http://aro.koyauniversity.org/index.php/aro/issue/feed ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY 2024-02-29T22:03:35+00:00 Secretary office aro.journal@koyauniversity.org Open Journal Systems <p>ARO, which means "Today" in Hewramí Kurdish, is a distinguished scientific journal published by Koya University. It is an open access journal with an electronic ISSN (e-ISSN) of 2307-549X, a print ISSN (p-ISSN) of 2410-9355, and a Digital Object Identifier (DOI) of 10.14500/2307-549X. ARO encompasses a wide range of scholarly contributions, including research articles, review articles, and letters to the editor.</p> <p>As a peer-reviewed publication, ARO upholds the highest standards of academic rigour and integrity. It provides a platform for researchers in the fields of Science and Engineering to share their original works and advance knowledge in their respective disciplines. ARO has gained recognition and credibility in the academic community, as evidenced by its inclusion in the Directory of Open Access Journals (DOAJ) and the receipt of the DOAJ Seal.</p> <p>Furthermore, ARO has achieved an Impact Factor of 0.6, as announced in June 2023. This noteworthy accomplishment signifies the journal's influence and the significance of the research it publishes. The Impact Factor is a testament to the quality and impact of ARO's articles within the scholarly community.</p> <p>In addition, ARO has been accepted for indexing in the Emerging Sources Citation Index (ESCI), a prestigious edition of Web of Science™ by Clarivate Analytics. This recognition further establishes ARO as a reputable journal and highlights its contributions to scholarly discourse. Since February 2016, ARO has been listed in the ESCI, enabling researchers to access and cite its published articles through the Web of Science platform.</p> <p>ARO serves as a valuable resource for academics, scientists, and researchers, offering a diverse range of high-quality publications that contribute to the advancement of scientific knowledge.</p> http://aro.koyauniversity.org/index.php/aro/article/view/1418 Structural Characterization of Salts Using X-ray Fluorescence Technique 2024-02-16T06:22:32+00:00 Bashdar I. Meena bashdar.ismael@koyauniversity.org Hawbash H. Karim hawbash.hamadamin@koyauniversity.org Kurdistan F. Aziz kurdistan.fakhradin@koyauniversity.org Faten A. Chaqmaqchee faten.chaqmaqchee@koyauniversity.org Dashne M. Kokhasmail dashne.mawlood@koyauniversity.org Khabat N. Hussein khabat.noori@uod.ac <p>This study investigates the structure of 21 table salts that were collected from different local markets in the Kurdistan region of Iraq. The major trace elements and iodine concentrations in tablesalt are analyzed through the X-ray fluorescence (XRF) technique and the titration method, respectively. The study shows that using XRF spectral analysis, the collected table salt samples are rich in chlorine, sodium, and contain a lower percentage of bromine, strontium, tin, tellurium, and iodine. Moreover, these samples have a high percentage of sulfur and sirconium, where the molybdenum is &gt;0.2%. Other elements such as zinc and copper are essential and found in low concentrations &lt;0.0086% and 0.001%. Iodine is a trace element that is necessary nutrients for human life, and it is naturally present in some foods. Iodine deficiency is brought on by a lack of iodine consumption. Iodized salt is highly recommended as a source of iodine to prevent iodine deficiency disease. Iodine is added to table salt in two different ways, either through iodate or through iodine. The results show that only 25% of the salt samples have an adequate level of iodine, while the other samples have low or no iodine content. According to the World Health Organization, quality of salt depends on iodine concentration and other trace elements, which are necessary for human health.</p> 2024-01-06T04:57:08+00:00 Copyright (c) 2024 Bashdar I. Meena, Hawbash H. Karim, Kurdistan F. Aziz, Faten A. Chaqmaqchee, Dashne M. Kokhasmail , Khabat N. Hussein http://aro.koyauniversity.org/index.php/aro/article/view/1471 Synthesis of Some novel Azomethine Oxide Derived from Aromatic Oximes and their Anti-microbial Studies 2024-02-20T12:55:31+00:00 Jihad H. Mohammed jhm020h@chem.soran.edu.iq Akram N. M. Qaddo alnaib.akram@uomosul.edu.iq Nabaz A. Muhammad Salih nabaz.mohammad@soran.edu.iq Faeza B. Omar faeza.omar@soran.edu.iq <p>The organic compound category known as azomethine oxides has garnered significant attention due to its potential for bioactive and pharmacological effects, as well as its role in organic syntheses.&nbsp; Existing literature offers various methods for producing derivatives of these compounds.&nbsp; This study, in particular, concentrates on the creation of several aromatic oximes through the reduction of corresponding aldehydes. Furthermore, these oximes are employed in the generation of new azomethine oxides through a condensation reaction with selected aldehydes.&nbsp; The molecular structure of the synthesized azomethine oxides is determined using techniques such as Fourier-transform infrared spectroscopy, <sup>1</sup>H-NMR,&nbsp; and&nbsp; <sup>13</sup>C-NMR.&nbsp; Finally, the antimicrobial effectiveness of these compounds was assessed against Escherichia coli (gram-negative bacteria), <em>Staphylococcus aureus</em> (gram-positive bacteria), and <em>Candida albicans</em> (fungus). The synthesized compounds were obtained with high purity and yielded excellent results. Furthermore, the data demonstrates that these azomethine oxides exhibit significant antimicrobial activity when compared to standard drugs.</p> 2024-02-15T00:00:00+00:00 Copyright (c) 2024 Jihad H. Mohammed, Akram N. Qaddo, Nabaz A. Muhammad , Faeza B. Omar http://aro.koyauniversity.org/index.php/aro/article/view/1358 An Innovative Embedded Processor-Based Signal Phase Shifter Algorithm 2024-02-28T18:53:15+00:00 Aven R. Hamza Aven.rawf@spu.edu.iq Mohammed A. Hussein mohammedabdullah.hussein@univsul.edu.iq <p>Digital filtration is widely used today in many&nbsp;application fields, and with the increased use of low-cost embedded processors, it can be applied to vast areas. A&nbsp;drawback of digital&nbsp;filtration algorithms is the introduction of phase angle shifts in&nbsp;the filtered signals, thereby creating undesirable characteristics&nbsp;in many application fields. In this work, low-pass filters of finite&nbsp;impulse response and infinite impulse response types are designed&nbsp;with an innovative buffering scheme to delay a digitally low-passed&nbsp;signal by an angle ranging from 0° to 180° for real-time signals. The&nbsp;application of the filtration and buffering scheme on a cost-effective&nbsp;embedded processor with limited signal processing capabilities&nbsp;opens the horizons for its applicability in many signal processing&nbsp;fields. In assessing its practicality, the generated filtered output&nbsp;signal is correlated with the original signal (a low-passed version),&nbsp;revealing correlation values reaching 0.99 in certain instances.&nbsp;The novelty of the proposed approach enables its application to a&nbsp;broad-spectrum area of digital signal filtration.</p> 2024-02-15T00:00:00+00:00 Copyright (c) 2024 Aven R. Hamza, Mohammed A. Hussein http://aro.koyauniversity.org/index.php/aro/article/view/1397 Web Page Ranking Based on Text Content and Link Information Using Data Mining Techniques 2024-02-28T18:50:39+00:00 Esraa Q. Naamha cs.20.29@grad.uotechnology.edu.iq Matheel E. Abdulmunim matheel.e.abdulmunem@uotechnology.edu.iq <p>Thanks to the rapid expansion of the Internet, anyone can now access a vast array of information online. However, as the volume of web content continues to grow exponentially, search engines face challenges in delivering relevant results. Early search engines primarily relied on the words or phrases found within web pages to index and rank them. While this approach had its merits, it often resulted in irrelevant or inaccurate results. To address this issue, more advanced search engines began incorporating the hyperlink structures of web pages to help determine their relevance. While this method improved retrieval accuracy to some extent, it still had limitations, as it did not consider the actual content of web pages. The objective of the work is to enhance Web Information Retrieval methods by leveraging three key components: text content analysis, link analysis, and log file analysis. By integrating insights from these multiple data sources, the goal is to achieve a more accurate and effective ranking of relevant web pages in the retrieved document set, ultimately enhancing the user experience&nbsp;and delivering more precise search results the proposed system was&nbsp;tested with both multi-word and single-word queries, and the results&nbsp;were evaluated using metrics such as relative recall, precision, and&nbsp;F-measure. When compared to Google’s PageRank algorithm, the&nbsp;proposed system demonstrated superior performance, achieving&nbsp;an 81% mean average precision, 56% average relative recall, and&nbsp;a 66% F-measure.</p> 2024-02-16T06:18:11+00:00 Copyright (c) 2024 Esraa Q. Naamha, Matheel E. Abdulmunim http://aro.koyauniversity.org/index.php/aro/article/view/1403 An Ensemble Model for Detection of Adverse Drug Reactions 2024-02-28T18:48:36+00:00 Ahmed A. Nafea ahmed.a.n@uoanbar.edu.iq Mustafa S. Ibrahim mustafa.s.alsomadae@uoanbar.edu.iq Abdulrahman A. Mukhlif abdulrahman@uoanbar.edu.iq Mohammed M. AL-Ani p18709@siswa.ukm.edu.my Nazlia Omar nazlia@ukm.edu.my <p>The detection of adverse drug reactions (ADRs) plays a necessary role in comprehending the safety and benefit profiles of medicines. Although spontaneous reporting stays the standard approach for ADR documents, it suffers from significant under reporting rates and limitations in terms of treatment inspection. This study proposes an ensemble model that combines decision trees, support vector machines, random forests, and adaptive boosting (ADA-boost) to improve ADR detection. The experimental evaluation applied the benchmark data set and many preprocessing techniques such as tokenization, stop-word removal, stemming, and utilization of Point-wise Mutual Information. In addition, two term representations, namely, term frequency-inverse document frequency and term frequency, are utilized. The proposed ensemble model achieves an F-measure of 89% on the dataset. The proposed ensemble model shows its ability in detecting ADR to be a favored option in achieving both accuracy and clarity.</p> 2024-02-20T12:51:34+00:00 Copyright (c) 2024 Ahmed A. Nafea, Mustafa S. Ibrahim, Abdulrahman A. Mukhlif, Mohammed M. AL-Ani , Nazlia Omar http://aro.koyauniversity.org/index.php/aro/article/view/1431 Bromination of Chalcone 2024-02-28T22:03:34+00:00 Kosrat N. Kaka kosrat.nazad@koyauniversity.org Rebaz A. Omer rebaz.anwar@koyauniversity.org Dyari M. Mamada dyari.mustafa@uor.edu.krd Aryan F. Qader aryan.qader@koyauniversity.org <p>In this research work, a new compound, namely 2,6-dibromo-2,6-bis(bromo(phenyl)methyl)cyclohexanone (1), is synthesized and characterized for possible applications in organic electronic devices. The formation of the compound was confirmed by Fourier-transform infrared spectroscopy, 1H-, and 13C-NMR spectroscopy measurements. Furthermore, the spectroscopic and optoelectronic properties of the chemical compound were theoretically investigated using density-functional theory (DFT). Herein, the B3LYP/cc-pVDZ level was used to discover the compound electrostatic potentials and frontier molecular orbitals. The theoretical investigations predicted by DFT were compared with the experimentally obtained results from the ultraviolet visible spectra of the compound after being dissolved in various solvents. Results showed that the experimental band-gap energy of the compound is 3.17 eV, whereas its theoretical value was calculated to be 3.33 eV. The outcome of the achieved results suggests the viability of 2,6-dibromo-2,6-bis(bromo(phenyl)methyl)cyclohexanone for possible applications in organic electronic devices</p> 2024-02-28T18:27:18+00:00 Copyright (c) 2024 Kosrat N. Kaka, Rebaz A. Omer, Dyari M. Mamada, Aryan F. Qader http://aro.koyauniversity.org/index.php/aro/article/view/1314 Permeability Prediction for Carbonate Rocks using a Modified Flow Zone Indicator Method 2024-02-28T22:03:34+00:00 Ahmed J. Mahmood dr.ahmed.jabir@alfarabiuc.edu.iq Mohammed A. Jubair mohammed.a@sadiq.edu.iq <p>Carbonate reservoir rocks are usually heterogeneous, so it is not an easy task to establish a relation between porosity and permeability in these types of reservoir rocks. First, Kozney and Kozney-carmen formulas were used to establish these relations. Later, the flow zone indicator (FZI) method was introduced, which was widely used to find such a relation since it shows better results than the two former methods. In this work, the classical FZI method and a modified form of the FZI method are utilized to identify the hydraulic flow units and rock quality index to predict permeability. In this FZI method, the cementation factor (m) was introduced in calculating the value of FZI. The data collected from core analysis of the cored intervals in the Tanuma and Khasib formations were used as a database for this work. The classical and the modified FZI methods were applied using the database to predict core permeability. The value of the cementation factor was tuned to get a better match between the predicted permeability resulting from applying the modified method and the measured permeability values. Results show that the correlation coefficients resulting from applying the modified FZI method are closer to unity compared with that resulting from the classical FZI method. Cementation factor (m) of m = 3 for Tanuma formation and m = 3 for Khasib formation are the best values used with the modified FZI method. The modified FZI method shows a regression factor of 0.9986 for Tanuma and 0.9942 for Khasib formation.</p> 2024-02-28T19:04:37+00:00 Copyright (c) 2024 Ahmed J. Mahmood, Mohammed A. Jubair http://aro.koyauniversity.org/index.php/aro/article/view/1444 Electrocardiogram Heartbeat Classification using Convolutional Neural Network-k Nearest Neighbor 2024-02-29T22:03:35+00:00 Zrar Kh. Abdul eng.zrar1394@gmail.com Abdulbasit K. Al‑Talabani abdulbasit.faeq@koyauniversity.org Chnoor M. Rahman chnoor.rahman@charmouniversity.org Safar M. Asaad safar.maghdid@koyauniversity.org <p>Electrocardiogram (ECG) analysis is widely used by cardiologists and medical practitioners for monitoring cardiac health. A high-performance automatic ECG classification system is challenging because there is difficulty in detecting and categorizing different waveforms in the signal, especially in manual analysis of ECG signals, which means, a better classification system is needed in terms of performance and accuracy. Hence, in this paper, the authors propose an accurate ECG classification and monitoring system called convolutional neural network-k nearest neighbor (CNN-kNN). The proposed method utilizes 1D-CNN and kNN. Unlike the existing techniques, the examined technique does not need training during classifying the ECG signals. The CNN-kNN is evaluated against the PhysioNet’s MIT-BIH and PTB diagnostics datasets. The CNN is fed using the ECG beat raw signal directly. In addition, the learned features are extracted from the 1D-CNN model and its dimensions are reduced using two fully connected layers and then fed to the k-NN classifier. The CNN-kNN model achieved average accuracies of 98% and 97.4% on arrhythmia and myocardial infarction classifications, respectively. These results are evidence of the great ability of the proposed model compared to the mentioned models in this article.</p> 2024-02-29T08:02:15+00:00 Copyright (c) 2024 Zrar Kh. Abdul, Abdulbasit K. Al‑Talabani, Chnoor M. Rahman, Safar M. Asaad http://aro.koyauniversity.org/index.php/aro/article/view/1239 Glucuronidase Gene 2024-02-16T06:26:37+00:00 Hikmat M. Masyab hikmat.mustafa@koyauniversity.org Qutaiba S. Al-Nema dr.qutaibashuaib@uomosul.edu.iq Mozahim Q. Al-Mallah mozahim.k@hcd.edu.iq <p><em>Gluconacetobacter</em> <em>diazotrophicus</em>&nbsp;lives inside plant&nbsp;tissue cells in the form of colonies and excretes about half of the fixed&nbsp;nitrogen, which offers potential power that improves plant growth.&nbsp;The aim of this study is to find the interaction of glucuronidase (GUS)-labeled G. diazotrophicus&nbsp;with spinach seedlings and the detection&nbsp;of&nbsp;GUS&nbsp;genes using X-gluc dye (5-bromo-4-chloro-3-indolyl-β-D-&nbsp;glucuronic acid). The GUS protocol is used to detect GUS-labeled&nbsp;G. diazotrophicus&nbsp;in spinach seedling tissues by chemical detection&nbsp;using X-gluc dye. The results show that the spinach seedlings are&nbsp;successfully infected with GUS-labeled&nbsp;G. diazotrophicus&nbsp;, with the&nbsp;survival of the seedlings throughout their growth period and an&nbsp;improvement in the growth of pollinated seedlings. The outcomes&nbsp;of the microscopic inspection of the root slices reveal the presence&nbsp;of bacterial cells at the root tips and their concentration in the area&nbsp;of the cell walls of the peripheral cells. Furthermore, the findings&nbsp;of microscopic examinations of longitudinal sections for cotyledons&nbsp;show the presence of a number of bacteria within epidermal cell&nbsp;walls. This indicates that the determinants of the interaction between&nbsp;these bacteria and spinach seedlings are suitable for the expression&nbsp;of the gene responsible for the formation of the nitrogenase enzyme.</p> 2024-01-08T11:49:14+00:00 Copyright (c) 2024 Hikmat M. Masyab, Qutaiba S. Al-Nema, Mozahim Q. Al-Mallah