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Iraqi Journal of Science

Volume: 64

Issue: 11

Publication Year: 2023

Publication Date: November 2023

Articles in This Issue

Pages 5462-6071

1

Synthesis, Characterization and Application of Calcium Ion-Imprinted Polymeric Solid-Phase Extraction and Pre-Concentration in Aqueous Solutions by Packed-Bed Columns

Pages: 5462-5475 English

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Abstract

In this work, calcium ions were determined by the addition to the allyl chloride monomer resulting from bulk polymerization formation. To acquire the highest adsorption capacity, molar ratios of the template, monomer, and cross-linking agent, as well as solvents and multiple monomers were investigated. Scanning Electron Microscopy (SEM) and Fourier Transform Infrared Spectroscopy (FTIR) were used to analyze the calcium ion polymer. The elution of calcium had a small effect on the surfaces of the three-dimensional network structure. Calcium (II) ions were successfully eluted using a mixture of methanol and acetic acid. The calcium adsorption capacities were 3.8145 and 9.01773 mol/g (Qmax), respectively. A Langmuir isotherm model follows calcium adsorption. Solid-phase extraction (SPE) syringes packed with ionic imprinted polymers (IIPs) were used to selectively separate and preconcentration the calcium (II) ion from aqueous solutions to determine the calcium ion by flame atomic absorption spectroscopy (FAAS).

Keywords

Molecularly imprinted polymer; calcium ion; allyl chloride monomers.

2

CFIA-ISNAG fluorimeter for the Determination of Bromhexine-HCl in Drugs via the Measurement Scattered Light at ± 90˚

Pages: 5476-5490 English

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Abstract

A precise, simple, and accurate continuous flow injection technique was used for the instantaneous estimation of bromhexine hydrochloride (BH-HCl) in tablet dosage form. The chemical and physical parameters of the reaction of BH-HCl with tetraphenylborate to produce a yellowish-white precipitate were determined using an ISNAG fluorimeter analyzer and diverging light at 90°. The calibration curve for BH-HCl was linear with correlation coefficients of 0.9994 and linearity percentage r2% = 99.87 over a concentration range of 0.01-20 mmol/L, L.O.D = 0.3610 μg/125μL (0.007 mmol/L), and RSD% less than 0.3% for 3 and 13 mmol/L (five replicates). This approach was efficiently used to estimate the levels of BH-HCl in two distinct pharmaceutical companies. When the newly developed method was compared with the turbidimetric method using a t-test and standard addition, it was discovered that there had not been any significant difference between the two approaches at the 95% level of confidence.

Keywords

Bromhexine hydrochloride Flow injection Scattered light Tetraphenylborate. turbidity

3

Serum Iron, Ferritin, Erythroferrone and their Inter-Correlation In Adult Cigarette Smokers: A Case-Control study

Pages: 5491-5500 English

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Abstract

Cigarette smoking is one of the leading causes of lung and blood cancers worldwide. A higher risk of pulmonary injury is associated with elevated lung iron and ferritin levels. Erythroferrone (ERFE) is a newly discovered tumor necrosis factor (TNF) superfamily member produced by erythroblasts during erythropoiesis. Eventually, it suppresses hepcidin during enhanced erythropoietic activity. The current study investigated the relationship between serum ferritin, iron, and erythroferrone concentrations among adult smokers. This study included 76 selected adult cigarette smokers and 48 healthy individuals (non-smokers) as a control group. The enzyme-linked immunosorbent assay (ELISA) and chemiluminescent immunoassay (CLIA) biochemical techniques were used to accurately measure serum iron, ferritin, and erythroferrone. Cigarette smokers (CS) had a mean age of 42.75±2.92 years, while healthy control (HC) subjects had a mean age of 37.36±2.7 years. The findings have shown a significant increase in serum iron, ferritin, and EREF levels in CS (119± 4.30, 131.1±6.58, and 75.02±2.09) compared with HC (98.67±7.84, 85.50±4.12, and 65.74±2.25) respectively. This study has shown a significant positive correlation between serum EREF (P=0.0072, r=0.4089) and the duration of smoking <20 years and a moderate association between serum iron (P=0.1907, r=0.4511) and the duration of smoking <40 years. For the first time, this outcome shows increased serum EREF and overexpression by erythroblasts in subjects associated with smoking habits, along with increased serum iron and ferritin
levels. An indicative correlation is found between EREF overexpression, iron overload, and hyperferritinemia with reference to the duration of smoking. The study also illustrates the interconnection between iron metabolism perturbations and ERFE overexpression induced by cigarette smoking.

Keywords

Cigarette smoking Duration of smoking Erythroferrone Ferritin Iron

4

Synthesis, Identification and Biological Study of New Pharmaceutical Model Based on Amino Acids with Some of Its Complexes

Pages: 5501-5516 English

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Abstract

The synthesis of the MBIB ligand by the reaction of the BIB ligand with methionine in 1:1 ratio, and the metal complexes with Ni(II), Cu(II), and Pt(IV) were described. All synthesized compounds were characterized using spectroscopic methods such as FT-IR, 1H NMR, UV-VIS, thermal analysis (TG and DSC), atomic absorption (AAS), elemental microanalysis (C.H.N.S), melting point (m.p.), magnetic susceptibility, molar conductivity measurements, and chloride content. All the complexes were electrolytes, and the suggested geometric shapes for the complexes were octahedral. The magnetic properties of the platinum complex were diamagnetic, while those of the nickel and copper complexes were paramagnetic. All synthesized compounds have good anti-biofilm properties against bacteria (Pseudomonas auroginosa, a gram-negative bacteria), except for C1(Ni), which is inactive against the same bacteria. In addition, the ligand was evaluated as an anti-cancer agent against human breast cancer (MCF-7), but its effectiveness has been shown to be less effective compared to metronidazole.

Keywords

Antibiofilm Boric acid methionine Metronidazole

5

Synthesis, Characterization, and Antioxidant Screening of Some New Azo Compounds Containing Pyrazole Moiety from Metoclopramide Drug

Pages: 5517-5524 English

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Abstract

In this work, some new pyrazole derivatives were prepared through the reaction of the diazonium salt of metoclopramide with acetylacetone to give 5-chloro-N-(2-(diethylamino)ethyl)-4-((2,4-dioxopentan-3-yl) diazenyl)-2-methoxybenzamide (1) in 80% yield. Compound 1 was then reacted with some hydrazine derivatives to afford the corresponding pyrazole derivatives in 75-93% yields. Some new azo compounds (6-10) were also prepared in 77-95% yields by treatment of the diazonium salt of metoclopramide with some phenol and aniline derivatives. The prepared compounds were characterized using FT-IR and 1H NMR spectroscopy. Some of these compounds were then tested to see how well they worked as antioxidants.

Keywords

Acetylacetone antioxidant Pyrazole

6

Novel Nano Zn+2-Compound from LA Ligand as an Acid-Base Indicator: Synthesis, Characterization, pH Sensor, and Fluorescent Study

Pages: 5525-5540 English

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Abstract

The main goal of our research is to synthesize a novel nano Zn+2 complex with the 8-(2-(dansyl chloride)azo)adenine (LA) ligand as a pH sensor because of its advantageous properties. The molecular formulas of the ligand and Zn+2-LA complex were confirmed by studying the elemental analyses (C.H.N.), spectral methods, XRD, and thermal analyses (TGA). The molar ratio of Zn+2-LA was studied as a ratio (1:2) (M:L). Through the survey in FT-IR and UV-Vis spectra, it was found that the complex has a tetrahedral geometry shape with a dark purple color (552 nm), obtained from a single molecule. The optimum concentration is 0.3 mM, pH = 5.5, and time = 0-3 hours, which in the studies followed Lambert-
Beer’s law. Linearity ranged from 0.025 to 0.4 mM for the Zn+2-LA complex, with a linear correlation coefficient of 0.9963. The detection limit was 0.0219 μg/mL, and the limit of quantification was 0.0663 μg/mL. LA could be used as a titration indicator of sodium hydroxide (NaOH) by oxalic acid (H2C2O4) with a maximum concentration of 0.1 M of H2C2O4. Finally, the characteristic fluorescence peaks of the solutions were identified at 462 nm and 554 nm for the ligand LA and its complex respectively, which were dependent on pH = 5.5 and at 1 minute. The type of emission fluorescence is ????∗ → ???? transition.

Keywords

Adenine azo ligand fluorescent pH sensors Zinc complexes.

7

The Effects of Alcoholic Extract of Ficus carica Leaves on Some Chemical and Microbiological Properties of Beef during Refrigerated Storage

Pages: 5541-5553 English

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Abstract

This study explored the preservative effects of the alcoholic leaves’ extract of Ficus carica plant on beef refrigerated for 15 days. Phytochemical analysis showed that the plant extract contained terpenoids, flavonoids, tannins, saponins, and alkaloids. Furthermore, the alcoholic extract of plants significantly reduced the total viable counts of psychrotrophic bacteria, pathogenic bacteria (Proteus, Salmonella typhimiurum, Escherichia coli, and Staphylococcus aureus), and yeasts (Candida kruse, Candida lambica, and Zygosaccharomyces) isolated from meat samples, particularly at 100 and 200 mg/ml concentrations.
The antioxidant activity of the extract was determined by using TBA and TVN values. The results showed that meat samples treated with 100 and 200 mg/ml of the alcoholic extract of F. carica had significantly lower TBA values (25, 0.24 mg/kg respectively) on day 5 which became 0.92, 0.53 mg/kg on day 15. Whereas the control values increased from 0.25 to 1.75 mg/kg on day 15,f ollowed by the TVN values of treatment meat samples with 100 and 200 mg/ml 5.57, 5.12 mg N/100 g meat respectively on day 5 which became 12.16, 10.65 mg N/ 100 g meat on day 15, while the TVN in control samples increased significantly (p < 0.05) from 7.35 to 15.76 mg N/100 g meat.
All results confirmed that the alcoholic extract of F. carica, which is rich in bioactive compounds is more effective as a natural antibacterial, antifungal and antioxidant, than synthetic antioxidants that maintain the quality of beef, compared to the control by reducing lipid oxidation and microbial growth at refrigeration temperatures, especially at 100 and 200 mg/ml concentrations of the plant extract.

Keywords

Ficus Carica; Antioxidant; Alcoholic extract; Meat; Antimicrobial

8

The Association of Age and Gender with the Histopathological Features among Thyroid Cancer Patients in Erbil City, Iraq: Clinical Analysis of 153 Cases

Pages: 5554-5563 English

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Abstract

Thyroid cancer (TC) is an increasingly prevalent malignancy throughout the world. It has long been recognized that the incidence of TC is higher in women which increases with age. However, the association of gender disparity and age with TC aggressiveness and outcomes are still controversial. The aim of this study was focused on the association of age and gender with histopathological characteristics in TC. Methods: 153 patients who met the criteria, were selected. The included cases were divided into four age groups (≤24 years, 25-44 years, 45-64 years, and ≥65 years). Demographic, age and pathological parameters were compared among them. The association of gender and age with histopathological features were then evaluated. Results: Females were significantly more frequent in almost all age groups with the highest female frequency found the age group of 25-44 years old. Females are more susceptible for TC even when they are young. The four groups showed highly significant differences regarding extrathyroidal extension (ETE) which is more aggressive in older individuals’ tumor. However, there were no significant differences regarding tumor size, multifocality, LV invasion and LN metastasis. Moreover, increasing age was significantly associated with increases risk of ETE. In addition, old patients and males were significantly more likely to have larger tumor size. Nonetheless, both gender and age non-significantly associated with multifocality and LV invasion. Conclusion: Our results confirmed that increasing age could really exert a negative prognostic effect, at least in terms of ETE risk and larger tumor size. In addition, TC risk in females was more frequent in all age groups and significantly more likely than men to present at younger, nonetheless, males represented larger tumor size.

Keywords

age Extrathyroidal extension Gender disparity Histopathological features Thyroid cancer Tumor size

9

Gene Polymorphism of Human Lymphotoxin Alpha in Iraqi Breast Cancer Women

Pages: 5564-5571 English

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Abstract

The lymphotoxin alpha is a highly polymorphic gene and any genetic variation in it may lead to an increased production of cytokine LTA thus helping tumor development and progression. The aim of this work was to investigate the association of LTA polymorphism with the risk of breast cancer among Iraqi women. The findings of this study demonstrated that the age group > 50 years old formed 52% of the breast cancer patients (P <0.001). Hardy–Weinberg equilibrium analysis revealed that genotype frequencies of most SNPs in BC patients and HC were consistent with HWE. No association was found between LTA polymorphisms and BC. Moreover, seven haplotypes were detected in BC group. However, only one of them developed significant increase; T -A -C -C -G -C –G (0.20 vs. 0.04, OR: 5.931, P = 0.015). Markedly, some SNPs were in a strong LD, while others showed weak or no LD. We can conclude that an insignificant association was found between LTA polymorphisms and breast cancer in Iraqi women.

Keywords

Breast Cancer haplotype Iraq LTA Polymorphism

10

Effect of a Ketogenic Diet on Some Biochemical Parameters in Obese People

Pages: 5572-5579 English

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Abstract

This study examined the effects of a few biochemical variables on obese Iraqi males and females with a 30.5 body mass index (BMI) when they were fed a ketogenic diet. The present study demonstrates how an individual who follows a ketogenic diet has an increase in low-density lipoprotein (LDL-cholesterol). This research's objective was to assess the levels of some biochemical variables in obese people who were eating a ketogenic diet. Following 35 days on a ketogenic diet, the results show a significantly higher P ≤ 0.05 level of low-density lipoprotein (LDL) and total cholesterol (TC). Additionally, insulin, fasting blood sugar (FBS), cortisol, HOMA-IR, urea, BMI, and creatinine all show a considerable reduction, P ≤ 0.05.

Keywords

Biochemical parameters Ketogenic diet Lipid profile

11

The Potential Regulatory Role of miR-378 in the Expression of Bone Morphogenetic Protein-15 in Infertile Women with Hyperprolactinemia (HPL)

Pages: 5580-5590 English

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Abstract

The aim of this study is to investigate the relationship between microRNA 378 and BMP15 gene expression levels in blood samples collected from 50 healthy fertile females as controls and 50 hyperprolactinemia infertile females by quantitative real-time polymerase chain reaction (RT-qPCR). Specific primers were designed for this purpose based on the sequences of microRNA 378 and BMP15 retrieved from NCBI and designed by primer 3 software. The result assessing the expression level of BMP15 in hyperprolactinemia (HPL) was 0.220, while the control group's fold change value was 1.000. The HPL group showed downregulation in the expression of the BMP15 gene. While the fold expression values of the miRNA378 gene in the hyperprolactinemia (HPL) group were 2.227 and the control group's mean value was 1.000, the HPL group showed up-regulation in the expression of the miRNA378 gene. The results of the study revealed that miR-378 has directly regulated BMP15 gene expression; based on this, BMP15 gene expression was obviously decreased. Therefore, the expression level of BMP15 was negatively correlated with miR-378 expression.

Keywords

BMP15 gene gene expression HPL. miRNA-378

12

Molecular Analysis of Bacterial Meningitis in Suspected Cases

Pages: 5591-5603 English

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Abstract

One hundred and seventy-six cases of suspected meningitis (SMN) were included in a cross-sectional study. Their ages ranged from less than 1 year to 80 years, of whom 44.3% were male. The aim was to assess bacterial meningitis (BMN) in terms of incidence and types of causative bacteria. Cerebrospinal fluid (CSF) specimens were collected and polymerase chain reaction (PCR) analysis was conducted with universal primers designed to amplify a DNA fragment (996 bp) of the 16S rRNA gene of eubacteria. Resolving PCR products in agarose-gel electrophoresis revealed that 37.5% of CSF specimens were PCR positive, while 62.5% of CSF specimens showed no band and were considered PCR-negative. Eighty percent of the latter specimens were noted to have pleocytosis, in addition to having protein and/or glucose concentrations lower or higher than those in the normal range (abnormal CSF). The remaining 20.0% of CSF specimens were considered normal regarding pleocytosis, protein, and glucose (normal CSF). When the amplified DNA of PCR-positive specimens was subjected to sequencing and alignment with reference sequences, both Gram-negative (GN) and Gram-positive (GP) bacteria were identified (23 and 9 types, respectively). Acinetobacter spp. and Pseudomonas spp. were the most common GN bacteria (each with 17.8%), while Staphylococcus spp. was the most common GP bacteria (43.75%). The study concluded that BMN presents an important public health challenge, and PCR analysis of the CSF was an effective method for diagnosing pathogenic bacteria in SMN. In addition, leukocytes, glucose, and protein are valuable CSF parameters that may aid in the diagnosis of BMN.

Keywords

Cerebrospinal fluid glucose Leukocytes polymerase chain reaction. Protein Suspected meningitis

13

The Effect of Sildenafil on Adenine-Induced Chronic Kidney Disease in Mice

Pages: 5604-5614 English

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Abstract

This study was done to find the potential renal protective effects of sildenafil and its underlying mechanisms in mice with adenine-induced CKD. For the experiment, 40 male mice were split into four groups. The control group (A) received the same food without medication until the research ends, while the other three collections (B, C, and D) were given adenine (0.25% w/w in feed daily for 8 weeks), groups (C and D) were given sildenafil (0.5 and 2.5 mg/kg) respectively orally every day for 30 days, and then blood samples were taken to assess the function of the kidneys (Urea, total protein, and creatinine), total antioxidant capacity (TAC), superoxide dismutase (SOD), and catalase (CAT) in addition to kidney histopathology, as well as body and kidney weight. Administration of adenine caused weight loss, increased TAC, SOD, and CAT, and increased plasma concentrations of urea, total protein, and creatinine. Damage-related renal histopathological indicators (fibrosis and inflammation) were considerably elevated by adenine. Most of the aforementioned metrics improved with sildenafil, indicating that it might be utilized as an adjuvant treatment for CKD in people through antioxidant, anti-inflammatory, and anti-apoptotic mechanisms.

Keywords

adenine Albino mice antioxidant histopathology. nephroprotective sildenafil

14

The Correlation Study between TP53 Gene Expression and Acute Myeloid Leukemia in Iraq

Pages: 5615-5623 English

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Abstract

Acute myeloid leukemia represents the most prevalent type of acute leukemia in adults .Mutations in the tumor protein (TP53) gene have been found in more than half of all human cancers. This study was done to investigate the relationship between TP53 gene expression and the appearance and progression of acute myeloid leukemia in Iraq. This study included 100 subjects, divided into 60 patients suffering from pre-diagnostic acute myeloid leukemia and 40 healthy individuals. The difference in TP53 gene expression between acute myeloid leukemia patients and healthy individuals has been investigated, and the gene expression of TP53 has been measured after extraction of total RNA at concentrations (15–83 ng/μl) and purity (1.76-2). Gene expression has involved calculating the double ΔCt value to assess TP53 expression in the presence of the GAPDH gene as a reference gene. Results showed that gene expression folding (2-ΔΔCt) reflects significant differences in TP53 gene expression. There was overexpression (up-regulation) of the TP53 gene in acute myeloid leukemia patients (mean ± SD: 2.29±2.12) compared with controls (1 ± 0.43), with a p=0.04.

Keywords

acute myeloid leukemia gene expression Qpcr Tumor protein 53(TP53).

15

Antibacterial Activity of Live Cells of Lactobacillus Plantarum L40 as A Probiotic Against Pathogens Associated with Diabetic Foot Infections

Pages: 5624-5639 English

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Abstract

The present study was designed to select a suitable isolate of Lactobacillus sp. in order to use it as a probiotic formula for treating diabetic foot ulcer disease in diabetic mellitus patients. In order to determine the inhibitory action, 240 isolates of Lactobacillus from different sources, were taken and exposed for screening tests to evaluate the (antagonism-activities) toward 4 multi-drug resistant foot ulcer pathogens which were chosen from 120 pathogenic isolates: Staphylococcus aureus, Klebsiella pneumonia, Proteus mirabilis, and P. aeruginosa. Twenty Lactobacillus isolates were selected from primary screening according to the capacity to restrain its expansion of four markers, that were exposed toward second screenings to detect their ability to produce a high amount of bacteriocin. Based on the results, the isolate Lactobacillus L40 was selected as the highest bacteriocin producing isolate which was further characterized as Lactobacillus plantarum Next, several tests were performed to study the properties of L. plantarum L40, in particular its biosafety and its suitability to be a successful probiotic. Results showed that L. plantarum was resistant to cephalosporin groups such as ceftriaxone and cefepime whereas, it was sensitive to amikacin and chloramphenicol. In addition, results revealed that this bacterium was strongly adherent and a good biofilm producer; had high auto-aggregation capability and a high ability to adhere with S. Staphylococcus aureus, Klebsiella pneumonia, Proteus mirabilis and P. aeruginosa. A gel formula containing live cells of L. plantarum L40 was prepared and based on the results, cells were successfully survived in this formula over 18 days. Therefore, it was selected to be utilized as a vector to store and transport viable cells of L. plantarum L40. This gel formula showed antibacterial activity by inhibiting Staphylococcus aureus, Klebsiella pneumonia, Proteus mirabilis, and P. aeruginosa growth. The results showed the possibility of using viable cells of bacteriocin-producing Lactobacillus plantarum as an effective probiotic to deal with some skin pathogens, and hence treat skin diseases such as diabetic foot ulcer disease.

Keywords

Diabetic foot ulcer formula. Lactobacillus plantarum probiotic

16

Biodisintegration of human mucin protein by protease produced from Escherichia coli AJ55 isolated from Urinary Tract Infection of Iraqi pa-tients

Pages: 5640-5653 English

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Abstract

Proteases have various applications in the food, pharmaceutical, medicine, path-ogenicity of some pathogenic bacteria, and detergent sectors as well as meeting the needs of approximately 60% of the global enzyme industry, whereas they catalyze the breakdown of protein molecules into peptides and amino acids. Production and purification of protease enzyme by the isolate Escherichia coli AJ55 was scrutinized in the present study. Cultivation optimum conditions, were various complex medi-um, carbon source, nitrogen source, temperature, pH of the medium, and time of in-cubation were optimized to enhance the total protease production in shake flask cul-ture of E.coli AJ55. The nutrient broth supplemented with 2% glucose and 2% yeast extract, with a pH of 7.0 and incubated at 37 °C for 24 hours, better conditioned for producing the maximum production of protease. Escherichia coli AJ55 proteolytic enzyme was separated and purified using ion-exchange chromatography on a DE-AE-Cellulose column and Sephadex G-150 gel after being precipitated with 0-70% saturated ammonium sulfate. Protease that had been partially purified had a yield of 34%, a purification fold of 13.4, an activity of 12.16 U/ml, a protein concentration of 0.005 mg/ml, and a specific activity of 2432 U/mg. By using gel filtration chro-matography on a Sephadex G-150 gel, partially purified protease was examined for its ability to cleave the mucin protein. The findings of mucin biodegradation showed that the five fractions of the small peptides were produced after treatment of mucin with partially purified protease.

Keywords

Cleavage Mucin optimum conditions purification

17

Study of Optical, Structural and Morphology Properties of Tin Oxide Nanoparticles by Pulse Laser Ablation and its Effect on Bacteria Staphylococcus aureus

Pages: 5654-5664 English

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Abstract

Tin oxide (Sn) nanoparticles were prepared by pulsed laser ablation (PLA) method at different laser energies (400-700mJ). (UV, XRD, AFM, SEM, EDS) methods were employed to determine the properties of nanomaterials. The optical properties showed that the energy gap decreased with increasing laser power; the structural properties showed the relationship between density and angle; Miller's coefficients for net angles were determined and the morphology properties showed the element's surface shape and surface roughness. Also, Tin oxide nanoparticles with added to Staphylococcus aureus bacteria isolated from the ear and cultured by striking method on nutrient agar to know the effect of tin oxide nanoparticles on the growth of this bacteria. The results showed that tin (Sn) oxide nanoparticles had a role in decreasing the growth of bacteria on cultured media using the laser energies of (400mJ, 500mJ and 600mJ), but at an energy of 700mJ a clear zone (no growth) of bacteria on cultured media was noted, indicating 100% bacterial killing.

Keywords

Nanoparticles (NPs) Pulse laser ablation (PLA) Staphylococcus aureus bacteria. Tin (Sn) oxide

18

A Review of Biosensors; Definition, Classification, Properties, and Applications

Pages: 5665-5690 English

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Abstract

Biosensor is defined as a device that transforms the interactions between bioreceptors and analytes into a logical signal proportional to the reactants' concentration. Biosensors have different applications that aim primarily to detect diseases, medicines, food safety, the proportion of toxins in water, and other applications that ensure the safety and health of the organism. The main challenge of biosensors is represented in the difficulty of obtaining sensors with accuracy, specific sensitivity, and repeatability for each use of the patient so that they give reliable results. The rapid diversification in biosensors is due to the accuracy of the techniques and materials used in the manufacturing process and the interrelationships in scientific research between various disciplines, i.e., physics and biology, engineering and biology. This research aims to define biosensors in general, classify them and show their most important applications, with a brief description of their time development and the reason for their speared in all fields.

Keywords

Biosensor Flavin Dinucleotide food safety glucose Organism Redox Sol-gel‏.‏

19

Landslides Study in Bac Can Province, Vietnam by Analytic Hierarchy Process Method

Pages: 5691-5706 English

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Abstract

In recent years, landslides in mountainous provinces have been increasing. Whenever the rainy season comes, landslides occur, causing casualties to people and the infrastructure. Bac Can, which has suffered significant damage from landslides, is a mountainous province in the north of Vietnam. This study introduces the applying the analytic hierarchy process (AHP) to study landslides in Bac Can province, Vietnam. Currently, the earth's temperature is rising, and natural and anthropogenic hazards in the mountain are causing hazards. Integrate elements of the DEM model with component maps and different precipitation scenarios as the basis for the author to issue landslide warnings under the climate change scenario with maximum day rain rainfall for 2025 and 2050.

Keywords

APH Bac Can Landslide Landslide hazard index Vietnam

20

Salt Eruptions and Their Role in the Shaping of the Oil Trapping for Selected Fields in Eastern Iraq

Pages: 5707-5715 English

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Abstract

This research had been achieved using 2D seismic sections to study the presence of subsurface salty bodies in the Khashim Al-Ahmer, Galabat, Injana fields as a case study. The selected oil fields is located to the northeast of Baquba city within Diyala Governorate.
The study aims to determine the salt accumulations of the selected fields and their role in the formation of oil traps.
The interpretation of seismic data was focused on two reflectors Fatha and Jeribe Formations which belong to the lower and Middle Miocene. Structurally, Two systems of reversal faults are affecting the fields, according to seismic sections, the first represents thrust faults affected on the top part of Fatha (Red Beds & Seepage) and the layers above with large displacements and trending in an NW-SE orientation; The separation surface of these faults is the salt bed in the Fatha Formation. the second represents reversal faults affected on the lower section of Fatha (Transition beds) and the layers beneath with high displacements.
The research concludes Petroleum flow from the source was directed by the faults created by the broad Zagros tectonism to Miocene and younger traps, also seal fracturing exceeds vertical petroleum flow. The differences in fault types are caused by the presence of a salt bed within the Fatha Formation and the high variation in its thickness at the crest and flanks. So, the main recommendation of research is to implement a 3D seismic survey covering these fields to determine salt body areas.

Keywords

Diyala Hamrin anticline oil trapping Salt eruptions structure

21

Effects of Land Uses on Soil Quality of Shwan Sub-basin, Kirkuk Governorate, Northern Iraq

Pages: 5716-5743 English

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Abstract

Thirty-two soil samples were collected from the study area in October 2020 for
geochemical and pollutants investigation of Shwan Sub-basin soil. All soil samples
were analysed for different geochemical analyses. The analysis results revealed that
the pH values in soil samples ranged from 7.12 to 7.56 with a mean of 7.327.
According to the pH values detected in the soil samples, the soil is classified as neutral
soil. The electrical conductivity ranged from 0.92 mmhos/cm to 7.8 mmhos/cm with
a mean of 1.53 mmhos/cm. Thus, according to the detected electrical conductivity
values, the soil was classified as non-saline to slightly saline. The organic matter
ranged from 1.14% to 1.45% with a mean value of 1.326 %, while total organic carbon
ranged from 0.66 % to 0.84 % with a mean value of 0.769 % which indicated the soil
was characterized by low organic content. The results of the geochemical analysis
revealed that the major and minor element mean concentrations were in the order Si>
Ca> Al> Fe> Mg > K> Ti> Na> P> Mn> S> Cl> N. The average concentrations of
trace elements in soil samples followed the decreasing order Sr > Cr> Ba> Zr> Ni>
V> Zn> Ta> Rb> Cu> Nb> Y> Pb> Co> Ga> Mo> As> Th> Br> Sn> I. Furthermore,
the comparison between heavy metal concentrations in the soil of the study area and
metal concentrations in the world soil limit and Indirect Geochemical Background
revealed an increase in metal concentrations of Cr, Ni, Zn, Co, As, Mo and Ta.
Multivariate statistical analyses, such as Principal Component Analysis and
Agglomerative Hierarchal Cluster Analysis, identified the potential sources of
pollutants in the soil. Most metals are from natural sources and some of them are from
anthropogenic sources mostly from agricultural activities mainly fertilizers use and
the waste of animals breeding on farms. Besides industrial activities such as deposits
of pollutants from emissions of petroleum refineries located inside or close to the
study area. In addition, building blocks and paint factories.

Keywords

geochemistry Multivariate statistical analyses. Shwan sub-basin Soil quality

22

Role Of -Operator in the Study of Minimal Open Sets

Pages: 5744-5755 English

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Abstract

The operator has been introduced as an associated set-valued set function. Although it has importance for the study of minimal open sets as well as minimal -open sets. As a result of this study, we introduce minimal -open sets . In this study, several characterizations of minimal -open sets are also investigated. This study also discusses the role of minimal -open sets in the -locally finite spaces. In an aspect of topological invariant, the homeomorphic images of minimal -open set has been discussed here.

Keywords

-open set -operator Homeomorphism. Minimal -open set

23

Nb-Compact and Nb-Lindelöf Spaces

Pages: 5756-5765 English

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Abstract

In this work, we present new types of compact and Lindelöf spaces and some facts and results related to them. There are also types of compact and Lindelöf functions and the relationship between them has been investigated. Further, we have present some properties and results related to them.

Keywords

Nb- Lindelöf. Nb-compact nearly Nb- Lindelöf nearly Nb-compact

24

Influence of Heat Transform and Rotation of Sutterby Fluid in an Asymmetric Channel

Pages: 5766-5777 English

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Abstract

In this research, the effect of the rotation variable on the peristaltic flow of Sutterby
fluid in an asymmetric channel with heat transfer is investigated. The modeling of
mathematics is created in the presence of the effect of rotation, using constitutive
equations following the Sutterby fluid model. In flow analysis, assumptions such as
long wave length approximation and low Reynolds number are utilized. The resulting
nonlinear equation is numerically solved using the perturbation method. The effects
of the Grashof number, the Hartmann number, the Hall parameter, the magnetic field,
the Sutterby fluid parameter, and heat transfer analysis on the velocity and the pressure
gradient are analyzed graphically. Utilizing MATHEMATICA software, numerical
results are computed. It is discovered that velocity varies with parameters, while the
pressure gradient is directly proportional to most parameters.

Keywords

heat transfer Magnetic field Peristaltic flow Sutterby Fluid

25

Goldie Rationally Extending Modules

Pages: 5778-5785 English

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Abstract

In this work, we introduce a new generalization of both Rationally extending and Goldie extending which is Goldie Rationally extending module which is known as follows: if for any submodule of an -module there is a direct summand of (denoted by ) such that . A is a relation of and , which defined as if and only if and .

Keywords

Goldie Extending Modules. Goldie Rationally Extending Modules Rationally Extending Modules

26

Mean Square Exponential Stability of Semi-Linear Stochastic Perturbed Differential Equation Via Lyapunov Function Approach

Pages: 5786-5794 English

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Abstract

In this work, a class of stochastically perturbed differential systems with standard Brownian motion of ordinary unperturbed differential system is considered and studied. The necessary conditions for the existence of a unique solution of the stochastic perturbed semi-linear system of differential equations are suggested and supported by concluding remarks. Some theoretical results concerning the mean square exponential stability of the nominal unperturbed deterministic differential system and its equivalent stochastically perturbed system with the deterministic and stochastic process as a random noise have been stated and proved. The proofs of the obtained results are based on using the stochastic quadratic Lyapunov function method. Form an application point of view of the proposed approach, an illustrative example is considered and implemented.

Keywords

Brownian motion Lyapunov Function. Mean square Stability Stochastic differential equation

27

Modeling Extreme COVID-19 Data in Iraq

Pages: 5795-5802 English

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Abstract

This paper considers the maximum number of weekly cases and deaths caused by
the COVID-19 pandemic in Iraq from its outbreak in February 2020 until the first of
July 2022. Some probability distributions were fitted to the data. Maximum
likelihood estimates were obtained and the goodness of fit tests were performed.
Results revealed that the maximum weekly cases were best fitted by the Dagum
distribution, which was accepted by three goodness of fit tests. The generalized
Pareto distribution best fitted the maximum weekly deaths, which was also accepted
by the goodness of fit tests. The statistical analysis was carried out using the Easy-
Fit software and Microsoft Excel 2019.

Keywords

Burr XII Dagum Generalized Extreme Value Generalized Pareto Pearson Type 6

28

Boubaker Scaling Operational Matrices for Solving Calculus of Variation Problems

Pages: 5803-5814 English

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Abstract

In this paper, a general expression formula for the Boubaker scaling (BS) operational matrix of the derivative is constructed. Then it is used to study a new parameterization direct technique for treating calculus of the variation problems approximately. The calculus of variation problems describe several important phenomena in mathematical science. The first step in our suggested method is to express the unknown variables in terms of Boubaker scaling basis functions with unknown coefficients. Secondly, the operational matrix of the derivative together with some important properties of the BS are utilized to achieve a non-linear programming problem in terms of the unknown coefficients. Finally, the unknown parameters are obtained using the quadratic programming technique. Some numerical examples are included to confirm the accuracy and applicability of the suggested direct parameterization method.

Keywords

Boubaker Scaling Functions Calculus of variation Lagrange multiplier technique Non-linear programming problem Operational matrix

29

The Generalized Homogeneous -Shift Operator ( ) for -Identities and -Integrals

Pages: 5815-5829 English

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Abstract

In this paper, we illustrate how to use the generalized homogeneous -shift operator in generalizing various well-known q-identities, such as Hiene's transformation, the q-Gauss sum, and Jackson's transfor- mation. For the polynomials , we provide another formula for the generating function, the Rogers formula, and the bilinear generating function of the Srivastava-Agarwal type. In addition, we also generalize the extension of both the Askey-Wilson integral and the Andrews-Askey integral.

Keywords

-hypergeometric polynomials Andrews-Askey -integral. Askey-Wilson integral generating function Hiene's transformation homogeneous -shift operator Jackson's transformation Rogers formula Srivastava-Agarwal generating function

30

Determination of Spacewise− Dependent Heat Source Term in Pseudoparabolic Equation from Overdetermination Conditions

Pages: 5830-5850 English

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Abstract

This paper examines the finding of spacewise dependent heat source function in pseudoparabolic equation with initial and homogeneous Dirichlet boundary conditions, as well as the final time value / integral specification as additional conditions that ensure the uniqueness solvability of the inverse problem. However, the problem remains ill-posed because tiny perturbations in input data cause huge errors in outputs. Thus, we employ Tikhonov’s regularization method to restore this instability. In order to choose the best regularization parameter, we employ L-curve method. On the other hand, the direct (forward) problem is solved by a finite difference scheme while the inverse one is reformulated as an optimization problem. The later problem is accomplished by employing lsqnolin subroutine from MATLAB. Two test examples are presented to show the efficiency and accuracy of the employed method by including many noises level and various regularization parameters.

Keywords

Finite Difference method inverse problem Pseudo-parabolic equation Tikhonov regularization method Von Neumann stability analysis

31

Efficient Algorithm for Solving Fuzzy Singularly Perturbed Volterra Integro-Differential Equation

Pages: 5851-5865 English

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Abstract

In this paper, we design a fuzzy neural network to solve fuzzy singularly perturbed Volterra integro-differential equation by using a High Performance Training Algorithm such as the Levenberge-Marqaurdt (TrianLM) and the sigmoid function of the hidden units which is the hyperbolic tangent activation function. A fuzzy trial solution to fuzzy singularly perturbed Volterra integro-differential equation is written as a sum of two components. The first component meets the fuzzy requirements, however, it does not have any fuzzy adjustable parameters. The second component is a feed-forward fuzzy neural network with fuzzy adjustable parameters. The proposed method is compared with the analytical solutions. We find that the proposed method has excellent accuracy in findings, a lower error rate, and faster convergence than other typical methods.

Keywords

Fuzzy Neural network Fuzzy Singularly perturbed Volterra integro-differential equations Levenberge-Marqaurdt Algorithm. Singularly perturbed Problems Volterra integro-differential equations

32

Novel Definitions of α-Fractional Integral and Derivative of the Functions

Pages: 5866-5877 English

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Abstract

An α-fractional integral and derivative of real function have been introduced in new definitions and then, they compared with the existing definitions. According to the properties of these definitions, the formulas demonstrate that they are most significant and suitable in fractional integrals and derivatives. The definitions of α-fractional derivative and integral coincide with the existing definitions for the polynomials for 0 ≤ α < 1. Furthermore, if α = 1, the proposed definitions and the usual definition of integer derivative and integral are identical. Some of the properties of the new definitions are discussed and proved, as well, we have introduced some applications in the α- fractional derivatives and integrals. Moreover, α-power series and α–rule of integration by parts have been proposed and implemented in this study.

Keywords

Fractional Integral; Fractional Derivative ;power series; rule of integration; FrDEs.

33

Existence and Uniqueness Theorem of Fuzzy Stochastic Ordinary Differential Equations

Pages: 5878-5886 English

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Abstract

A fuzzy valued diffusion term, which in a fuzzy stochastic differential equation refers to one-dimensional Brownian motion, is defined by the meaning of the stochastic integral of a fuzzy process. In this paper, the existence and uniqueness theorem of fuzzy stochastic ordinary differential equations, based on the mean square convergence of the mathematical induction approximations to the associated stochastic integral equation, are stated and demonstrated.

Keywords

Brownian motion. Existence and uniqueness theorem Fuzzy Differential Equations Stochastic differential equations

34

Machine Learning Approach for New COVID-19 Cases Using Recurrent Neural Networks and Long-Short Term Memory

Pages: 5887-5895 English

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Abstract

This research aims to predict new COVID-19 cases in Bandung, Indonesia. The system implemented two types of deep learning methods to predict this. They were the recurrent neural networks (RNN) and long-short-term memory (LSTM) algorithms. The data used in this study were the numbers of confirmed COVID-19 cases in Bandung from March 2020 to December 2020. Pre-processing of the data was carried out, namely data splitting and scaling, to get optimal results. During model training, the hyperparameter tuning stage was carried out on the sequence length and the number of layers. The results showed that RNN gave a better performance. The test used the RMSE, MAE, and R2 evaluation methods, with the best numbers being 0.66975075, 0.47075, 0.29616625, and 0.7644 on the test data.

Keywords

Covid-19 Long-Short Term Memory Prediction Recurrent neural networks

35

An Artificial Intelligence-based Proactive Network Forensic Framework

Pages: 5896-5911 English

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Abstract

is at an all-time high in the modern period, and the majority of the population uses the Internet for all types of communication. It is great to be able to improvise like this. As a result of this trend, hackers have become increasingly focused on attacking the system/network in numerous ways. When a hacker commits a digital crime, it is examined in a reactive manner, which aids in the identification of the perpetrators. However, in the modern period, it is not expected to wait for an attack to occur. The user anticipates being able to predict a cyberattack before it causes damage to the system. This can be accomplished with the assistance of the proactive forensic framework presented in this study. The proposed system combines a reactive and proactive framework. The proactive part will use machine learning-based classification algorithms to forecast the attack. Once the assault has been predicted, the reactive element of the proposed framework is used to investigate who is attempting to initiate the attack. The suggested system further emphasizes integrity and confidentiality by proposing an encryption method that encrypts the proactive module's report before decrypting it in the reactive module. The suggested elliptical curve cryptography-based security model was compared to several existing security methods in this paper.A comparison of multiple machine learning-based categorization algorithms is also performed in order to determine which is the most suitable for the proposed Network Forensic Framework. Accuracy, recall, precision, and F1 value are the performance metrics used to evaluate the various machine learning-based algorithms. According to the analysis, the suggested Network Forensic Framework is best implemented using the Extreme Gradient Boosting (XGB) technique.

Keywords

artificial intelligence Cyber Security Cyber-crime machine learning Network Forensic Framework

36

Multi-Objective Genetic Algorithm-Based Technique for Achieving Low-Power VLSI Circuit Partition

Pages: 5912-5922 English

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Abstract

Minimizing the power consumption of electronic systems is one of the most critical concerns in the design of integrated circuits for very large-scale integration (VLSI). Despite the reality that VLSI design is known for its compact size, low power, low price, excellent dependability, and high functionality, the design stage remains difficult to improve in terms of time and power. Several optimization algorithms have been designed to tackle the present issues in VLSI design. This study discusses a bi-objective optimization technique for circuit partitioning based on a genetic algorithm. The motivation for the proposed research is derived from the basic concept that, if some portions of a circuit's system are deactivated during the processor's idle time, the circuit's power consumption is automatically reduced. To reduce the overall system's power consumption, maximization of sleep time and minimization of net cuts are required. To achieve these, an effective fitness function has been constructed in such a way that the balance criteria are also maintained. The approach has been tested on a set of net lists from the ISPD'98 benchmark suite, each containing 10 to 30 nodes. The experimental results are compared with two existing methods that clearly indicate the acceptability of the suggested method. The suggested strategy achieves an average reduction of 24.69% and 31.46% for net cut, whereas average extensions of 15.20% and 12.31% are observed in sleep time when compared with two existing methods. The proposed method also achieves an average power efficiency of 14.98% and 12.09% with respect to these two state-of-the-art methods.

Keywords

VLSI Design; Partitioning; Multi-Objective Optimization; Genetic Algorithm; Net list; Sleep time; Net Cut

37

Developing the Complexity and Security of the Twofish Algorithm Through a New Key Scheduling Design

Pages: 5923-5939 English

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Abstract

The Twofish cipher is a very powerful algorithm with a fairly complex structure that permeates most data parsing and switching and can be easily implemented. The keys of the Twofish algorithm are of variable length (128, 192, or 256 bits), and the key schedule is generated once and repeated in encrypting all message blocks, whatever their number, and this reduces the confidentiality of encryption. This article discusses the process of generating cipher keys for each block. This concept is new and unknown in all common block cipher algorithms. It is based on the permanent generation of sub keys for all blocks and the key generation process, each according to its work. The Geffe's Generator is used to generate subkeys to make each explicit block a new key that differs from block to block, gaining protection against attacks. Finally, this algorithm works almost like a One-Time Pad.

Keywords

Geffe’s Algorithm key schedule Security Symmetric block cipher Twofish algorithm.

38

Image Splicing Detection Based on Discrete Wavelet Transform and co-occurrence Matrix

Pages: 5940-5951 English

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Abstract

In this paper a method to determine whether an image is forged (spliced) or not is
presented. The proposed method is based on a classification model to determine the
authenticity of a tested image. Image splicing causes many sharp edges (high
frequencies) and discontinuities to appear in the spliced image. Capturing these high
frequencies in the wavelet domain rather than in the spatial domain is investigated in
this paper. Correlation between high-frequency sub-bands coefficients of Discrete
Wavelet Transform (DWT) is also described using co-occurrence matrix. This
matrix was an input feature vector to a classifier. The best accuracy of 92.79% and
94.56% on Casia v1.0 and Casia v2.0 datasets respectively was achieved. This
performance is reached when Cb and Cr channels in YCbCr color space only are
utilized to form this feature vector. The outcomes of the experiments showed that
the proposed method achieved very good results in comparison with existing
splicing detection approaches.

Keywords

classification. Co-occurrence Matrix Discrete Wavelet transform Image forgery YCbCr color space

39

A Key Based Hybrid Approach for Privacy and Integrity in Multi-Cloud

Pages: 5952-5963 English

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Abstract

Before users store data in the cloud, many security issues must be addressed, as they will have no direct control over the data that has been outsourced to the cloud, particularly personal and sensitive data (health, finance, military, etc.). This article proposes a system based on chaotic maps for private key generation. A hybrid encryption for fast and secure cryptography. In addition to a multi-cloud storage with Pseudonymized file names to preserve user data privacy on the cloud while minimizing data loss. As well as a hash approach to check data integrity. AES in combination with RSA and fragmenting the file is used for the encryption. Integrity is cheeked using SHA-3. The experiments demonstrated that the key generation strategy may provide efficient keys in a shorter amount of time. Furthermore, the keys for the proposed approach passed NIST randomness testing. When cipher text fragmentation and encryption are combined, the average entropy value was (7.99). In addition, as file sizes grew, the total system's execution time increased only slightly.

Keywords

Cloud Computing (CC) Data integrity Encryption. Fragmentation key generation

40

Grey Wolf Optimization Algorithm: A Survey

Pages: 5964-5984 English

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Abstract

The Gray Wolf Optimizer (GWO) is a population-based meta-heuristic algorithm that belongs to the family of swarm intelligence algorithms inspired by the social behavior of gray wolves, in particular the social hierarchy and hunting mechanism. Because of its simplicity, flexibility, and few parameters to be tuned, it has been applied to a wide range of optimization problems. And yet it has some disadvantages, such as poor exploration skills, stagnation at local optima, and slow convergence speed. Therefore, different variants of GWO have been proposed and developed to address these disadvantages. In this article, some literature, especially from the last five years, has been reviewed and summarized by well-known publishers. First, the inspiration and the mathematical model of GWO were explained. Subsequently, the improved GWO variants were divided into four categories and discussed. After that, each variant's methodology and experiments were explained and clarified. The study ends with a summary conclusion of the main foundation of GWO and suggests some possible future directions that can be explored further.

Keywords

Grey wolf optimizer GWO applications. GWO variants metaheuristic Optimization

41

A Lightweight Image Encryption Algorithm Based on Elliptic Curves and a 5D Logistic Map

Pages: 5985-6000 English

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Abstract

Cryptography can be thought of as a toolbox, where potential attackers gain access to various computing resources and technologies to try to compute key values. In modern cryptography, the strength of the encryption algorithm is only determined by the size of the key. Therefore, our goal is to create a strong key value that has a minimum bit length that will be useful in light encryption. Using elliptic curve cryptography (ECC) with Rubik's cube and image density, the image colors are combined and distorted, and by using the Chaotic Logistics Map and Image Density with a secret key, the Rubik's cubes for the image are encrypted, obtaining a secure image against attacks. ECC itself is a powerful algorithm that generates a pair of public and private elements, and we generate secret key values with the help of the above key pair. This algorithm is applied to smart cards, sensors, and wireless network security. Whereas, the test results indicate that the highest value for PSNR is 7.9641, while the highest values for UACI and NPCR are 35.3721 and 99.9992, respectively. The encoding and decoding speeds reach 0.1561 and 0.1532 seconds, respectively.

Keywords

Chaotic cryptography Density Magic cube. NIST

42

Effect of Genetic Algorithm as a Feature Selection for Image Classification

Pages: 6001-6012 English

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Abstract

Analysis of image content is important in the classification of images, identification, retrieval, and recognition processes. The medical image datasets for content-based medical image retrieval ( are large datasets that are limited by high computational costs and poor performance. The aim of the proposed method is to enhance this image retrieval and classification by using a genetic algorithm (GA) to choose the reduced features and dimensionality. This process was created in three stages. In the first stage, two algorithms are applied to extract the important features; the first algorithm is the Contrast Enhancement method and the second is a Discrete Cosine Transform algorithm. In the next stage, we used datasets of the medical images using GA-based feature selection to find feature vectors. Images from the datasets and images from the query are recognized using a correlation coefficient. The third stage of the proposed method used a diverse density algorithm feedback technique to enhance the performance of the . Images of breast cancer, brain cancer, lung cancer, thyroid cancer, etc., may be retrieved using the suggested procedure. By using a feature selection algorithm based on GA to determine the best subset of features, the challenge of system dimensionality is reduced. The suggested method has greater accuracy in precision, recall, and F-score than the other techniques.

Keywords

Contrast Enhancement Technique Discrete Cosine Transform Feature extraction Feature Selection Genetic Algorithm.

43

COVID-19 Detection via Blood Tests using an Automated Machine Learning Tool (Auto-Sklearn)

Pages: 6013-6024 English

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Abstract

Widespread COVID-19 infections have sparked global attempts to contain the virus and eradicate it. Most researchers utilize machine learning (ML) algorithms to predict this virus. However, researchers face challenges, such as selecting the appropriate parameters and the best algorithm to achieve an accurate prediction. Therefore, an expert data scientist is needed. To overcome the need for data scientists and because some researchers have limited professionalism in data analysis, this study concerns developing a COVID-19 detection system using automated ML (AutoML) tools to detect infected patients. A blood test dataset that has 111 variables and 5644 cases was used. The model is built with three experiments using Python's Auto-Sklearn tool. First, an analysis of the Auto-Sklearn process is done by studying the impact of several learning settings and parameters on the COVID-19 dataset using different classification methods, namely meta-learning, ensemble learning, and a combination of ensemble learning and meta-learning. The results show that using Auto-Sklearn with a meta-learning and ensemble learning parameter model predicts the patients infected with COVID-19 with high accuracy, reaching 96%. Furthermore, the best algorithm selected is the Random Forest Classifier (RF), which outperforms other classification methods. Finally, AutoML can assist those new to data sciences or programming skills in selecting the appropriate algorithm and hyperparameters and reducing the number of steps required to achieve the best results.

Keywords

Auto-Sklearn AutoML Bayesian optimization Covid-19 Ensemble Learning meta-learning

44

Automatic Short Answer Grading System Based on Semantic Networks and Support Vector Machine

Pages: 6025-6040 English

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Abstract

In education, exams are used to asses students’ acquired knowledge; however, the manual assessment of exams consumes a lot of teachers’ time and effort. In addition, educational institutions recently leaned toward distance education and e-learning due the Coronavirus pandemic. Thus, they needed to conduct exams electronically, which requires an automated assessment system. Although it is easy to develop an automated assessment system for objective questions. However, subjective questions require answers comprised of free text and are harder to automatically assess since grading them needs to semantically compare the students’ answers with the correct ones. In this paper, we present an automatic short answer grading method by measuring the semantic similarity between the students answer and the correct answer. A semantic network was built to represent the relationship between the words of the two texts to calculate semantic similarity. Representing a text as a semantic network is the best knowledge representation that comes closest to human comprehension of the text, where the semantic network reflects the sentence's semantic, syntactical, and structural knowledge. Several features were extracted from the semantic network and used as input to train the support vector machine (SVM) model to predict the degree of the targeted semantic similarity. The proposed method was tested on the Mohler dataset that is publicly available online. The obtained results were evaluated and reported in terms of Pearson correlation and root mean squared error (RMSE) where it achieved 0.63 and 0.83 respectively. The proposed method outperformed all previous methods on the used dataset.

Keywords

Automatic Short Answer Grading E-learning semantic network Semantic Similarity Support vector machine

45

Attention Mechanism Based on a Pre-trained Model for Improving Arabic Fake News Predictions

Pages: 6041-6054 English

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Abstract

Social media and news agencies are major sources for tracking news and events. With these sources' massive amounts of data, it is easy to spread false or misleading information. Given the great dangers of fake news to societies, previous studies have given great attention to detecting it and limiting its impact. As such, this work aims to use modern deep learning techniques to detect Arabic fake news. In the proposed system, the attention model is adapted with bidirectional long-short-term memory (Bi-LSTM) to identify the most informative words in the sentence. Then, a multi-layer perceptron (MLP) is applied to classify news articles as fake or real. The experiments are conducted on a newly launched Arabic dataset called the Arabic Fake News Dataset (AFND). The AFDN dataset contains exactly 606912 news articles collected from multiple sources, so it is suitable for deep learning requirements. Both simple recurrent neural networks (S-RNN), long short-term memory (LSTM), and gated recurrent units (GRU) are used for comparison. According to evaluation criteria, our proposed model achieved an accuracy of (0.8127), which is the best and highest accuracy among the deep learning methods used in this work. Moreover, the performance of our proposed model is better compared to previous studies, which used the AFND.

Keywords

and Deep Learning. Arabic Fake News Attention Model Bi-LSTM GRU

46

Sensors Work in Agriculture: Where Are We? What Are the Prospects?

Pages: 6055-6071 English

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Abstract

The increased food requirement puts intense pressure on the agriculture community to grow more from the same resources resulting in people leaving the farming business. This happened not exclusively due to the industrial pressure to produce more but to the lack of technology adoption among growers. The use of the sensor in agriculture is not new, but its adoption among agriculture producers is a challenge for industry and scientists. This study aimed to determine sensors used in agricultural fields with challenges and prospects. The study found that sensors have successfully been used at the industry level with highly skilled labor; however, their adoption is challenging in rural agriculture systems due to the lack of a support system. The study found that the sensors used in predicting crop parameters, yield, quality, insect attacks, leaf damage, and several plants are crucial parameters to study. Sensors, particularly ground-based active optical sensors, have performed well while developing algorithms where soil parameters, environmental factors, and sensors have successfully predicted crop yield and quality.

Keywords

agriculture and Yield prediction Remote sensing sensor