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                  <text>Canadian Journal of European and Russian Studies</text>
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                <text>Makarov, Igor</text>
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                <text>According to the current international climate change regime, countries are responsible for greenhouse gas (GHG) emissions that result from economic activities within their national borders, including emissions from producing goods for export. At the same time, imports of carbon-intensive goods are not addressed by international agreements, including the Paris Agreement that was adopted in 2015. This paper examines emissions embodied in Russia’s exports and imports based on the results of an input-output analysis. Russia is the second largest exporter of emissions embodied in trade and the large portion of these emissions is directed to developed countries. Because of the large amount of net exports of carbon-intensive goods, the current approach to emissions accounting does not suit Russia’s interests. On the one hand, Russia, as well as other large net emissions exporters, is interested in the revision of allocation of responsibility between exporters and importers of carbon-intensive products. On the other hand, both the commodity exports structure and relatively carbon inefficient technologies make Russia vulnerable to the policy of “carbon protectionism,” which can be implemented by its trade partners.
&amp;nbsp;
Full text available at: https://doi.org/10.22215/rera.v11i2.1192</text>
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                <text>Canadian Journal of European and Russian Studies; 2017: RERA V11:2 Economic Challenges and Solutions for Rational Environmental Management in the Russian Federation (backfile abstracts)</text>
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                <text>Carbon Emissions Embodied in Russia’s Trade: Implications for Climate Policy1</text>
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                <text>Indiana International &amp; Comparative Law Review; Vol. 2 No. 1 (1991); 191-220</text>
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                <text>This research is an android-based educational game development research to increase interest in learning mathematics for elementary school students. This study aims to make the development of educational games able to be a solution in increasing students' interest in learning Mathematics at the initial level, namely the elementary school level. The method used in this research is the Research and Development model ADDIE (Analyse, Design, Development, Implement, Evaluation). In this study, it was limited to the implementation stage which was tested through experimental research. This research is included in the type of experimental research. The experimental design used is a simple experiment in the form of Posttest Only Control Group Design. The conclusion that can be drawn from this research is that Android-based educational games are proven to increase the interest in learning mathematics for elementary school students.</text>
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                <text>Copyright (c) 2022 Iva Sarifah, Ai Rohmaniar, ARITA MARINI, Julius Sagita, Sri  Nuraini, Desy Safitri, Arifin Maksum, Ajat Sudrajat, Yustia Suntari</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 18 (2022); pp. 149-161</text>
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                <text>1865-7923</text>
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                <text>Development of Android Based Educational Games to Enhance Elementary School Student Interests in Learning Mathematics</text>
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                <text>Technology advent has been transforming students’ perceptions and preferences mostly on how they acquire information and learn. The way students perceive e-books and print books significantly influences the format they prefer to use for academic purposes. Recently, the accessibility of e-books on assorted mobile gadgets is substituting the conventional print based resources which are regarded costly in production, sharing and also heavy. Differing views on the format (e-book or print) that students prefer for academic purposes to improve their educational experience exist of which most studies have been done in developed countries. Therefore, a research that reveals students’ perceptions and preferences towards the two book formats in the nation of South Africa can afford a better understanding and conclusion on an African student. This study aimed to determine students’ preference on using e-books and print books in meeting academic information needs based on perceptions. The study adopted a cross-sectional research design and a questionnaire as a research instrument which was administered to students at the University of Fort Hare. Findings revealed that students preferred using both (e-books and print books) for their academic needs. Moreover, they perceived e-books to be as good as print books, easy and friendly to use and capable of providing sufficient information to meet educational needs. </text>
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                <text>Copyright (c) 2019 Comfort Makwanya, Olabanji Oni</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 13 No. 12 (2019); pp. 236-245</text>
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                <text>1865-7923</text>
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                <text>E-Books Preference Compared to Print Books Based on Student Perceptions: A  Case of University of Fort Hare Students</text>
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                <text>Taha Ahmed, Shaymaa</text>
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                <text>— Chest imaging diagnostics is crucial in the medical area due to many serious lung diseases like cancers and nodules and particularly with the current pandemic of Covid-19. Machine learning approaches yield prominent results toward the task of diagnosis. Recently, deep learning methods are utilized and recommended by many studies in this domain. The research aims to critically examine the newest lung disease detection procedures using deep learning algorithms that use X-ray and CT scan datasets. Here, the most recent studies in this area (2015-2021) have been reviewed and summarized to provide an overview of the most appropriate methods that should be used or developed in future works, what limitations should be considered, and at what level these techniques help physicians in identifying the disease with better accuracy. The lack of various standard datasets, the huge training set, the high dimensionality of data, and the independence of features have been the main limitations based on the literature. However, different architectures of deep learning are used by many researchers but, Convolutional Neural Networks (CNN) are still state-of-art techniques in dealing with image datasets.</text>
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          <element elementId="47">
            <name>Rights</name>
            <description>Information about rights held in and over the resource</description>
            <elementTextContainer>
              <elementText elementTextId="44011">
                <text>Copyright (c) 2021 Shaymaa Taha Ahmed, Suhad Malallah Kadhem</text>
              </elementText>
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            <description>A related resource from which the described resource is derived</description>
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              <elementText elementTextId="44012">
                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 16 (2021); pp. 95-112</text>
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              <elementText elementTextId="44013">
                <text>1865-7923</text>
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            <name>Subject</name>
            <description>The topic of the resource</description>
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                <text>Lung Disease</text>
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                <text>Machine Learning</text>
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                <text>Deep Learning</text>
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                <text>CT-Images</text>
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                <text>CNN</text>
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                <text>Covid-19</text>
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            <name>Title</name>
            <description>A name given to the resource</description>
            <elementTextContainer>
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                <text>Using Machine Learning via Deep Learning Algorithms to Diagnose the Lung Disease Based on Chest Imaging: A Survey</text>
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              <name>Title</name>
              <description>A name given to the resource</description>
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                  <text>International Journal of Interactive Mobile Technologies (iJIM)</text>
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      <name>Dataset</name>
      <description>Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing.</description>
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            <name>Creator</name>
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                <text>Malik ALattar, Ibrahim</text>
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                <text>Monem S. Rahma, Abdul</text>
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            <description>An account of the resource</description>
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                <text>This paper describes the development of encryption algorithms using the magic square of order 5 and Multi-level keys with the addition of Matrix keys to increase implementation speed and complexity. This work relied mainly on the magic sum and some equations that were added as an improvement on previous work. Multi-level keys were used for three different message sizes, and an additional key matrix with size 5×5 was used to add more complexity. The proposed work was performed using both GF(P) and GF(28). Results were compared with the MS3, they have been found good, with acceptable speed and high complexity where it was (P)9 × (256)16 in the first algorithm, (P)9 × (256)16 × 3 in the second algorithm, and (P)9 × (256)16 × 3 × (P)25 in the third algorithm, the complexity changed according to the chosen value of N randomness, in addition to speed, complexity, NIST calculations have been performed for texts and histogram calculations for different images were calculated and compared as well.</text>
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            <description>The file format, physical medium, or dimensions of the resource</description>
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                <text>application/pdf</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/24187</text>
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                <text>10.3991/ijim.v15i16.24187</text>
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            <description>A language of the resource</description>
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                <text>eng</text>
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            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
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                <text>International Association of Online Engineering (IAOE), Vienna, Austria</text>
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            </elementTextContainer>
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          <element elementId="47">
            <name>Rights</name>
            <description>Information about rights held in and over the resource</description>
            <elementTextContainer>
              <elementText elementTextId="43965">
                <text>Copyright (c) 2021 Ibrahim Malik ALattar, Abdul Monem S. Rahma</text>
              </elementText>
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            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
            <elementTextContainer>
              <elementText elementTextId="43966">
                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 16 (2021); pp. 63-78</text>
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              <elementText elementTextId="43967">
                <text>1865-7923</text>
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            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="43968">
                <text>Cryptography</text>
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                <text>GF(28)</text>
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                <text>GF(P)</text>
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                <text>Magic Square</text>
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                <text>Multi-level key.</text>
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          </element>
          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
            <elementTextContainer>
              <elementText elementTextId="43973">
                <text>A New Block Cipher Algorithm Using Magic Square of Order Five and Galois Field Arithmetic with Dynamic Size Block</text>
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          </element>
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            <name>Type</name>
            <description>The nature or genre of the resource</description>
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              <description>A name given to the resource</description>
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                <elementText elementTextId="15984">
                  <text>International Journal of Interactive Mobile Technologies (iJIM)</text>
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          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
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              <elementText elementTextId="22899">
                <text>Webb, Stephen</text>
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                <text>Malik, Manish</text>
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              <elementText elementTextId="22901">
                <text>Wilson, Mike</text>
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              <elementText elementTextId="22902">
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            <description>An account of the resource</description>
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                <text>For many HE institutions, a major factor inhibiting the wider deployment of computer-based objective assessment is the lack of suitable IT suites. The advent of pervasive wifi within HE campus environments, combined with the development of portable and low-cost browser-based devices, motivates the question of whether existing teaching spaces can be used as venues for computer-based assessment. This work describes the results of a pilot study aimed at investigating some of the technical and logistical issues surrounding this question and evaluating student perceptions of this particular implementation of an educational technology.</text>
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          <element elementId="42">
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            <description>The file format, physical medium, or dimensions of the resource</description>
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                <text>application/pdf</text>
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                <text>eng</text>
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              <elementText elementTextId="22908">
                <text>International Association of Online Engineering (IAOE), Vienna, Austria</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/4681/3615</text>
              </elementText>
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          <element elementId="47">
            <name>Rights</name>
            <description>Information about rights held in and over the resource</description>
            <elementTextContainer>
              <elementText elementTextId="22910">
                <text>Copyright (c) 2017 Stephen Webb, Manish Malik, Mike Wilson</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 9 No. 4 (2015); pp. 69-73</text>
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              <elementText elementTextId="22912">
                <text>1865-7923</text>
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            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="22913">
                <text>computer aided instruction</text>
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                <text>computer aided assessment</text>
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                <text>electronic learning</text>
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                <text>Can web thin clients be used to create flexible assessment spaces in a higher education setting?</text>
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              <description>An entity responsible for making the resource available</description>
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                <elementText elementTextId="1982">
                  <text>Centre for Land Warfare Studies, New Delhi, India</text>
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              <description>A language of the resource</description>
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                  <text>English</text>
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              <elementText elementTextId="847">
                <text>Malik, V.P.</text>
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              <elementText elementTextId="848">
                <text>2019-06-30</text>
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              <elementText elementTextId="849">
                <text>No nation-state can be built without first creating and inculcating nationalism. The Indian paradox is that we are an old society and civilisation but we are a new nation-state in the modern political sense. In its long history, India can be considered to have been a ‘nation-state' only a few times: during the Mauryan Empire (321-185 BC), in the Gupta Age (320-500 AD), the Mughal period (1527-1857 AD), and as the British India colonial empire (1857-1947 AD). The dynamics of these near whole or complete Indian nation-states has been that each time, it has risen out of a hotbed of internecine quarrels and fighting among small states: a tendency which is sometimes felt even today. As a nation-state, India comprises a myriad stream of culture; 22 scheduled languages, 200 dialects, a dozen ethnic groups, seven religious communities with several sects and sub-sects, and 68 socio-cultural subregions. That makes us great as well as a complex society and nation. This very paradox also poses challenges in building India as a nation.</text>
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                <text>https://ojs.indrastra.com/index.php/clawsjournal/article/view/82</text>
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                <text>Centre For Land Warfare Studies (CLAWS), New Delhi, India</text>
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                <text>CLAWS Journal; Vol. 12 No. 1 (2019): Summer 2019; 1-8</text>
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                <text>India</text>
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                <text>Today is the age of the Fourth Industrial Revolution. The current period of rapid, simultaneous, and systemic transformations driven by advances in science is reshaping industries, blurring geographical boundaries, challenging existing regulatory frameworks, and even redefining what it means to be human. Artificial Intelligence (AI) is the software engine that drives the Fourth Industrial Revolution. AI is creating targeted marketing, safer travel through self-driving cars, smarter weapons, and new efficiencies in manufacturing processes, supply chain management, and agricultural production. It holds the promise of solving some of the most pressing issues facing society but also presents challenges such as inscrutable “black box” algorithms, unethical use of data, and potential job displacement.</text>
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                <text>Copyright (c) 2018 Centre For Land Warfare Studies (CLAWS), New Delhi, India</text>
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                <text>CLAWS Journal; Vol. 11 No. 2 (2018): Winter 2018; 63-79</text>
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                <text>2319-5177</text>
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                <text>Artificial Intelligence</text>
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                <text>Artificial Intelligence in Armed Forces: An Analysis</text>
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                  <text>Journal of Naval Architecture and Marine Engineering</text>
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                <text>Mallik, Muhammad Saiful Islam</text>
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                <text>Uddin, Md. Ashraf</text>
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                <text>A large eddy simulation (LES) of a plane turbulent channel flow is performed at a Reynolds number Re? = 590 based on the channel half width, ? and wall shear velocity, u? by approximating the near wall region using differential equation wall model (DEWM). The simulation is performed in a computational domain of 2?? x 2? x&amp;nbsp;??. The computational domain is discretized by staggered grid system with 32 x 30 x 32 grid points. In this domain the governing equations of LES are discretized spatially by second order finite difference formulation, and for temporal discretization the third order low-storage Runge-Kutta method is used. Essential turbulence statistics of the computed flow field based on this LES approach are calculated and compared with the available Direct Numerical Simulation (DNS) and LES data where no wall model was used. Comparing the results throughout the calculation domain we have found that the LES results based on DEWM show closer agreement with the DNS data, especially at the near wall region. That is, the LES approach based on DEWM can capture the effects of near wall structures more accurately. Flow structures in the computed flow field in the 3D turbulent channel have also been discussed and compared with LES data using no wall model.</text>
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                <text>https://www.banglajol.info/index.php/JNAME/article/view/31266</text>
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                <text>Association of Naval Architects and Marine Engineers</text>
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                <text>Copyright (c) 2018 Journal of Naval Architecture and Marine Engineering</text>
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                <text>Journal of Naval Architecture and Marine Engineering; Vol. 15 No. 2 (2018); 75-89</text>
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                <text>2070-8998</text>
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                <text>1813-8535</text>
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                <text>Large eddy simulation of turbulent channel flow using differential equation wall model</text>
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