve spatial and spectral characteristics
of the multispectral image that has a low resolution to match the high spatial
resolution of a panchromatic image for different satellites image data (Orbview-3
and Landsat-7) for the same region. The Signal-to-Noise Ratio (SNR) fidelity
criterion for achromatic information has been calculated, as well as the mean colorshifting
parameters that computed the ratio of chromatic information loss of the
RGB compound inside each pixel to evaluate the quality of the fused images. The
results showed the superiority of HSL color space to fuse images over the rest of the
spaces, as it recorded the highest SNR and the lowest mean color-shifting. The
quality of the fused images using Lab color space was not affected by the type of
intermediate algorithm used for XYZ space, unlike LUV color space. The XYZ
algorithm type affected the fused image results, which recorded the worst
consequences. It is noted that the computational time taken increased exponentially
with the difference in spatial resolution between the fused images.