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                  <text>International Journal of Interactive Mobile Technologies (iJIM)</text>
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                <text>Alaidi , Abdul Hadi M.</text>
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                <text>Alrikabi, Haider Th.Salim</text>
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                <text>Aljazaery, Ibtisam A.</text>
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                <text>Dark web is a canopy concept that denotes any kind of illicit activities carried out by anonymous persons or organizations, thereby making it difficult to trace. The illicit content on the dark web is constantly updated and changed. The collection and classification of such illegal activities are challenging tasks, as they are difficult and time-consuming. This problem has in recent times emerged as an issue that requires quick attention from both the industry and academia. To this end, efforts have been made in this article a crawler that is capable of collecting dark web pages, cleaning them, and saving them in a document database, is proposed. The crawler carries out an automatic classification of the gathered web pages into five classes. The classifiers used in classifying the pages include Linear Support Vector Classifier (SVC), Naïve Bayes (NB), and Document Frequency (TF-IDF). The experimental results revealed that an accuracy rate of 92% and 81% were achieved by SVC and NB, respectively.</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/30209</text>
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                <text>Copyright (c) 2022 Haider Th.Salim Alrikabi, Abdul Hadi M.  Alaidi , Roa'a M.  Al_airaji, Ibtisam A.  Aljazaery, Saif Hameed  Abbood</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 10 (2022); pp. 122-139</text>
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                <text>1865-7923</text>
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                <text>Linear Support Vector Classifier, dark Web, Naïve Bayes</text>
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                <text>Dark Web Illegal Activities Crawling and Classifying Using Data Mining Techniques</text>
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                  <text>Journal of Naval Architecture and Marine Engineering</text>
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                <text>Islam, Mohammed</text>
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                <text>Jahra, Fatima</text>
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                <text>Hiscock, Scott</text>
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                <text>This paper presents the methodologies developed in order to quality control and analyze the data acquired in hydrodynamic seakeeping experiments of physical models in waves. In such experiments, the data file consists of wave elevations and directions, loads, motions, velocities and accelerations of one or multiple bodies. Additionally, mooring, slamming, sea-fastening, fender and other vessel specific load data may be acquired, which requires special analysis technique. Data products of such experiments are primarily consist of the basic statistics of each of the acquired data channels selected segments. Various wave statistics are produced to estimate the significant and other percentile of peaks/troughs/heights of each relevant data signal. This is done for the wave segment using zero crossing analysis. The response amplitude operator analysis is done through spectral analysis. Weibull analysis is done to estimate the maximum and minimum of an occurrence in a projected time. Analysis routines are written to incorporate each of these analysis techniques to produce results both in tabular and graphical formats. Analysis technique for decay experiments in multiple directions of motion, which are integral parts of any sea-keeping experiments, is also presented. Examples of all such analysis are provided where appropriate.</text>
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                <text>https://www.banglajol.info/index.php/JNAME/article/view/25347</text>
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                <text>10.3329/jname.v13i1.25347</text>
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                <text>Association of Naval Architects and Marine Engineers</text>
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                <text>Copyright (c) 2016 Journal of Naval Architecture and Marine Engineering</text>
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              <elementText elementTextId="67180">
                <text>Journal of Naval Architecture and Marine Engineering; Vol. 13 No. 1 (2016); 1-15</text>
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                <text>2070-8998</text>
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              <elementText elementTextId="67182">
                <text>1813-8535</text>
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              <elementText elementTextId="67183">
                <text>Data Analysis</text>
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                <text>Wave Experiments</text>
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                <text>Wave Statistics</text>
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                <text>ZCA Analysis</text>
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                <text>RAO Analysis</text>
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                <text>Weibull Analysis</text>
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                <text>Data analysis methodologies for hydrodynamic experiments in waves</text>
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            <description>The nature or genre of the resource</description>
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                <text>Data Analyis Methodologies for Physical Model Experiments</text>
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                  <text>International Journal of Interactive Mobile Technologies (iJIM)</text>
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              <elementText elementTextId="24982">
                <text>Akinwale, Olawale Babatunde</text>
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              <elementText elementTextId="24983">
                <text>Kehinde, Lawrence Olakunle</text>
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                <text>2017-05-22</text>
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                <text>Remote laboratories on mobile phones have been around for a few years now. This has greatly improved accessibility of these remote labs to students who cannot afford computers but have mobile phones. When money is a factor however (as is often the case with those who can’t afford a computer), the cost of use of these remote laboratories should be minimized. This work addressed this issue of minimizing the cost of use of the remote lab by making use of data compression for data sent between the user and remote lab.</text>
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              <elementText elementTextId="24992">
                <text>Copyright (c) 2017 Olawale Babatunde Akinwale, Lawrence Olakunle Kehinde</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 11 No. 4 (2017); pp. 95-113</text>
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                <text>1865-7923</text>
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                <text>Data compression</text>
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                <text>Lempel-Ziv-Welch</text>
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                <text>Data Compression for Remote Laboratories</text>
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              <elementText elementTextId="32077">
                <text>Prakancharoen, Somchai</text>
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                <text>2019-12-18</text>
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                <text>The objective of this research was to suggest some simple solution to increase database manipulation security. Based on advantage of Homomorphic encryption, user’s data in database is always encrypted by Homomorphic encryption algorithm such as Paillier. User’s data is manipulated or processed on many times such as addition, subtraction, multiplication and division. By the advantage of Homomorphic encryption algorithm, user’s data were no need to decrypt while it was manipulated therefore secrecy of data was still reserved. Unfortunately, Paillier’s Homomorphic encryption is normally coverage only addition and multiplication mathematical data operation. This paper suggests simple technique to enhance Pailler’s encryption algorithm to perform data operation as well in subtraction and division operation. Evaluation in suggested data base manipulation, DSM-PHE, indicates that its operation tasks was five operation times more than ordinary data base manipulation operation tasks, without any encryption. Therefore DSM-PHE should be especially used in more sensitive data.</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/11396</text>
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                <text>CLAWS Journal; Vol. 13 No. 2 (2020): Winter 2020; 235-239</text>
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                <text>Thailand is transforming its economy into a digital economy. Mobile payment (m-payment) is a core technology that helps the country phases from the manu-facturing-based economy into the digital economy. However, a question remains what factors influencing people to adopt mobile payment. Little literature focuses on users in Thailand. This study aims to determine factors associating with the decision-making process in selecting m-payment systems of respondents in Bangkok. The study addresses a research question. What do factors segregate m-payment adoption? 820 respondents were asked by using a questionnaire. Em-ployment of confirmatory factor analysis (CFA) developed the measurement showing acceptable validity and reliability. The study uses multinomial logistic regression to classify Technology Choices (TCs).  The results show low values of Pseudo R-Square, indicating that there is a lack of practical variables. Discus-sions and suggestions are addressed in this research.</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 13 No. 09 (2019); pp. 126-139</text>
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                <text>MTs Muhammadiyah Pekuncen is one of the MTs in the Banyumas Regency area where each year determines superior students and gets a 50% tuition discount for these students, with the aim of motivating students to become even better. Excellent students are students with high achievement, noble character and good behavior. Determination of superior students at MTs Muhammadiyah Pekuncen is still done manually, namely by deliberation between the teacher council which results in differences of opinion. Therefore we need a system that can determine superior students fairly without taking sides with any party and can be accepted by teachers and students. In this study, it will produce data on students who are selected to be superior students with 5 criteria including attitude, attendance, social, activity and achievement based on the AHP algorithm process. With the existence of a Decision Support System using the Analytical Hierarchy Process method it is proven to produce accurate values in determining superior students at Mts Muhammadiyah Pekuncen with a total value of 0.4464 a class IX student named Seftria Salsabila Putri was selected as a superior student.</text>
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                <text>https://pubs.ascee.org/index.php/iota/article/view/564</text>
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              <elementText elementTextId="15755">
                <text>Copyright (c) 2022 Internet of Things and Artificial Intelligence Journal</text>
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              <elementText elementTextId="15756">
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                <text>Internet of Things and Artificial Intelligence Journal; Vol. 2 No. 2 (2022): Volume 2, Issue 2, 2022 [May]; 122-132</text>
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              <elementText elementTextId="15758">
                <text>2774-4353</text>
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                <text>Excellent Student</text>
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                <text>Decision Support System for Muhammadiyah Pekuncen Islamic Junior High School in Determining Excellent Students Using the AHP Method</text>
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                  <text>Internet of Things and Artificial Intelligence Journal</text>
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            <name>Creator</name>
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              <elementText elementTextId="15767">
                <text>Khotimah, Khusnul</text>
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                <text>Anggraini, Lintang Wahyu</text>
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                <text>Alfirnanda, Weersa Talta</text>
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                <text>Tahyudin, Imam</text>
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                <text>2022-11-23</text>
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            <description>An account of the resource</description>
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                <text>The Indonesia Smart College Card Program (KIP-K) is a tuition assistance program (scholarship) from the Government through the Ministry of Education, Culture, Research and Technology (Kemdikbudristek). In the KIP-K scholarship selection process, criteria are needed to determine who is right to receive the KIP-K scholarship. This study aims to carry out the process of determining the ranking of KIP-K scholarship recipients based on the TOPSIS method. To determine scholarship recipients with outstanding achievements, Amikom Purwokerto University selects prospective scholarship recipients based on several criteria. The criteria used are Student DTKS Status, Parents' Income, Parents' Dependents, Average School Exams, Student Transportation Costs. The results obtained from this study are in the form of ranking obtained from the highest value to the lowest value. There were 112 prospective students who were entitled to get KIP-K scholarships out of a total of 314 applicants.</text>
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            <name>Identifier</name>
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            <elementTextContainer>
              <elementText elementTextId="15774">
                <text>https://pubs.ascee.org/index.php/iota/article/view/566</text>
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              <elementText elementTextId="15775">
                <text>10.31763/iota.v2i4.566</text>
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            <description>A language of the resource</description>
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              <elementText elementTextId="15776">
                <text>eng</text>
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            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
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              <elementText elementTextId="15777">
                <text>Association for Scientific Computing, Electronics, and Engineering (ASCEE)</text>
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          <element elementId="46">
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            <description>A related resource</description>
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                <text>https://pubs.ascee.org/index.php/iota/article/view/566/162</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="47">
            <name>Rights</name>
            <description>Information about rights held in and over the resource</description>
            <elementTextContainer>
              <elementText elementTextId="15779">
                <text>Copyright (c) 2022 Internet of Things and Artificial Intelligence Journal</text>
              </elementText>
              <elementText elementTextId="15780">
                <text>https://ascee.org/</text>
              </elementText>
            </elementTextContainer>
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          <element elementId="48">
            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
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              <elementText elementTextId="15781">
                <text>Internet of Things and Artificial Intelligence Journal; Vol. 2 No. 4 (2022): Vol. 2 No. 4 (2022): Volume 2 Issue 4, 2022 [November]; 279-290</text>
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              <elementText elementTextId="15782">
                <text>2774-4353</text>
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            <description>The topic of the resource</description>
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              <elementText elementTextId="15783">
                <text>DSS</text>
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                <text>MOORA</text>
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                <text>Students</text>
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                <text>Criteria</text>
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                <text>Field practice</text>
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            <description>A name given to the resource</description>
            <elementTextContainer>
              <elementText elementTextId="15788">
                <text>Decision Support System for Selecting KIP-K Recipients at Amikom University, Purwokerto Using the TOPSIS Method</text>
              </elementText>
            </elementTextContainer>
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            <description>The nature or genre of the resource</description>
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          <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
          <elementContainer>
            <element elementId="50">
              <name>Title</name>
              <description>A name given to the resource</description>
              <elementTextContainer>
                <elementText elementTextId="2304">
                  <text>Artha Journal of Social Sciences</text>
                </elementText>
              </elementTextContainer>
            </element>
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      </elementSetContainer>
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    <itemType itemTypeId="14">
      <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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    <elementSetContainer>
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        <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
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          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="9875">
                <text>S, Shantharaju</text>
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            <name>Date</name>
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                <text>2020-12-10</text>
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            <description>An account of the resource</description>
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                <text>The fluidity of time and space, diverse collection, and personalized recommendations of streaming (OTT players) would mean a lot to a viewer looking for instant entertainment. On the other hand, such transitions from traditional viewing platforms pose a diverse challenge to everyone involved in entertainment productions. The remote select button is replaced with a scrolling option, but the difference is in the platform's 'thinking' or analytical algorithm, which was not part of traditional TV or Cinema hall. This global shift might be beneficial to a few and yet, lowers the number of personnel involved in productions. This is a conceptual paper looking into the interaction between streaming and the entertainment industry labour.</text>
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            <description>The file format, physical medium, or dimensions of the resource</description>
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                <text>https://journals.christuniversity.in/index.php/artha/article/view/2709</text>
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                <text>10.12724/ajss.54.2</text>
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                <text>Centre for Publications, CHRIST (Deemed to be University), Bangalore</text>
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                <text>https://journals.christuniversity.in/index.php/artha/article/view/2709/1827</text>
              </elementText>
            </elementTextContainer>
          </element>
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            <description>Information about rights held in and over the resource</description>
            <elementTextContainer>
              <elementText elementTextId="9884">
                <text>Copyright (c) 2020 Artha Journal of Social Sciences</text>
              </elementText>
              <elementText elementTextId="9885">
                <text>http://creativecommons.org/licenses/by-nc/4.0</text>
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              <elementText elementTextId="9886">
                <text>Artha Journal of Social Sciences; Vol. 19 No. 3 (2020): Artha Journal of Social Sciences; 21-35</text>
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              <elementText elementTextId="9887">
                <text>0000-0000</text>
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              <elementText elementTextId="9888">
                <text>0975-329X</text>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="9889">
                <text>Streaming</text>
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                <text>Netflix</text>
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                <text>Entertainment</text>
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                <text>Labour</text>
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                <text>Declining Bargain Power: Streaming, Production, and Entertainment Labour</text>
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