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                <text>G.J. Mohammed</text>
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                <text>Alyousif, Shahad</text>
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                <text>Mohammed Hasan Ali</text>
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                <text>Jaber , Mustafa Musa</text>
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                <text>Cloud-based enterprise resource planning (ERP) and cloud computing are critical requirements for all SMEs since they can be used to facilitate the SMEs’ growth by creating competitive and personalized innovations considering their required business scope. To date, the growth of cloud technologies has led to the development of new systems and applications in many fields and areas including businesses. Our previous study proposed an adoption model to investigate the main determinants and logistical factors that influence decision-makers of SMEs to adopt cloud-based ERP systems. The aim of this research is to enhance the previous work by evaluating and validating the new model in real life to determine whether it has achieved what it was developed for and determine the reliability of the research results. The methodology and results of the evaluation and validation process of the proposed model are presented in this research. Considering there is little documentation in the literature specifically relevant to how proposed models have been evaluated and validated, hence providing this insight will assist both the academic researchers and decision-makers. The evaluation and validation methodology and the model itself contribute toward a better understanding of adoption processes. Furthermore, the evaluation and validation procedure in future work can be used to measure, enhance and determine whether the proposed models can be used in real life.</text>
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                <text>Copyright (c) 2022 Haider TH.Salim ALRikabi, G.J. Mohammed, Burhanuddin bin  Mohd Aboobaider , Shahad  Alyousif, Ahmed  Alkhayyat , Mohammed Hasan Ali , Rami Qays  Malik , Mustafa Musa  Jaber</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 21 (2022); pp. 153-167</text>
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                <text>1865-7923</text>
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                <text>Evaluation, Validation, Cloud ERP, decision makers, SME, Iraq</text>
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                <text>Affecting Factors for the Adoption of Cloud-Based ERP System in Iraqi SMEs: An Empirical Study</text>
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                <text>Wahyuni, Refni</text>
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                <text>Yuda Irawan</text>
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                <text>Covid-19 patients experience several symptoms such as shortness of breath, abnormal heart rate, lung function abnormalities that are similar to pneumonia symptoms. These symptom conditions indicate that the saturation of oxygen (O2) levels dissolved in the blood is not normal. To measure oxygen levels in the blood using a medical device, one of which is a Pulse Oximeter. Covid-19 patients in the Sapta Taruna Health Center were 665 patients, of which this patient was counted from January 2022 to April 2022. Based on information obtained from the Sapta Taruna Health Center, the only patients that were counted were those who did the PCR/Swab test, while the people who were suspected infected with Covid-19 there are still many who do not do PCR/Swab tests, this refusal is due to fear because Hoax information is spread in the community such as: PCR/Swab tests are painful, if the PCR/Swab test results are positive, fear of being ostracized, feel healthy and other reasons. other. Patients who have been tested positive for Covid-19 will be given drugs such as fever medicine, antibiotics, anti-virus, Vitamin C, and others according to the level of symptoms they feel, if the symptoms are felt at a moderate, mild or even asymptomatic stage, they will be advised to isolate independently (Isoma) at home, but there is no further monitoring from the Sapta Taruna Health Center, even though patients who are self-isolating at home may experience a decrease in blood oxygen levels drastically, so these patients need medical devices such as pulse oximetry so that patients who are isoma can perform independent checking, henceforth the current pulse oximetry cannot provide remote information related to the condition of oxygen saturation in the patient's blood. Judging from the problems above, the research team made a product, namely Pulse Oximetry based on IoT, this tool is to measure oxygen saturation in the patient's blood and the data from the measurements made by the patient will be automatically sent to the server and can be viewed on the Sapta Taruna Health Center website, so that the Sapta Taruna Health Center can monitoring the condition of the patient in real time without having to meet directly with the patient.</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/35859</text>
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                <text>Copyright (c) 2023 Refni Wahyuni, Herianto, Ikhtiyaruddin, Yuda Irawan</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 17 No. 03 (2023); pp. 177-187</text>
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                <text>1865-7923</text>
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                <text>Covid-19</text>
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                <text>Oxygen Detection</text>
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                <text>happy hypoxia</text>
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                <text>IoT</text>
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                <text>IoT-Based Pulse Oximetry Design as Early Detection  of Covid-19 Symptoms</text>
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                <text>Seno, Mohammed E.</text>
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                <text>Mohammad, Omer K. Jasim</text>
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                <text>Dhannoon, Ban N.</text>
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                <text>The cloud paradigm has swiftly developed, and it is now well known as one of the emerging technologies that will have a significant influence on technology and society in the next few years. Cloud computing also has several benefits, including lower operating costs, server consolidation, flexible system setup, and elastic resource supply. However, there are still technological hurdles to overcome, particularly with real-time applications by providing resources. Resources allocation management most charming part of cloud computing; therefore, several authors have worked in the area of resource usage. This study introduces an innovative cloud machine learning framework-based linear regression approach called cloud linear regression (CLR), which entails both cloud technology and machine learning concept. CLR using machine learning yielded good prediction results for resource allocation management, as appeared with many researching, and still seek, research to raise optimal solutions to the resources' allocation problem as the aim of this study.&amp;nbsp;&amp;nbsp; This study discusses the relation between cloud resource allocation management and machine learning techniques by illustrating the role of linear regression methods, resource distribution, and task scheduling. The analytical analysis shows that the CLR promises to present an effective solution for resources (scheduling, provisioning, allocation, and availability).</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/35791</text>
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                <text>10.3991/ijim.v16i22.35791</text>
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                <text>Copyright (c) 2022 Haider TH.Salim ALRikabi; Mohammed E.  Seno, Omer K. Jasim  Mohammad, Ban N.  Dhannoon</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 22 (2022); pp. 157-175</text>
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                <text>1865-7923</text>
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                <text>Task scheduling, Resource Allocation, Machin Learning Algorithms, linear regression, cloud-host, VM-placement, VM-migration.</text>
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                <text>CLR: Cloud Linear Regression Environment as a More Effective Resource-Task Scheduling Environment (State-of-the-Art)</text>
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                <text>Cloud computing technology is known as a distributed computing network, which consists of a large number of servers connected via the internet. This technology involves many worthwhile resources, such as applications, services, and large database storage. Users have the ability to access cloud services and resources through web services. Cloud computing provides a considerable number of benefits, such as effective virtualized resources, cost efficiency, self-service access, flexibility, and scalability. However, many security issues are present in cloud computing environment. One of the most common security challenges in the cloud computing environment is the trojan horses. Trojan horses can disrupt cloud computing services and damage the resources, applications, or virtual machines in the cloud structure. Trojan horse attacks are dangerous, complicated and very difficult to be detected. In this research, eight machine learning classifiers for trojan horse detection in a cloud-based environment have been investigated. The accuracy of the cloud trojan horses detection rate has been investigated using dynamic analysis, Cukoo sandbox, and the Weka data mining tool. Based on the conducted experiments, the SMO and Multilayer Perceptron have been found to be the best classifiers for trojan horse detection in a cloud-based environment. Although SMO and Multilayer Perceptron have achieved the highest accuracy rate of 95.86%, Multilayer Perceptron has outperformed SMO in term of Receiver Operating Characteristic (ROC) area.</text>
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                <text>Copyright (c) 2022 Dr. Hasan Kanaker, Dr.Nader Salameh , Dr.Samer A. B. Awwad , Dr. Nurul H.A. Ismail , Dr. Jamal Zraqou , Dr. Abdulla M. F. Al Ali</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 24 (2022); pp. 81-106</text>
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                <text>1865-7923</text>
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                <text>Trojan Horse Infection Detection  in Cloud Based Environment  Using Machine Learning</text>
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                <text>This research uses the Android module based on a strategy called "inquiry-based learning" and "flipped classroom" to help people utilize their cross-disciplinary skills in complex real-world situations. This experiment showed how the Android module-based inquiry flipped classroom learning affects math pre-service teachers' ability to solve mathematical problems and think creatively in geometry. In the third term, 123 students were randomly assigned Android module-based inquiry flipped classroom learning, PowerPoint module-based conventional flipped learning, or conventional learning. The study found that math pre-service teachers were much better at solving mathematics problems and creative thinking when using Android module-based inquiry flipped classroom learning because its use effectively extends learning time, permits the acquisition of more knowledge, and encourages a collective responsibility for learning in order to engage in the process of deeper learning. This type of learning also helps them learn how to deal with real-world problems that they may face in their future jobs. This implication can guide instructional designers on how to help students solve math problems and think creatively.</text>
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            <description>Information about rights held in and over the resource</description>
            <elementTextContainer>
              <elementText elementTextId="52362">
                <text>Copyright (c) 2022 Dessy Noor Ariani, Mohamad Syarif Sumantri, Firmanul Catur Wibowo</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 24 (2022); pp. 32-46</text>
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                <text>1865-7923</text>
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                <text>The Impact of Android Module-Based Inquiry Flipped Classroom Learning on Mathematics Problem Solving and Creative Thinking Ability</text>
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                  <text>International Journal of Interactive Mobile Technologies (iJIM)</text>
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                <text>Mahmood, Ibrahim Nasir</text>
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                <text>E-learning became the main medium of education in the world for the past two years. COVID-19 virus has pushed all the universities and academic institutions to utilize and activate E-learning platforms and systems. The sudden and urgent transformation from the regular traditional learning system to E-learning system has involved many challenges and limitations. Therefore, the need to evaluate and enhance the current E-learning mechanism in Iraq became very urgent and critical need. The target level was students at higher education institutes which include university students in Basra city. The data collected based on students’ evaluation and opinions about E-learning based on their interaction and usage during two years under COVID-19 spread era. This research involved applying data mining techniques to sample dataset and utilizing the obtained results as feedback for a proposed model suggested by the authors to measure adaptability. The proposed model is derived from the idea of the Technology Acceptance Model (TAM) with focus on the positivity as the main factor to measure adaptability. The results of the research showed approximate adaptation level of 52% which is very close compared to the actual situation in real life which involve limitations and challenges faced by Iraqi students.</text>
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              <elementText elementTextId="52342">
                <text>Copyright (c) 2022 Ibrahim Nasir Mahmood, Mustafa Ali Abuzaraida</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 17 No. 01 (2023); pp. 74-95</text>
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                <text>1865-7923</text>
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                <text>E-Learning, Computer Aided Learning, Data Mining, E-learning Adaptation Model, Web Based Learning</text>
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                <text>A Proposed Model for E-learning Adaptability Measurement During COVID-19 Pandemic Using Data Mining Techniques</text>
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                <text>Tawafak, Ragad M</text>
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                <text>The e-learning system is one of the most common methods for improving student performance and the ongoing goal of using e-learning in higher education. The most popular kind of e-learning system is a big one that is used at the college level, including Moodle, MOOCs, and e-learning systems. A rigorous review of various e-learning tools that can be used to raise students' performance is presented in this paper. Based on a survey of the literature, a comparison was established between the key elements employed in e-learning. The method used was to extract the common elements used in more than one popular model, then to connect these factors to e-learning. In order to create a better model with full element constraints, this paper also includes extracting causal links between these aspects. The analysis's finding is that the most recent models accepted for use in raising student performance are TAM2, TAM3, and ECT. This study reveals the framework used to highlights the easy and popular factors according to the updated related studies.  </text>
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                <text>International Association of Online Engineering (IAOE), Vienna, Austria</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 17 No. 03 (2023); pp. 160-176</text>
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                <text>1865-7923</text>
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                <text>In the most recent few years, there has been a meteoric rise in the number of different wireless networks, as has the demand for wireless data services and multimedia applications. An improvement in quality of service (QoS) is required in order to meet the ever-increasing demand while also providing a service that is of a higher standard. One of the most cutting-edge technologies, known as World Wide Interoperability for Microwave Access (WIMAX), was developed with the quality of service in mind during its development. Despite utilizing the most recent advancements in technology, the WiMAX network continues to struggle with QoS performance issues. A brand new distributed Client-Server model was designed for the fixed WiMAX Network in order to reduce application response time. This was done in order to improve the quality of service performance. In order to make a comparison with the existing centralized model, the performance of the proposed model was analyzed with OPNET Modeler 16.0. According to the findings, the newly proposed distributed Client-Server system is capable of satisfying the requirements set forth by its users owing to an improvement in QoS performance in terms of application response time when compared to the conventional model. The performance of the network was increased by the deployment of more Base Stations (BSs), Subscriber Stations, and the utilization of client-server Base Stations that were chosen by the Nearest Neighborhood Algorithm that was devised</text>
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                <text>Copyright (c) 2022 Ibrahim A. Lawal, Adamu Abubakar, Nuha A. Zammarah</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 22 (2022); pp. 75-93</text>
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                <text>1865-7923</text>
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                <text>WiMAX, QoS, Application Responsse Time, OFDM, FDM Base Station, Sub-scriber Station and OPNET Modeler 16.0</text>
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                <text>Improving the Quality of Service of Fixed WiMAX Networks by Decreasing Application Response Time Using a Distributed Model</text>
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                <text>Ajlouni, Aseel O</text>
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                <text>Robots and hypermedia have been used as effective technological tools in the educational field. Despite their educational benefits, there are no studies investigating their impact on primary students’ intrinsic motivation in the field of science. For these reasons, the study aims to recognize the impact of employing LEGO WeDo 2.0 robotic and hypermedia on intrinsic motivation to learn science among primary students. The study implemented the quasi-experimental approach with a dual group design. The experimental group (n=25) was instructed on the force and motion topic using instruction-based LEGO WeDo 2.0 robotic and hypermedia, while the control group (n=25) was instructed using traditional instruction. The study conducted in Jordan involved fifty primary students.  The data was gathered by administering the developed Intrinsic Motivation Towards Learning Science Scale to both groups at pre and post-points; ANCOVA analysis revealed a significant effect in favor of the experimental group in increasing intrinsic motivation to learn science at α = 0.05. These results recommend science instructors employ robots and hypermedia to foster students’ intrinsic motivation. It also encourages decision-makers in educational institutions to make decisions related to the science curriculum and its instructional methods.</text>
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              <elementText elementTextId="52276">
                <text>Copyright (c) 2022 Aseel O Ajlouni</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 17 No. 01 (2023); pp. 22-39</text>
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                <text>1865-7923</text>
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                <text>Robot</text>
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                <text>The  Impact of Instruction-based LEGO WeDo 2.0 Robotic and Hypermedia on Students’ Intrinsic Motivation to Learn Science</text>
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              <elementText elementTextId="52244">
                <text>Naser, Marwa T.</text>
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                <text>Wheeb, Ali H.</text>
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                <text>Future generations of wireless networks are expected to heavily rely on unmanned aerial vehicles (UAVs). UAV networks have extraordinary features like high mobility, frequent topology change, tolerance to link failure, and extending the coverage area by adding external UAVs. UAV network provides several advantages for civilian, commercial, search and rescue applications. A realistic mobility model must be used to assess the dependability and effectiveness of UAV protocols and algorithms.&amp;nbsp; In this research paper, the performance of the Gauss Markov (GM) and Random Waypoint (RWP) mobility models in multi-UAV networks for a search and rescue scenario is analyzed and evaluated. Additionally, the two mobility models GM and RWP are described in depth, together with the movement patterns they are related with. Furthermore, two-simulation scenarios conduct with help of an NS-3 simulator. The first scenario investigates the effect of UAV Speed by varying it from 10 to 50 m/s. the second scenario investigates the effect of the size of the transmitting packet by varying it from 64 to 1024 bytes. The performance of GM and RWP was compared based on packet delivery ratio (PDR), goodput, and latency metrics. Results indicate that the GM model provides the highest PDR and lowest latency in such high mobility environments.</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/35559</text>
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                <text>International Association of Online Engineering (IAOE), Vienna, Austria</text>
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              <elementText elementTextId="52254">
                <text>Copyright (c) 2022 Ass. Prof. Ali H. Wheeb, Marwa T. Naser</text>
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                <text>https://creativecommons.org/licenses/by/4.0</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 23 (2022); pp. 125-137</text>
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                <text>1865-7923</text>
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                <text>UAV</text>
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                <text>Gauss Markov</text>
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                <text>Implementation of RWP and Gauss Markov Mobility Model for Multi-UAV Networks in Search and Rescue Environment</text>
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