ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY <p>ARO (Today in Hewramí Kurdish) is a&nbsp;scientific&nbsp;journal published by Koya University with&nbsp;e-ISSN: 2307-549X, p-ISSN: 2410-9355, and DOI: 10.14500/2307-549X.&nbsp;ARO is a journal of research articles, review articles, and letters to editor. ARO is a peer-reviewed, open access journal that publishes original works in areas of Science and Engineering. ARO has been indexed by <a href="">DOAJ</a> and got <a href="">DOAJ Seal</a>. ARO has been accepted for indexing in the Emerging Sources Citation Index (ESCI), a new edition of Web of Science™ - <a href=";Word=aro" target="_self">Clarivate&nbsp;Analytics</a> (Web of Science) since Feb 2016.</p> en-US <p>Authors who publish with this journal agree to the following terms:</p> <ol type="a"> <li class="show">Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a&nbsp;Creative Commons Attribution License [<a href="">CC BY-NC-SA 4.0</a>]&nbsp;that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.</li> <li class="show">Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.</li> <li class="show">Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See&nbsp;<a href="" target="_new">The Effect of Open Access</a>).</li> </ol> (Dr. Dilan M. Rostam) (Prof. Dr. Salah I. Yahya) Fri, 18 Feb 2022 08:19:32 +0000 OJS 60 Wound Healing Properties and Structural Analysis of Four Geographical Areas’ Natural Clays <p>Clays are fine particle materials that harden after drying. The difference in their structure is the key to their efficacy and their subsequent application. The current study aims to evaluate the wound healing property of four countries (C1:Iraq, C2:Turkey, C3:Azerbaijan and C4:Russia) clay samples by excision model using Sprague dawley rats also the chemical analysis of the samples was performed using X-ray diffraction (XRD) and X-ray Fluorescence (XRF) methods. Results revealed that the best wound healing activities were given by C1, C3, C4 and C2 respectively with healing percentages (76%, 71%, 62%, and 60%), respectively. XRD results revealed the presence of Calcium carbonate and CalciumMagnesium carbonate in C1, Dolomite and Calcium-Magnesium carbonate in C2, Cobalt Tantalum Sulfide in C3, Finally Quartz and Silicon Oxide in C4. On the other hand, XRF analysis showed the appearance of different major and trace elements with different quantities in each clay type. We conclude that different countries clays enclose wound healing property with diverse ranges and this diversity is due to their chemical and mineral structures.</p> Zahra A. Amin Copyright (c) 2022 Zahra A. Amin Tue, 15 Feb 2022 00:00:00 +0000 Cement Percent Effect on the Shear and Interface Strength of Remolded Cement Treated Sand <p>This research aims to simulate the behavior of remolded cement treated poorly graded sand in term of shear and interface strength using the direct shear test. Different percentages of cement up to 15% by weight are added to the soil samples. Compacted cement treated soil samples are prepared at the optimum moisture content and left for 28 days in the humidity room then distributed to use them for the remolding samples preparation. The shear strength parameters for both cases soil to soil interface and concrete to soil interface are predicted, where the results show that the interface strength parameters are higher than the shear strength parameters of the remolded soil samples. The increase in cement percent increases the cohesion (C) of the treated soil, whereas the interface cohesion (Cint.) has a maximum value at 10% of added cement, and the maximum percent between cohesion (Cint.) and soil cohesion (C) is of 76.2% at 0% added cement. Moreover, the results show an increase in the interface angle of friction (δ) and a decrease in the angle of friction (φ) as the percent of cement increases. The maximum percent between interface angle (δ) and angle of friction (φ) is 63.5% at 15% of the added cement. The hardened cement in the remolded case adheres to sand grains and works as soil grains with different sizes that lead to changes in the shear properties of the soil.</p> Zahraa N. Rashied Copyright (c) 2022 Zahraa N. Rashied Sat, 19 Feb 2022 09:10:20 +0000 Application of Experimental Design Methodology for Adsorption of Brilliant Blue onto Amberlite XAD-4/Agaricus campestris as a New Biocomposite Adsorbent <p>This research presents a new biocomposite adsorbents using response surface methodology (RSM) to find the best conditions for highest adsorption of Brilliant Blue G250 (BBG) from aqueous solution by Amberlite XAD-4/<em>Agaricus campestris</em>. The most effective parameters are determined by Plackett–Burman design (PBD) with specific ranges initial dye concentration (5–150 mg.L<sup>-1</sup>), temperature (20–50°C), contact time (5–100 min), pH (3–11), shaking speed (150–300 rpm), sample volume (5–75 mL), and adsorbent dosage (0.05–0.6 g). Then, in the second step, the optimum condition of effective factors is predicted using steepest ascent design. Finally, optimal medium conditions of effective parameters with central composite design are located. According to RSM, the best adsorbent amount, contact time, initial dye concentration, and sample volume for maximum removal% of BBG (96.72%) are 0.38 g, 60.78 min, 107.13 mg.L<sup>-1</sup>, and 28.6 mL, respectively. The adsorption of brilliant blue is approved by scanning electron microscopy. Under optimum conditions, it is concluded that XAD4/A. <em>campestr</em> is biocomposite is a suitable adsorbent for removing BBG from aqueous solution.</p> Ahmed A. Ahmed, Vahap Yönten Copyright (c) 2022 Ahmed A. Ahmed, Vahap Yönten Fri, 25 Feb 2022 00:00:00 +0000 Detecting Deepfakes with Deep Learning and Gabor Filters <p>The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters in<br>different directions and then feed them to a binary CNN classifier instead of using the red-green-blue color information. The purpose of this paper is to give the reader a deeper view of (1) enhancing the efficiency of distinguishing fake facial images from real facial images by developing a novel model based on deep learning and Gabor filters and (2) how deep learning (CNN) if combined with forensic tools (Gabor filters) contributed to the detection of deepfakes. Our experiment shows that the training accuracy reaches about 98.06% and 97.50% validation. Likened to the state-of-the-art methods, the proposed model has higher efficiency.</p> Wildan J. Jameel, Suhad M. Kadhem, Ayad R. Abbas Copyright (c) 2022 Wildan J. Jameel, Suhad M. Kadhem, Ayad R. Abbas Fri, 18 Mar 2022 18:07:34 +0000 Suitability of the Carbonate Rocks of the Bekhme Formation Exposed in Shakrook Anticline, Iraqi Kurdistan region, for Cement Industry <p style="text-align: justify;">The Bekhme Formation forms almost the bulk of the Shakrook anticline, especially the limbs. The current research deals with studying the exposed beds within the Bekhme Formation at the Shakrook anticline to check the suitability of the exposed rocks at the northeastern limb of the anticline for the cement industry. Twenty rock samples from a section which lies along a deeply cut valley that crosses the northeastern limb of the Shakrook anticline within the Bekhme Formation were collected. The channel sampling method was applied; therefore, each sample represents the concerned sampling interval and to be representative for the thickness of the sampled interval. The total thickness of the sampled section is 110 m with a covered interval of 15 m, totaling to 125 m. The collected 20 samples were prepared at the laboratory of the Koya University and were subjected to XRF test at the Tarbiat Modares University, Iran, to indicate the concentration of the main oxides (CaO, MgO, Al2O3, Fe2O3, Na2O, K2O, and SO3), and Cl and L.O.I. The indicated concentrations at each sample, from both universities, were compared and were found to be almost coinciding. The average concentrations at each sample were changed to weighted averages and the results were compared with the Iraqi standards for cement industry. The results revealed that the sampled rocks are excellent for cement production.</p> Mohammed J. Hamwandy, Rahel Kh. Ibrahim, Varoujan K. Sissakian Copyright (c) 2022 Mohammed J. Hamwandy, Rahel Kh. Ibrahim, Varoujan K. Sissakian Fri, 25 Mar 2022 00:00:00 +0000 Bioremediation Ability of the Local Isolate Enterobacter cloacae from Disposal Site <p>Illegal dumping is a serious problem that needs to be addressed immediately to preserve human health and the environment as if the pollution that arises from it reaches the groundwater, complications of the remediation processes will increase. To decontaminate the organic and inorganic components, bioremediation seems to be the most environmentally friendly and economically viable technique without further treatment as reported by many studies. In this investigation, samples were taken from the soil of the main dumping area in Koysinjaq in Kurdistan Region of Iraq to determine the most potent bacteria to remediate the existed pollutants. The existence of non-essential minerals and organic compounds in the soil sample was detected using X-ray fluorescence device, and ethane and 1,2-dichloroethane solvents separating technique, respectively. Then, from the same samples, three different naturally occurring bacteria were isolated and cultured under optimized conditions then stimulated for a good result. Finally, spectrophotometer was set at wavelength of 600 nm and used to detect the heaviest growth of bacteria after incubating the cultured bacteria on a mineral salt broth medium with the extracted pollutants at pH 7.0 overnight at 32°C. Based on the highest absorbance, the most effective type of bacteria (Enterobacter cloacae) was chosen among others to remediate the organic components in which approximately 90% of them are plastics, medical waste, municipal waste, electrical items, and hydrocarbons, and some heavy metals, for instance aluminum and lead, which were found in the soil.</p> Hanaa A. Muhammad, Hanan T. Subhi, Khalid N. Sediq Copyright (c) 2022 Hanaa A. Muhammad, Hanan T. Subhi, Khalid N. Sediq Sun, 10 Apr 2022 00:00:00 +0000 Network Transmission Flags Data Affinity-based Classification by K-Nearest Neighbor <p>Abstract—This research is concerned with the data generated during a network transmission session to understand how to extract value from the data generated and be able to conduct tasks. Instead of comparing all of the transmission flags for a transmission session at the same time to conduct any analysis, this paper conceptualized the influence of each transmission flag on network-aware applications by comparing the flags one by one on their impact to the application during the transmission session, rather than comparing all of the transmission flags at the same time. The K-nearest neighbor (KNN) type classification was used because<br>it is a simple distance-based learning algorithm that remembers earlier training samples and is suitable for taking various flags with<br>their effect on application protocols by comparing each new sample with the K-nearest points to make a decision. We used transmission session datasets received from Kaggle for IP flow with 87 features and 3.577.296 instances. We picked 13 features from the datasets and ran them through KNN. RapidMiner was used for the study, and the results of the experiments revealed that the KNN-based model was not only significantly more accurate in categorizing data, but it was also significantly more efficient due to the decreased processing costs.</p> Nahla Aljojo Copyright (c) 2022 Nahla Aljojo Mon, 25 Apr 2022 20:50:35 +0000 Detection of SARS-CoV-2 Reinfections by Rapid Inexpensive Methods <p>New SARS-CoV-2 infections are difficult to beverified, whether they are reinfections or persistent infections. The most prominent factors used for differentiating reinfections from persistent infections are whole-genome sequencing and phylogenetic analyses that require time and funds, which may not be feasible in most developing countries. This study explores reinfections with COVID-19 that harbors D614G and N501Y mutations by rapid inexpensive methods. It exploits the previously developed rapid economic methods that identified both D614G and N501Y mutations in clinical samples using real-time reverse transcriptase polymerase chain reaction (rRT-PCR) probes and conventional PCR specific primers. In the present study, an immunocompetent patient has been found with a SARS-CoV-2 N501Y reinfection without comorbidities. According to the obtained results, this study suggests that the initial infection was due to a variant that contained only D614G mutation whereas the reinfection was potentially a result of alpha variant contained three mutations confirmed by DNA sequencing, including D614G, N501Y, and A570D mutations. These techniques will support rapid detection of SARS-CoV-2 reinfections through the identification of common spike mutations in the developing countries where sequencing tools are unavailable. Furthermore, seven cases of reinfections were also confirmed by these methods. These rapid methods can also be applied to large samples of reinfections that may increase our understanding epidemiology of the pandemic.</p> Sirwan M.A. Al-jaf, Sherko S. Niranji Copyright (c) 2022 Sirwan M.A. Al-jaf, Sherko S. Niranji Tue, 03 May 2022 08:13:27 +0000 Driver Drowsiness Detection Using Gray Wolf Optimizer Based on Face and Eye Tracking <p>It is critical today to provide safe and collision-free transport. As a result, identifying the driver’s drowsiness before their capacity to drive is jeopardized. An automated hybrid drowsiness classification method that incorporates the artificial neural network (ANN) and the gray wolf optimizer (GWO) is presented to discriminate human drowsiness and fatigue for this aim. The proposed method is evaluated in alert and sleep-deprived settings on the driver drowsiness detection of video dataset from the National Tsing Hua University Computer Vision Lab. The video was subjected to various video and image processing techniques to detect the drivers’ eye condition. Four features of the eye were extracted to determine the condition of drowsiness, the percentage of eyelid closure (PERCLOS), blink frequency, maximum closure duration of the eyes, and eye aspect ratio (ARE). These parameters were then integrated into an ANN and combined with the proposed method (gray wolf optimizer with ANN [GWOANN]) for drowsiness classification. The accuracy of these models was calculated, and the results demonstrate that the proposed method is the best. An Adadelta optimizer with 3 and 4 hidden layer networks of (13, 9, 7, and 5) and (200, 150, 100, 50, and 25) neurons was utilized. The GWOANN technique had 91.18% and 97.06% accuracy, whereas the ANN model had 82.35% and 86.76%.</p> Sarah S. Jasim, Alia K. Abdul Hassan, Scott Turner Copyright (c) 2022 Sarah S. Jasim, Alia K. Abdul Hassan, Scott Turner Thu, 05 May 2022 00:00:00 +0000