http://aro.koyauniversity.org/index.php/aro/issue/feed ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY 2024-06-19T22:40:00+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 2024-03-24T09:40:53+00:00 Kosrat N. Kaka kosrat.nazad@koyauniversity.org Rebaz A. Omer rebaz.anwar@koyauniversity.org Dyari M. Mamand 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 2024-03-02T09:09:50+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 2024-03-02T09:09:04+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/1495 Analyzing Colorectal Cancer at the Molecular Level through Next-generation Sequencing in Erbil City 2024-03-05T14:31:39+00:00 Vyan A. Qadir vyan.asad@koyauniversity.org Kamaran K. Abdoulrahman kamaran.abdoulrahman@su.edu.krd <p>Colorectal cancer (CRC) ranks as the third leading cause of cancer-related deaths globally. It is characterized as a genomic disorder marked by diverse genomic anomalies, including point mutations, genomic rearrangements, gene fusions, and alterations in chromosomal copy numbers. This research aims to identify previously undisclosed genetic variants associated with an increased risk of CRC by employing next-generation sequencing technology. Genomic DNA was extracted from blood specimens of five CRC patients. The sequencing data of the samples are utilized for variant identification. In addition, the Integrative Genomic Viewer software (IGV) is used to visualize the identified variants. Furthermore, various in silico tools, including Mutation Taster and Align GVGD, are used to predict the potential impact of mutations on structural features and protein function. Based on the findings of this research, 12 different genetic variations are detected among individuals with CRC. Inherited variations are located within the following genes: MSH6, MSH2, PTPRJ, PMS2, TP53, BRAF, APC, and PIK3CA.</p> 2024-03-04T20:49:42+00:00 Copyright (c) 2024 Vyan A. Qadir, Kamaran K. Abdoulrahman http://aro.koyauniversity.org/index.php/aro/article/view/1402 Deep Learning-Based Optical Music Recognition for Semantic Representation of Non-overlap and Overlap Music Notes 2024-03-24T07:29:31+00:00 Rana L. Abdulazeez rana.abdulazeez@su.edu.krd Fattah Alizadeh fattah.alizadeh2010@gmail.com <p><span class="fontstyle0">In the technology era, the process of teaching a computer to interpret musical notation is termed optical music recognition (OMR). It aims to convert musical note sheets presented in an image into a computer-readable format. Recently, the sequence-to-sequence model along with the attention mechanism (which is used in text and handwritten recognition) has been used in music notes recognition. However, due to the gradual disappearance of excessively long sequences of musical sheets, the mentioned OMR models which consist of long short-term memory are facing difficulties in learning the relationships among the musical notations. Consequently, a new framework has been proposed, leveraging the image segmentation technique to break up the procedure into several steps. In addition, an overlap problem in OMR has been addressed in this study. Overlapping can result in misinterpretation of music notations, producing inaccurate findings. Thus, a novel algorithm is being suggested to detect and segment the notations that are extremely close to each other. Our experiments are based on the usage of the Convolutional Neural Network block as a feature extractor from the image of the musical sheet and the sequence-to-sequence model to retrieve the corresponding semantic representation. The proposed approach is evaluated on The Printed Images of Music Staves dataset. The achieved results confirm that our suggested framework successfully solves the problem of long sequence music sheets, obtaining SER 0% for the non-overlap symbols in the best scenario. Furthermore, our approach has shown promising results in addressing the overlapping problem: 23.12 % SER for overlapping symbols.</span></p> 2024-03-11T00:00:00+00:00 Copyright (c) 2024 Rana L. Abdulazeez, Fattah Alizadeh http://aro.koyauniversity.org/index.php/aro/article/view/1333 Brain Tumor Segmentation Using Enhancement Convolved and Deconvolved CNN Model 2024-04-04T21:17:21+00:00 Mohammed Al-Mukhtar mohammed.abdul@cc.uobaghdad.edu.iq Ameer H. Morad ameer@kecbu.uobaghdad.edu.iq Hussein L. Hussein hussein.l.h@ihcoedu.uobaghdad.edu.iq Mina H. Al-hashimi mina.haider@muc.edu.iq <p>The brain assumes the role of the primary organ in the human body, serving as the ultimate controller and regulator. Nevertheless, certain instances may give rise to the development of malignant tumors within the brain. At present, a definitive explanation of the etiology of brain cancer has yet to be established. This study develops a model that can accurately identify the presence of a tumor in a given magnetic resonance imaging (MRI) scan and subsequently determine its size within the brain. The proposed methodology comprises a two-step process, namely, tumor extraction and measurement (segmentation), followed by the application of deep learning techniques for the identification and classification of brain tumors. The detection and measurement of a brain tumor involve a series of steps, namely, preprocessing, skull stripping, and tumor segmentation. The overfitting of BTNet-convolutional neural network (CNN) models occurs after a lot of training time because training the model with a large number of images. Moreover, the tuned CNN model shows a better performance for classification step by achieving an accuracy rate of 98%. The performance metrics imply that the BTNet model can reach the optimal classification accuracy for the brain tumor (BraTS 2020) dataset identification. The model analysis segment has a WT specificity of 0.97, a TC specificity of 0.925914, an ET specificity of 0.967717, and Dice scores of 79.73% for ET, 91.64% for WT, and 87.73% for TC.</p> 2024-03-30T17:00:30+00:00 Copyright (c) 2024 Mohammed Almukhtar, Ameer H. Morad, Hussein L. Hussein, Mina H. Al-hashimi http://aro.koyauniversity.org/index.php/aro/article/view/1519 Bridging the Gap 2024-04-04T21:17:36+00:00 Soran S. Badawi soran.sedeeq@charmouniversity.org <p class="Abstract" style="margin-top: 0in; text-indent: 0in; line-height: 150%;">Effective organization and retrieval of news content are heavily reliant on accurate news classification. While the mountainous research has been conducted in resourceful languages like English and Chinese, the researches on under-resourced languages like the Kurdish language are severely lacking. To address this challenge, we introduce a hybrid approach called RFO-CNN in this paper. The proposed method combines an improved version of red fox optimization algorithm (RFO) and convolutional neural network (CNN) for finetuning CNN’s parameters. Our model’s efficacy was tested on two widely used Kurdish news datasets, KNDH and KDC-4007, both of which contain news articles classified into various categories. We compared the performance of RFO-CNN to other cutting-edge deep learning models such as bidirectional long short-term memory networks and bidirectional encoder representations from transformers (BERT) transformers, as well as classical machine learning approaches such as multinomial naive bayes, support vector machine, and K-nearest neighbors. We trained and tested our datasets using four different scenarios: 60:40, 70:30, 80:20, and 90:10. Our experimental results demonstrate the superiority of the RFO-CNN model across all scenarios, outperforming the benchmark BERT model and other machine learning models in terms of accuracy and F1-score.</p> 2024-04-03T07:50:01+00:00 Copyright (c) 2024 Soran S. Badawi http://aro.koyauniversity.org/index.php/aro/article/view/1486 Synthesis, Characterization, and Bioactivity Studies of the Schiff Base Ligand and its Zinc(II) Complex 2024-05-08T07:59:32+00:00 Nabaz A. Muhammad Salih nabaz.mohammad@soran.edu.iq <p>One of the largest concerns to global health in recent decades has been identified as the growth of bacteria resistance to antibiotics. The Schiff base (SBs) and the zinc(II) SBs complex compounds category have attracted a lot of interest because of their function in chemical syntheses and their potential for bioactive and pharmacological effects. The present study includes the synthesis of various SBs with different substituents. Equimolar mixtures of benzaldehyde derivatives (1, 2) and aniline derivatives (3, 4) are used to carry out a series of condensation reactions to get compounds (5-7). By stoichiometrically combining Zn (II) acetate and ZnCl2 separately with the SBs ligand (7) in ethanol, it has been possible to prepare the SBs zinc(II) complex (8). The structure of the ligand and its metal complex are analyzed using (Fourier transform infrared spectroscopy, 1H-NMR, 13C-NMR) spectroscopy, scanning electron microscopy, and liquid chromatography–mass spectrometry. Moreover, the synthesized compounds are verified in vitro against Escherichia coli Gram negative, Staphylococcus aureus Gram positive, and fungi (Candida albicans). Compounds (5, 7, and 8) indicated significant growth inhibition against E. coli Gram negative and fungi (C. albicans) with different inhibition zones starting from 7 to 17.5 mm.</p> 2024-04-08T00:00:00+00:00 Copyright (c) 2024 Nabaz A. Muhammad Salih http://aro.koyauniversity.org/index.php/aro/article/view/1526 Oxidative Stress Assessment in Colorectal Cancer Patients 2024-05-10T22:29:38+00:00 Vyan A. Qadir vyan.asad@koyauniversity.org Kamaran K. Abdoulrahman kamaran.abdoulrahman@su.edu.krd <div>Colorectal cancer (CRC), a global health challenge, exhibits rising incidence in low-income nations due to lifestyle&nbsp;changes. Oxidative stress, indicated by reactive oxygen species&nbsp;imbalance and Malondialdehyde (MDA), is linked to CRC. This&nbsp;study investigates oxidative stress markers, antioxidant enzymes,&nbsp;genetic markers, cellular regulation markers, and Vitamin E in&nbsp;CRC patients in Erbil. Ninety CRC patients and 30 healthy controls&nbsp;provided blood samples, processed and stored at –20°C. Enzyme-linked immunosorbent assay kits quantified oxidative stress,&nbsp;antioxidant markers, and Vitamin E. Oxidative stress markers showed significant differences, with elevated MDA and 8-hydroxy-2’-deoxyguanosine levels in patients. Nitrotyrosine exhibited lower expression in patients. Antioxidant enzymes glutathione peroxidase and superoxide dismutase were enhanced in patients, while glutathione (GSH), glutathione reductase and catalase levels were significantly lower in patients. The genetic marker KRAS showed a substantial decrease in patients (&lt;0.0001) but both adenomatous polyposis coli (APC) and CRC antigen (CCA) were higher. Serum&nbsp;vitamin E levels were significantly lower in patients (71.78 ± 6.368)&nbsp;compared to controls (142.3 ± 4.828, p &lt; 0.0001). Elevated oxidative&nbsp;stress, altered enzymatic activity, significantly lower expression of&nbsp;KRAS, and higher expression of APC and CCA in the patient group.&nbsp;Furthermore, reduced Vitamin E levels were observed in the patient&nbsp;group, highlighting potential challenges in antioxidant defense.</div> 2024-05-10T08:23:13+00:00 Copyright (c) 2024 Vyan A. Qadir, Kamaran Abdoulrahman http://aro.koyauniversity.org/index.php/aro/article/view/1393 Analysis and Design of a Box Culvert Using Bentley Culvert Master Software 2024-05-10T22:29:38+00:00 Anwer H. Dawood anwer.hazim@koyauniversity.org Dana K. Mawlood dana.mawlood@su.edu.krd <div>Box culverts are utilized in situations where natural stream flow intersects with roads and railway lines. This research&nbsp;utilizes a digital elevation model and the water Modeling System software to assess the catchment area of the primary valley and identify the factors contributing to flooding in Qoshtapa City. The study involves an analysis of the existing culvert and generated the necessary data for the design of a new culvert. Despite the presence of the existing culvert, floodwater levels rose to over 1 m above the roadway elevation of Erbil-Kirkuk during the last flood event in 2021–2022. The research collected hydrological and climatic data for the study area, conducted soil type analysis using the Harmonized World Soil Database software, and performed hydraulic calculations to estimate the maximum flood discharge of the valley using the Hydrological Engineering Center-Hydrological Modeling System software for flood return periods of 50, 100, and 200 years, for design, to select the best economic alternative. The new culvert design was executed using Bentley Culvert Master software to ensure that floodwaters can flow through the culvert without rising to street level. The results indicated that the new culvert design surpasses the capacity of the existing one. The results show that the best economic alternative hydraulic design is the first alternative capacity of 201 m<sup>3</sup>/s of a 100-year return period; the new&nbsp;design cross-section area of the culvert is 52.5 m<sup>2</sup>.</div> 2024-05-10T08:23:52+00:00 Copyright (c) 2024 Anwer H. Dawood, Dana K. Mawlood http://aro.koyauniversity.org/index.php/aro/article/view/1515 Efficient and Simplified Modeling for Kerosene Processing Quality Detection Using Partial Least Squares-Discriminant Analysis Regression 2024-05-10T22:29:38+00:00 Hayder M. Issa hayder.mohammed@garmian.edu.krd Rezan H. Hama Salih rezan.huseen@garmian.edu.krd <div>Kerosene from various refineries and crudes is&nbsp;used for heating and other purposes in many countries like Iraq;</div> <div>therefore, it is important to identify its source to recognize and tax any adulteration. In this study, a fast classification technique&nbsp;for kerosene marketed in Iraq was developed with the goal of&nbsp;identifying its quality. The samples were categorized using a&nbsp;supervised partial least squares discriminant analysis (PLS-DA)&nbsp;approach. Multivariate analyses using agglomerative hierarchal&nbsp;clustering and principal component analysis were utilized to&nbsp;identify outliers and sample dissimilarities. The dataset was divided&nbsp;into calibration and prediction sets. The prediction set was used&nbsp;to evaluate the model’s separation performance. The Q<sup>2</sup> cross-validation was applied. The PLS-DA models achieved significant&nbsp;accuracy, sensitivity, and specificity, showing strong segregation ability, notably for the calibration set (100% accuracy and 1.00&nbsp;sensitivity). It was found that kerosene processing can be classified&nbsp;rapidly and non-destructively without the need for complicated&nbsp;analyses, demonstrating the best results for classification even&nbsp;when compared with the classification outcomes of other fuels.&nbsp;This PLS-DA approach has never been looked at before for process&nbsp;quality detection, and the results are comparable to direct kerosene&nbsp;classification with soft independent modeling of class analogy and&nbsp;support vector machines.</div> 2024-05-10T09:54:54+00:00 Copyright (c) 2024 Hayder M. Issa, Rezan H. Hama Salih http://aro.koyauniversity.org/index.php/aro/article/view/1477 Optimizing Emotional Insight through Unimodal and Multimodal Long Short-term Memory Models 2024-06-17T06:53:18+00:00 Hemin F. Ibrahim hemin.ibrahim@tiu.edu.iq Chu K. Loo ckloo.um@um.edu.my Shreeyash Y. Geda sgeda@ee.iitr.ac.in Abdulbasit K. Al-Talabani abdulbasit.faeq@koyauniversity.org <p>The field of multimodal emotion recognition is increasingly gaining popularity as a research area. It involves analyzing human emotions across multiple modalities, such as acoustic, visual, and language. Emotion recognition is more effective as a multimodal learning task than relying on a single modality. In this paper, we present an unimodal and multimodal long short-term memory model with a class weight parameter technique for emotion recognition on the CMU-Multimodal Opinion Sentiment and Emotion Intensity dataset. In addition, a critical challenge lies in selecting the most effective fusion method for integrating multiple modalities. To address this, we applied four different fusion techniques: Early fusion, late fusion, deep fusion, and tensor fusion. These fusion methods improved the performance of multimodal emotion recognition compared to unimodal approaches. With the highly imbalanced number of samples per emotion class in the MOSEI dataset, adding a class weight parameter technique leads our model to outperform the state of the art on all three modalities — acoustic, visual, and language — as well as on all the fusion models. The challenges of class imbalance, which can lead to biased model performance, and using an effective fusion method for integrating multiple modalities often result in decreased accuracy in recognizing less frequent emotion classes. Our proposed model shows 2–3% performance improvement in the unimodal and 2% in the multimodal over the state-of-the-art achieved results.</p> 2024-06-09T22:43:04+00:00 Copyright (c) 2024 Hemin F. Ibrahim, Chu K. Loo, Shreeyash Y. Geda, Abdulbasit K. Al-Talabani http://aro.koyauniversity.org/index.php/aro/article/view/1618 Encryption of Color Images with a New Framework 2024-06-17T06:50:41+00:00 Mardan A. Pirdawood mardan.ameen@koyauniversity.org Shadman Kareem shadman.rahman@koyauniversity.org Omar Al-Rassam omar.alrassam@koyauniversity.org <p>The significance of image encryption has risen due to the widespread use of images as a key means of sharing data across different applications. Encryption methods are crucial in defending the confidentiality and integrity of valuable image data. This work proposes a novel method of image encryption technique based on the Elzaki transformation and substitution process, which is made possible by the extension of the Maclaurin series coefficients. The image is encrypted using an infinite series of hyperbolic functions and the Elzaki transform; the inverse Elzaki transform is then used to decrypt the image. Using modular arithmetic, the coefficients that result from the transformation are keyed.</p> 2024-06-14T11:02:52+00:00 Copyright (c) 2024 Mardan A. Pirdawood, Shadman Kareem, Omar Al-Rassam http://aro.koyauniversity.org/index.php/aro/article/view/1553 Geotechnical Assessment of the Slopes of Hamamok Dam, NE of Koya, Kurdistan Region of Iraq 2024-06-17T22:39:44+00:00 Bahra Dh. Ghafour bahra.dhahir@koyauniversity.org Mohammed J. Hamawandy mohammed.hamawandy@koyauniversity.org Varoujan K. Sissakian varoujan.sissakian@komar.edu.iq <p class="Abstract" style="margin-top: 0cm; text-indent: 0cm; line-height: 150%;"><span style="font-size: 12.0pt; line-height: 150%;">The Hamamok Dam is an earthfill dam with a height of 25 m and length of 125 m; constructed in 2011; located northwest of Koya town on a deep canyon-like valley that flows along the southeastern plunge of the Bana Bawi anticline; which forms Bawagi Mountain. The exposed rocks in the site belong to the Pila Spi and Gercus formations; however, rocks of the Khurmala and Kolosh formations are exposed upstream from the dam’s reservoir. The difference in the hardness of the carbonate rocks of the Pila Spi Formation which forms the uppermost parts of the cliffs surrounding the dam site and those of soft reddish brown clastics of the Gercus Formation caused steep slopes that suffer from slope instability problems. To assess a geotechnical study of slopes in the dam site, we have collected different field data to perform a Kinematic assessment method using Dip Analyst 2.0 software and draw the stereographic projection for the studied 10 stations using Stereonet v.11 software. Besides Bejerman’s method, which is based on field data only and indicates the Landslide Possibility Index (LPI). The results showed that the L.P.I. values range between 23 and 27, whereas the results of the Kinematic analysis showed that the right bank (Stations 1 – 5) suffers from plane sliding, whereas the left bank (Stations 6 – 10) suffers from toppling. In both cases, Joint 2 has the main role in the developed failures.</span></p> 2024-06-17T00:00:00+00:00 Copyright (c) 2024 Bahra Dh. Ghafour, Mohammed J. Hamawandy, Varoujan K. Sissakian http://aro.koyauniversity.org/index.php/aro/article/view/1351 A Comprehensive Framework for Integrating Robotics and Digital Twins in Façade Perforation 2024-06-19T22:40:00+00:00 Ahmed K. Ali ahmed.khairadeen@uod.ac <p>In contemporary design practices, the conflict between initial design approaches and subsequent manufacturing and construction stages presents a notable challenge. To address this disparity, our study aims to establish a comprehensive digital design workflow, bridging these gaps. The authors introduce a conceptual framework that seamlessly integrates the imperatives of LEED with the realm of robotic manufacturing, specifically tailored for construction sites. The proposed methodology encompasses four distinct iFOBOT modules: iFOBOT-environment, iFOBOT-design, iFOBOT-construct, and iFOBOT-monitor. The integration of these modules allows for a holistic approach to design and construction, fostering efficient collaboration between multidisciplinary teams. To validate the efficacy of the author’s approach, we conducted an empirical study involving the creation of a double-skin facade panel perforation using this integrated process. Initial findings emphasize the enhanced constructability achieved through simulated robotic interventions utilizing a heuristic function. Moreover, this research presents a functional prototype as a tangible embodiment of the method’s practical application and potential impact on the field of architectural design and construction.</p> 2024-06-19T10:48:27+00:00 Copyright (c) 2024 Ahmed K. Ali 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 http://aro.koyauniversity.org/index.php/aro/article/view/1388 A Review on Adverse Drug Reaction Detection Techniques 2024-06-17T07:09:09+00:00 Ahmed A. Nafea ahmed.a.n@uoanbar.edu.iq Manar AL-Mahdawi manar.thaer@nahrainuniv.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) is an important piece of information for determining a patient’s view of a single drug. This study attempts to consider and discuss this feature of drug reviews in medical opinion-mining systems. This paper discusses the literature that summarizes the background of this work. To achieve this aim, the first discusses a survey on detecting ADRs and side effects, followed by an examination of biomedical text mining that focuses on identifying the specific relationships involving ADRs. Finally, we will provide a general overview of sentiment analysis, particularly from a medical perspective. This study presents a survey on ADRs extracted from drug review sentences on social media, utilizing and comparing different techniques.</p> 2024-06-07T06:20:19+00:00 Copyright (c) 2024 Ahmed A. Nafea, Manar AL-Mahdawi, Mohammed M. AL-Ani , Nazlia Omar http://aro.koyauniversity.org/index.php/aro/article/view/1620 Microstrip Passive Components for Energy Harvesting and 5G Applications 2024-06-17T06:56:01+00:00 Leila Nouri leilanouri@duytan.edu.vn Salah I. Yahya salah.ismaeel@koyauniversity.org Abbas Rezaei a.rezaee@kut.ac.ir Sohrab Majidifar s.majidi@kut.ac.ir <p>This review paper provides a comprehensive overview of microstrip passive components for energy harvesting and 5G applications. The paper covers the structure, fabrication and performance of various microstrip passive components such as filters, couplers, diplexers and triplexers. The size and performance of several 5G and energy harvester microstrip passive devices are compared and discussed. The review highlights the importance of these components in enabling efficient energy harvesting and high-speed communication in 5G networks. Additionally, the paper discusses the latest advancements in microstrip technology and identifies key research challenges and future directions in this field. Overall, this review serves as a valuable resource for researchers and engineers working on microstrip passive components for energy harvesting and 5G applications.</p> 2024-06-10T07:51:44+00:00 Copyright (c) 2024 Leila Nouri, Salah I. Yahya, Abbas Rezaei, Sohrab Majidifar