Iraqi Journal of Science

Echinococcosis is a common parasitic disease in humans and ruminants; it is considered as a health and economic problem in most parts of the world. The present study aims to evaluate the in vitro and in vivo scolicidal effects of Psidium guajava extracts on the protoscolices from hydatid cysts of Echinococcus granulosus. Protoscolices were aseptically aspirated from the livers of naturally infected sheep. Various concentrations of the extract were used for 6-48hrs. Eosin staining (0.1%) was used to determine the viability of protoscolices. The findings showed that the extract at the concentrations of 100 mg/ml killed 100% protoscolices after 48 hrs. However, the concentrations of 75 and 50 mg/ml were not effective in killing the protoscolices after 48 hrs. of exposure. The results of this investigation demonstrated that P. guajava could be used as a natural source for the production of new scolicidal agents.

Five hundred nasal swabs were taken from normal medical staff and public in the city of Baghdad. Several identification parameters were used to recognize the bacterial isolates. S. aureus isolations form nasal swabs were identified using morphology and VITECK 2 system. Polymerase chain reaction (PCR) was employed to determine PVL (Panton–Valentine leukocidin ) gene in S. aureus. The data showed no significant evidence on the relationship between PVL gene presence and gender and age of the studied groups. There was no relation between the prevalence of PVL gene in the age groups of 21-30 years (p=0.328) and 31-40 years (p=0.682).
The results showed that 38.4% and 37.5% S. aureus isolates were isolated from nurses working at Baghdad Teaching Hospital and AL-Yarmouk Teaching Hospital, respectively, while, doctors, pharmacists, and radiology staff were negative (0.00%).
There was no significant difference between hospital staff and community in AL-Karkh (p=0.838) and in AL-Rusafa (p=0.118).

Preparation of nanoparticles is one of the important ways to increase the biological effectiveness of materials. There are several methods to prepare the polyhydroxybutyrate (PHB) nanoparticles. Here, a new method is used based on exposing PHB to ultrasound waves under variable pH conditions. In the present study, PHB was added to distilled water and pH was adjusted to 4 by HCl (1 N). The suspension was exposed to ultrasound waves at 4500 kh for 25 seconds. Then, pH was readjusted to 10 by NaoH (1N) and the mixture was incubated for 2 h at 21 oC. Finally, the pH was adjusted to 7 by HCl (1 N) and the mixture was incubated at 21 oC for 18 h. The characterization of the prepared nanoparticles was achieved by using atomic force microscopy (AFM), Fourier-transform infrared spectroscopy (FTIR), ultraviolet (UV) spectrophotometer, X-ray powder diffraction (XRD), and scanning electron microscopy (SEM). The results demonstrated the formation of nanoparticles, especially after examinations by SEM and AFM, which showed that the diameter of particles was between 22.9 and 73.95. The present study confirmed that the method of exposing PHB to gradient pH and high levels of ultrasonic waves could produce PHB nanoparticles.

Culex quinquefasciatus is an intermediate host of several human pathogens and serve as a vector of filariasis worldwide. Recently, there are increasing efforts to develop new and effective nanoparticles to control mosquito vectors. The green synthesis of ZnO-CuO nanoporous composite using Gum Arabic (Acacia senegalensis) was successfully carried out with Gum Arabic and the composite was characterized by UV-Visible, FTIR, and SEM/EDX techniques. Three different larval instars (1st, 2nd, and 3rd) of Culex quinquefasciatus were exposed to various concentrations (10, 20, 25 mg/l) of the ZnO-CuO nanocomposite for 24 h. The LC50 values for the 1st, 2nd, and 3rd instars were found to be 4.702, 5.459, and 5.459, respectively, while the LC90 values were 22.923, 33.922, and 33.922, respectively. The correlation coefficient values for the three instars were found to be 0.982, 0.941, and 0.941, respectively, and these indicate concentration-dependent larvicidal activity. The novel ZnO-CuO nanoporous composite could serve as a new nanolarvicide against the filariasis-transmitting vector.

PARP-1 is a protein enzyme with a major role in DNA repair that is overexpressed in many malignancies. It is correlated with susceptibility and metastasis to lymph nodes in gastric cancer (GC). The objective of the present investigation is to estimate PARP1 expression in patients with gastric cancer and detected if it could be used as a predictive marker. Furthermore, we aimed to find the correlation between PARP1 expression and clinicopathological parameters, such as gender, age, invasion depth, histopathological type, involvement of lymph nodes, grade, and stages of GC. This is a retrospective study from the period 2018-2020. Fifty randomly selected subjects (10 normal and 40 GC) were examined for formalin-fixed, paraffin-embedded blocks (FFPE) of stomach tissue . The diagnosis reports were collected from the Pathology Department of the Gastroenterology and Hepatology Teaching Hospital and some private hospitals in Baghdad, Iraq. Hematoxylin and eosin (H&E) and immunohistochemical (IHC) staining of PARP1 were applied for the histological sections. Statistical analysis was accomplished by SPSS system at P<0.05. There were significant differences between the patients and control groups in the expression level of PARP1. There were also significant correlations between PARP1 expression and each of the histopathological subtype, grade, invasion depth, involvement of lymph node, and stages in patients. However, non- significant associations were found between the expression and the age and gender of patients. These results indicate that PARP1 could be employed as a good prospective marker for gastric cancer.

The water quality index was used for the evaluation of the quality of water, as well its impacts on the rotifer abundance, in the Tigris River as it passes through Mishahda City, northern Baghdad. Five sites were selected and samples were collected during October 2019 to September 2020. It was noticed that the index values in most sites have exceeded the upper limits of river waters. The values ranged from 40 (Poor) to 45 (Marginal) in all sites. While, the values were from 42 (Poor) to 65 (Fair) during different seasons. As for drinking usages, the results demonstrated poor or undrinkable (31-40) water in all sites. Meanwhile, the values ranged from 39 (Poor) to 56 (Clear) in regard to seasons. The index values recorded for the purpose of Conservation of Aquatic Organisms ranged from 36 (Poor) to 66 (Fair) in the all sites, and 56 (Clear) to 69 (Fair) during different seasons. Twenty five rotifer species were recorded, including 11, 2, 1, 5, 2, 1, 2, and 1 species of Brachionidae, Euchlanidae, Gastropodidae, Lecanidae, Lapadellidae, Notomanatidae, Synchoetidae, and Trichotoidae, respectively. It is concluded that the water of the Tigris on Mishahda City is considered to be highly contaminated and not suitable for human consumption without the necessary treatment. It was also noticed that the population density of the rotifers community was affected by the river water quality. However, despite the presence of environmental pressures, the rotifers continued to reproduce and conserve.

The aim of this study was to evaluate the possibility of using Lactobacillus cells as a probiotic to treat some vaginal infections. For this purpose, thirty Lactobacillus isolates were collected from vaginal samples subjected to a screening program to investigate their antagonism abilities against four vaginosis species: Pseudomonas aeruginosa, Escherichia coli, Klebsiella pneumonia and Proteus spp. Eighteen isolates were selected from the primary screening (agar plug diffusion method) based on their ability to inhibit the growth of 4 indicators which then subjected to a secondary screening program with two methods: detection of bacteriocin activity and biofilm forming capacity. The isolate Lactobacillus IS30 was selected based on its high bacteriocin production as well as being biofilm producer. Further identification tests revealed that isolate IS30 was Lactobacillus crispatus. Optimization experiments revealed that MRS broth was the best medium for bacteriocin and biomass production with glucose and yeast extract as best carbon and nitrogen sources. The maximum production observed in optimized culture was 15.9 mg/mL and 40 AU/mL for biomass and bacteriocin production respectively, hence this medium was used in the preparation of the formula containing Lactobacillus IS30 cells. Study the probiotic properties demonstrated the capability of Lactobacillus crispatus IS30 cells to tolerate the high acidity with an ability to adhere to vaginal epithelial cells. Moreover, Lactobacillus crispatus IS30 showed ability to auto-aggregation (72.66%) and 58% of Pseudomonas co-aggregation percentage after 5 hours. Lactobacillus crispatus IS30 cells was successfully incorporated into a gel bases formula and results revealed that cells have kept their viability over 14 days with an ability to produce and releasing the bacteriocin. The formula was tested against P. aeruginosa and E. coli and results confirmed its activity on both species.

One of the most common forms of diabetes is Type-2 that occurs due to the failure of cells in recognizing and responding to insulin if not accurately treated. The aim of this work is to evaluate the relations of thyroid hormones, vitamins, and lipid peroxidation with the glycemic index in patients experiencing Type-2 diabetes. Some tests of biochemical parameters and vitamins were conducted on 35 patients experiencing Diabetes Mellitus (DM) and 35 healthy subjects. The results indicated the increase in the levels of MDA (3.86 ± 0.97 μmol/L), HbA1c (8.27 ± 1.66 %), FBS (198.34 ± 32.41 mg/dl) and TSH (5.67 ±0.34 mIU/L) in the blood of diabetic subjects in comparison to the controls at a P value lower than 0.05. These increases resulted in decreasing the levels of GSH (3.68 ± 1.21 μM/mL), T3 (0.91 ± 0.03 ng/ml), vitamin E (0.66 ± 0.15 mg/dl), T4 (3.67 ± 0.46 μg/dl), and vitamin D3 (16.78 ± 4.32 mg/L) in diabetic subjects at the same P value. The present study concludes that there is relationship between thyroid hormones and oxidative stress in type 2 diabetes mellitus. In addition, there is a negative correlation between the levels of vitamin E, D, and HbA1c. Therefore, diabetics should monitor their levels of thyroid hormones and vitamins E and D.

The purpose of this study was to measure the radon concentration of some dried fruit and grain samples which were consumed as a meal. This is performed by counting the alpha tracks emitted from radon by exposing the CR-39 detector. Measurements indicated that the highest concentration of radon in dried fruit samples was in dried coconut sample 69.89247 Bq/m3, and the lowest concentration of radon was in figs 50.40323 Bq/m3, while the highest concentration of radon was in grain samples in oats was 61.82796 Bq/m3, The lowest concentration of radon was in Iraqi bulgur was 48.3871 Bq/m3, These results are due to the type and characteristics of the soil. Also shows that the behavior of the surface exhalation rate is higher than the mass exhalation rate.The concentration of radon gas and the rate of exhalation of radon for samples of Dehydrated fruit and cereals are within the permissible global limit, and eating these foods will be healthy and safety for the public.

Computer Aided Designing Tools of Electron Lenses (CADTEL) is a software packages cares about design, compute and plot simultaneously of the objective and projector properties of electron magnetic lenses. The developments in CADTEL software leads to contain a large fields and methods, adding to previous publish in 2013. The current improvement is inserting of some important parameters which are the resolution and focusing parameters. These parameters are angular semi-angle (α), focusing power (β), resolution limit (δ), image rotation (θ), spherical aberration (Cs), defocus (ΔZ), wave aberration (Χwab), depth of field (Dfld), and depth of focus (Dfoc) at certain magnification conditions. Thus, user can easily compute and plot, according to relations and forms, the effect of these parameters at the lens properties of four magnification conditions; zero, infinite and finite (low and high) magnification modes. This work introduces a new development for CADTEL software which is an interactive visual interface in electromagnetic lenses.Whereas, it reflects a substantial reduction of time and resources desired for training new users and researchers in electron optics field. The results and curves representations appear with visual interfaces which are coded in visual basic programing language. In addition, the computations and figures which were plotted appeared that complete identification between these results which are obtained from CADTEL and that from other software’s and direct computations methods.

Hydrothermal technology has many advantages compared to other growth methods such as the availability of their simple equipment,catalyst-free growth,Environmental friendliness, less dangerous environmental, and low costs. Combine spinning method technology with Hydrothermal could improve the structural of ZnO NS by increasing the formation of ZnO NS due to influence of heat annealed treatments on the structure of ZnO NS. ZnONano-Sheets (NS)were prepared to employ hydrothermal process utilizing zinc acetate, that has the chemical composition (Zn (CH3CO2)2.2H2O),as a precursor. After preparing the material, it is deposited in two methods, the first being distillation of the material on the glass (S1),while the second method was using the spinning technique (S2).The spinning method showed better results than the other method.The synthesized ZnO NS were analyzed byscanning electron microscopy (SEM),X-ray diffraction (XRD) analysis and their optical properties have been characterized utilizingUV- absorption spectra.

In this work, the optical emission spectrum technique was used to analyze the optical emission spectrum of (CdO: Fe) plasma produced by laser Nd: YAG with a wavelength of (532) nm, a period of 10 ns, and a focal length of 10 cm in the energy range of (200-500) mJ. The electron temperature (Te) was determined using the method of line intensities ratio. Using the Saha-Boltzmann equation, the electron density (ne) was determined. Other plasma parameters such as plasma frequency (fp), Debye length (λD) and Debye number (ND) were also measured. The CdO: Fe (at a mixing ratio of X= 0.5.) plasma spectrum was observed for different energies. As a function of the laser energies, the changes in electron temperature and densities were studied. The value of the electron temperature, at X=0.5, was (0.420 - 1.160) eV for laser energy (200-500) mJ, respectively.

was studied by taking several different values for the constant α and fixing the other three variables β, c and d with the values 25.58, -0.7142857, and -1.142, respectively. The purpose of this paper is to know the values by which the system transforms from a steady state to a chaotic state under the initial conditions x, y, and z that equal -1.6, 0 and 1.6 respectively. It was found that when the value of α is equal to 0, the Chua system is in a steady state, and when the value of α is equal to 9.5 and the wave is sinusoidal, the system is in oscillation, and when α is equal 13.4 the system is in a Quasi-chaotic state, and finally the system turns to the chaotic state when the value of α equals 15.05.

An interpretative study of the two-dimensional seismic data of the Afaq area was conducted using the Petrel 2017 software. 2D seismic reflection sections are used to give a structural interpretation of Afaq structure based on synthetic seismogram and well log data. Three reflectors, Zubair, Yamama, and Gotina Formations, were selected. These reflectors are defined from well west kifl (wk-1), Where located adjacent to the study area. Structural maps of the Zubair, Yamama, and Gotnia formations are prepared and interpreted, including TWT maps, Average velocity maps, and depth maps. The studies concluded that the Afaq structure area does not contain main faults, but secondary faults with short and limited extensions. The structure of Afaq is a Monocline structure at Zubair and turns into a semi-structure (trap structure) at the Yamama and Gotnia formations. The study also showed that the structure of Afaq is plunging structure towards the east.

The Sargule Formation was deposited during the Middle Jurassic, representing one of the most important source rocks in Iraq and surrounding areas.
Jurassic successions are commonly exposed as an isolated patch at some eroded anticline’s cores and limbs in the High Folded Zone, Imbricate Zone, and Thrust Zones of northern Iraq. The Sargelu section is located in Sargelu village at Surdash anticline, while the Rania section is located in Rania city near Hanjira village at Shaweri anticline. Fieldwork in Rania and Sargelu Sections allow to divide Sargelu Formation lithostratigraphically into many subdivisions as follow:
The Sargelu Formation in the Rania section is about 40 m and can be divided into two lithologic units; the upper thin to medium bituminous limestone beds alternated with thin chert beds, and the lower thin to medium bituminous limestone beds alternated with fissile gray shale beds.
the The Sargelu section comprises 180m and is divided into three units; the upper unit consists of dark gray limestone beds and thin brownish-black of laminated shale. The middle unit includes dark chert alternated with dark gray bituminous limestone and brownish-black laminated shale. At the same time, the lower unit consists of dark gray bituminous limestone beds alternated with medium brownish-black laminated shale beds.

This study aims to set up a 3D static model to characterize and evaluate Mishrif Formation which represents the main reservoir in Buzurgan Oilfield, southern Iraq. Six wells have been selected to set up structural, facies and petrophysical models of Mishrif reservoir by using Petrel Software. The structural model has been built based on the structural contour map of the top of Mishrif Formation, which derived from seismic interpretation, and by using different static algorithms in Petrel Software. The structural model showed that the Buzurgan Oilfield represents an anticlinal fold with two domes north and south separated by a depression. The petrophysical model included the porosity model and water saturation model. The results of petrophysical models showed lateral and vertical variations in the porosity and water saturation characteristics of the Mishrif reservoir. The integration between the structural and petrophysical models illustrated that the main productive zones in Mishrif reservoir are MB21, MC1 and MC2 units.

This study aims to assess the formation evaluation of the Jeribe Formation in Hamrin oilfield. The present study involved four selected wells of (Early- Mid Miocene) Jeribe Formation in Hamrin structure-Allas field; HR-2, HR-8, HR-9, and HR-16 located North of Iraq. The work deals with the available data that includes the most required information to improve such studies. Techlog Software V.2015 was used to carry out a reliable calculation of petrophysical properties utilizing conventional logs to determine the reservoir characteristics (lithology, porosity, and saturation). The computed CPI (software resulted) based on log information divided the Jeribe reservoir into two reservoir units (Jr-1 and Jr-2) within the studied wells. The calculated effective porosity and water saturation revealed that the unit Jr-1 in Hamrin- Allas oil field contains hydrocarbons at wells HR-2 and HR-16. In contrast, unit Jr-2 was 100% water-saturated along the selected well depths at wells HR-2, HR-8, HR-9, and HR-16.

The depth conversion process is a significant task in seismic interpretation to hstlbatse the link between the seismic data in the time domain and the drilled wells in tehdepth domain. To promote the exploration and development of tehSubba oilfield, more accurate depth conversion is required. In this paper, three approaches of depth conversions: Models 1, 2, and 3 are applied from the simplest to the most complex on Nahr Umr Reservoir in Suba oilfield. This is to obtain the best approach, lehsstvt s ahss itst with the actual depth at well locations and good inter/extrapolation between or away from well controls. The results of these approaches, together with the uncertainty analysis provide a reliable velocity model and more accurate predicted depth that reduced the ambiguity of the subsurface. The uncertainty analysis reveals that Model 3 is considered a more practical and most accurate approach because it gives a minimized standard deviation value of 14 with less residual and error values. The uncertainty of the depth conversion and the standard deviation values is raised towards the eastern part of the field due to an increase in the dipping depth in this region that affects the depth conversion results.

In this paper, we introduce new concepts that relates to soft space based on work that was previously presented by researchers in this regard. First we give the definition of Soft Contraction Operator and some examples. After that we introduce the concepts of soft Picard iteration and soft Mann iteration processes. We also give some examples to illustrate them.
Many concepts in normed spaces have been generalized in soft normed spaces. One of the important concepts is the concept of stability of soft iteration in soft normed spaces. We discuss this concept by giving some lemmas that are used to prove some theorems about stability of soft iteration processes (with soft contraction operator) with soft Picard iteration procedure as well as soft Mann iteration procedure.

The main objective of this research is to study and to introduce a concept of strong fully stable Banach Γ-algebra modules related to an ideal.. Some properties and characterizations of full stability are studied

This work aims to introduce and to study a new kind of divisor graph which is called idempotent divisor graph, and it is denoted by . Two non-zero distinct vertices v1 and v2 are adjacent if and only if , for some non-unit idempotent element . We establish some fundamental properties of , as well as it’s connection with . We also study planarity of this graph.

In this work, the methods (Moments, Modified Moments, L-Moments, Percentile, Rank Set sampling and Maximum Likelihood) were used to estimate the reliability function and the two parameters ( ) of the Transmuted Pareto (TP) distribution. We use simulation to generate the required data from three cases this indicates sample size , and it replicates for the real value for parameters, for reliability times values we take ( ) ( ).
Results were compared by using mean square error (MSE), the result appears as follows :
The best methods are Modified Moments, Maximum likelihood and L-Moments in first case, second case and third case respectively.

This study aims to classify the critical points of functions with 4 variables and 8 parameters, we found the caustic for the certain function with the spreading of the critical points. Finally, as an application, we found the bifurcation solutions for the equation of sixth order with boundary conditions using the Lyapunov-Schmidt method in the variational case.

In this paper, we derive some subordination and superordination results for certain subclasses of p− valent analytic functions that defined by generalized Fox-wright functions using the principle of differential subordination, ----------producing best dominant univalent solutions. We have also derived inclusion relations and solved majorization problem.

The focus of this article is to add a new class of rank one of modified Quasi-Newton techniques to solve the problem of unconstrained optimization by updating the inverse Hessian matrix with an update of rank 1, where a diagonal matrix is the first component of the next inverse Hessian approximation, The inverse Hessian matrix is generated by the method proposed which is symmetric and it satisfies the condition of modified quasi-Newton, so the global convergence is retained. In addition, it is positive definite that guarantees the existence of the minimizer at every iteration of the objective function. We use the program MATLAB to solve an algorithm function to introduce the feasibility of the proposed procedure. Various numerical examples are given`.

This paper concerns with the state and proof the existence and uniqueness theorem of triple state vector solution (TSVS) for the triple nonlinear parabolic partial differential equations (TNPPDEs) ,and triple state vector equations (TSVEs), under suitable assumptions. when the continuous classical triple control vector (CCTCV) is given by using the method of Galerkin (MGA). The existence theorem of a continuous classical optimal triple control vector (CCTOCV) for the continuous classical optimal control governing by the TNPPDEs under suitable conditions is proved.

The linear instability and nonlinear stability analyses are performed for the model
of bidispersive local thermal non-equilibrium flow. The effect of local thermal nonequilibrium
on the onset of convection in a bidispersive porous medium of Darcy
type is investigated. The temperatures in the macropores and micropores are
allowed to be different. The effects of various interaction parameters on the stability
of the system are discussed. In particular, the effects of the porosity modified
conductivity ratio parameters, p  and s  , with the inter-phase momentum transfer
parameters 1  and 2  , on the onset of thermal Convection are also considered.
Furthermore, the nonlinear stability boundary is found to be below the linear
instability threshold. The numerical results are presented for free-free boundary
conditions.

Gangyong Lee, S. Tariq Rizvi, and Cosmin S. Roman studied Dual Rickart modules. The main purpose of this paper is to define strong dual Rickart module. Let M and N be R- modules , M is called N- strong dual Rickart module (or relatively sd-Rickart to N)which is denoted by M it is N-sd- Rickart if for every submodule A of M and every homomorphism f Hom (M , N) , f (A) is a direct summand of N. We prove that for an R- module M , if R is M-sd- Rickart , then every cyclic submodule of M is a direct summand . In particular, if M is projective, then M is Z-regular. We give various characterizations and basic properties of this type of modules.

In this research, we study the dynamics of one parameter family of meromorphic functions * ( ) ( ) +. Furthermore, we describe the nature of fixed points of the functions in ,and we explain the numbers of real fixed points depending on the critical point . So, we develop some necessary conditions for the convergence of the sequence * ( )+when .

Nowadays, the process of ontology learning for describing heterogeneous systems is an influential phenomenon to enhance the effectiveness of such systems using Social Network representation and Analysis (SNA). This paper presents a novel scenario for constructing adaptive architecture to develop community performance for heterogeneous communities as a case study. The crawling of the semantic webs is a new approach to create a huge data repository for classifying these communities. The architecture of the proposed system involves two cascading modules in achieving the ontology data, which is represented in Resource Description Framework (RDF) format. The proposed system improves the enhancement of these environments achieving both semantic web and SNA tools. Its contribution clearly appears on the community productions and skills developments. Python 3.9.0 platform was used for data pre-processing, feature extraction and clustering via Naïve Bayesian and support vector machine. Two case studies were conducted to test the accuracy rate of the proposed system. The accuracy rate for the case studies was (90.771%) and (90.1149 %) respectively, which is considered an affective precision when it is compared with the related scenario with the same data set.

Semantic segmentation is effective in numerous object classification tasks such as autonomous vehicles and scene understanding. With the advent in the deep learning domain, lots of efforts are seen in applying deep learning algorithms for semantic segmentation. Most of the algorithms gain the required accuracy while compromising on their storage and computational requirements. The work showcases the implementation of Convolutional Neural Network (CNN) using Discrete Cosine Transform (DCT), where DCT exhibit exceptional energy compaction properties. The proposed Adaptive Weight Wiener Filter (AWWF)rearranges the DCT coefficients by truncating the high frequency coefficients. AWWF-DCT model reinstate the convolutional layers giving modularity in the design using multi scale convolution block. The impact of selection of DCT coefficients in the proposed model is validated on the benchmark database as City Spaces. The same level of accuracy compared to the conventional algorithm is achieved using only 40 % of the DCT coefficients. Extensive experiments validate the advantages of adaptive DCT modeling of CNN in semantic segmentation and image classification.

Meerkat Clan Algorithm (MCA) is a nature-based metaheuristic algorithm which imitates the intelligent behavior of the meerkat animal. This paper presents an improvement on the MCA based on a chaotic map and crossover strategy (MCA-CC). These two strategies increase the diversification and intensification of the proposed algorithm and boost the searching ability to find more quality solutions. The 0-1 knapsack problem was solved by the basic MCA and the improved version of this algorithm (MCA-CC). The performance of these algorithms was tested on low and high dimensional problems. The experimental results demonstrate that the proposed algorithm had overcome the basic algorithm in terms of solution quality, speed and gained optimality with low dimensional problems. Furthermore, in high dimensional problems, it has competitive results in comparison with the other algorithms.

Internet of Vehicle (IoV) is one of the most basic branches of the Internet of Things (IoT), which provides many advantages for drivers and passengers to ensure safety and traffic efficiency. Most IoV applications are delay-sensitive and require resources for data storage and computation that cannot be afforded by vehicles. Thus, such tasks are always offloaded to more powerful nodes, like cloud or fog. Vehicular Fog Computing (VFC), which extends cloud computing and brings resources closer to the edge of the network, has the potential to reduce both traffic congestion and load on the cloud. Resources management and allocation process is very critical for satisfying both user and provider needs. However, the strategy of task offloading to fog node in constraints of energy and latency is still an open issue. Several research works have tackled the resource scheduling problem in the field of VFC; however, the recent studies have not carefully addressed the transmission path to the destination node, nor has it considered the energy consumption of vehicles. This paper aims to optimize the task offloading process in the VFC system in terms of latency and energy objectives while taking the deadline constraint into considerations by adopting a Multi-Objective Evolutionary Algorithm (MOEA). Four different execution/transmission models are proposed where vehicle resources are utilized for tasks execution and transmission, and the well-known Dijkstra's algorithm is adopted to find the minimum path between each two nodes. The simulation results show that the models which involve the vehicles in the transmission process have reduced the latency and the total energy for the VFC system significantly in comparison with other models and the current state of the art methods.

Agriculture improvement is a national economic issue that extremely depends on productivity. The explanation of disease detection in plants plays a significant role in the agriculture field. Accurate prediction of the plant disease can help treat the leaf as early as possible, which controls the economic loss. This paper aims to use the Image processing techniques with Convolutional Neural Network (CNN). It is one of the deep learning techniques to classify and detect plant leaf diseases. A publicly available Plant village dataset was used, which consists of 15 classes, including 12 diseases classes and 3 healthy classes. The data augmentation techniques have been used. In addition to dropout and weight regularization, which leads to good classification results by preventing the model from over fitting. The model was optimized with the Adam optimization technique. The obtained results in terms of performance were 98.08% in the testing stage and 99.24% in the training stage. Next, the baseline model was improved using early stopping, and the accuracy increased to 98.34% on the testing set and 99.64% on the training set. The substantial success rate makes it a valuable advisory method to detect and identify transparently.

In data mining and machine learning methods, it is traditionally assumed that training data, test data, and the data that will be processed in the future, should have the same feature space distribution. This is a condition that will not happen in the real world. In order to overcome this challenge, domain adaptation-based methods are used. One of the existing challenges in domain adaptation-based methods is to select the most efficient features so that they can also show the most efficiency in the destination database. In this paper, a new feature selection method based on deep reinforcement learning is proposed. In the proposed method, in order to select the best and most appropriate features, the essential policies in deep reinforcement learning are defined, and then the selection features are applied for training random forest, k-nearest neighborhood and support vector machine classifiers. The trained classifiers with the considered features are evaluated on the target database. The results are evaluated with the criteria of accuracy, sensitivity, positive and negative predictive rates in the classifiers. The achieved results show the superiority of the proposed method of feature selection when used in domain adaptation. By implementing the RF classifier on the VisDA-2018 database and the Syn2Real database, the classification accuracy in the feature selection of the proposed deep learning reinforcement has increased compared to the two-feature selection of Laplace monitoring and feature selection states. The classification sensitivity with the help of SVM classifier on the Syn2Real databases had the highest values in the feature selection state of the proposed deep learning reinforcement. The obtained number 100 is a positive predictive rate in the Syn2Real database with the help of SVM classifier and in the case of selecting the proposed feature, it indicates its superiority. The negative predictive rate in the Syn2Real database in the state of feature selection of the proposed deep reinforcement learning was 100%, which showed its superiority in comparison with 90.1% in the state of selecting the Laplace monitoring feature. Gmean in KNN classifier on the Syn2Real database has improved in the feature selection state of the proposed deep learning reinforcement in comparison to without feature selection state.

Speech encryption approaches are used to prevent eavesdropping, tracking, and other security concerns in speech communication. In this paper, a new cryptography algorithm is proposed to encrypt digital speech files. Initially, the digital speech files are rearranged as a cubic model with six sides to scatter speech data. Furthermore, each side is encrypted by random keys that are created by using two chaotic maps (Hénon and Gingerbread chaotic maps). Encryption for each side of the cube is achieved, using the based map vector that is generated randomly by using a simple random function. Map vector that consists of six bits, each bit refers to one of the specific chaotic maps that generate a random key to encrypt each face of the cube. Results show that the pseudo-random keys created by using chaotic maps for cryptographic speech file have an acceptable characteristic concerning randomness tests, which is confirmed in this paper by using five statistical tests. The final evaluation of the speech encryption algorithm is measured by using different quality metrics, and the results show that the algorithm can achieve resist encryption.

Multiple applications use offline handwritten signatures for human verification. This fact increases the need for building a computerized system for signature recognition and verification schemes to ensure the highest possible level of security from counterfeit signatures. This research is devoted to developing a system for offline signature verification based on a combination of local ridge features and other features obtained from applying two-level Haar wavelet transform. The proposed system involves many preprocessing steps that include a group of image processing techniques (including: many enhancement techniques, region of interest allocation, converting to a binary image, and Thinning). In feature extraction and analysis stages, a combination of local ridge features and other features obtained from the details of Haar wavelet subbands are extracted. Each wavelet sub-band image is fragmented into blocks with overlap and then the local features and wavelet energies are extracted from each block. Experiments were performed using a database of 600 signature prints collected from 100 persons, (i.e., 6 samples per person). The recognition accuracy of the system was the optimum (100%) using two decomposition levels. For verification purposes, the False Reject Rate for the system was (0.025%) while False Acceptable Rate was (0.03%) respectively.

This work aims to investigate the dependence of gravitational lensing properties on the lens redshift and source redshift.
The angular diameter distance hereafter referred to as ADD has been determined using two different numerical integral methods, Simpson's rule, and definite integral methods. Both of those two methods gave identical results. In addition, observational data of gravitational Lensing systems have been used to find the most probable value of lens redshift and source redshift. The result showed that the lens redshift and source redshift are more likely to occur in the ranges of zL=0.2-0.6 and zS=1-3, respectively.
Einstein radius and the critical surface mass density have been studied for those ranges of lens and source redshift. The result clearly showed that the redshifts and distances affect the lensing properties. This indicates that observations of gravitational lensing can be efficiently used to probe the distances and redshifts.

Cadastral map environment is directed, more than ever before, towards Artificial Intelligence use to produce fast and accurate maps and keep up with the huge population growth. The traditional approach currently in production of maps is expensive and effort-intensive in addition to be considered as highly time-consuming process. UAV-based cadastral mapping imagery that use automatic techniques are newly being exploited to accelerate the process of production or updating. The state-of-the-art intelligent algorithms are capable to extract land boundaries from images better than conventional techniques. This paper presents an automatic workflow of cadastral map production based on land boundary and automatic feature extraction from UAV-based imageries. The developed workflow involved four steps: (i) Flight planning and Ground Control Points (GCPs) observation, (ii) image pre-processing, (iii) image segmentation (iv) boundary detection and extraction (classification), (v) postprocessing, and (vi) accuracy assessment. The study area includes geometrical and affect spectral reflectivity (slums) covered by 206 images those captured using a quad-rotary UAV (DJI Phantom 4 pro). The mosaic image of the Area of Interest (AOI) was produced by following Structure from Motion /Multi-view Stereo (SfM-MVS) photogrammetry which covers 0.592 km2 ground area using pix4DMapper software. The Multi-Resolution Segmentation (MRS) algorithm was applied for object generation and later both spectral and geometrical information (area, brightness, border and the normalized digital surface model NDSM)) utilised to extract the boundaries by Object Based Image Analysis (OBIA) rule-based expert systems in eCognition software. The most exciting challenge in this AOI was buildings separation depending on number of buildings using the QGIS software. The accuracy assessment of the obtained results showed that 88% of the extracted boundaries were correct following automatic extraction routine when compared to manual digitizing. This approach can highly compensate time, efforts, and low accuracy outcomes from traditional surveying and manual registration approaches applied in Iraqi institutes nowadays. The presented approach can definitely help to speed up map production phase and keep pace up with population expansion and modern technologies.

The present research aims to measure concentration of lead Pb214 in soil using remote sensing and GIS, associated radiological hazards in Baghdad, Iraq. Concentration of specific radioactivity of radioactive elements was measured and analyzed naturally and artificially in 48 soil samples for separate sites from Baghdad, Iraq using crystalline spectroscopy to detect germanium. The average radioactivity concentrations of lead were found, as it was found to have varying values from one site to another, as most of them exceeded the international permissible limit, as the highest concentration was recorded at 180 Bq in the sample H28 in Waziriyah district. Battery Lab (1), and the lowest concentration value is 40Bq in (H4, H15, H45) which represents (Dora Expressway, Mansour Street, Fuel Express, and Mahmoudiya Road 2).
Remote sensing data techniques, and Global Positioning System (GPS) have been used to analyze the effect of the isotopic distribution of heavy bullets for the city of Baghdad. Using Geographic Information Systems (GIS), concentrations were measured and observed. Results of interpolation maps showed isotope of lead is concentrated in the center and west of Baghdad, and then graded with fewer values in other sites.

The rapid development of automation industries and technologies has shown
incredible prospects for transforming our homes into a smart home automation
system, which are more secure than a simple home. This paper proposes a home
application based on voice and text called the Automated Control and Monitoring
System (ASCM). This application can be utilized by both normal and visionimpaired
people by using with a mobile phone.
The application allows users to send voice commands through Google Assistant
installed on Android to control the appliances. They can also have complete
monitoring by logging onto the ThingSpeak dashboard, which displays a device
status indicator and sends alert messages in the event of danger. The NodeMCU
development board based on the ESP8266 and a combination of sensors, modules
and actuators were used to create a "control system" for home appliances based on
the Internet of Things (IoT). This work mitigates the challenges that faced the design
of smart homes based on (IoT). The control and monitoring system is using voice
without the need to use programming languages. As well as the automation process
is not only on / off but also querying the status of any device sensors. In addition,
this application dispenses with IFTTT(If-This-Then-that) services to send alert
messages because their number is limited during the month, compared to the alerts
provided by the Blynk app, which is unlimited. Mobile phones and robotic homes
will make life easier and more enjoyable for the elderly and differently abled people
who are unable to manually turn the items ON/OFF