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    <id>3302</id>
    <completedYear>2007</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>70</pageFirst>
    <pageLast>73</pageLast>
    <pageNumber/>
    <edition/>
    <issue>6</issue>
    <volume>68</volume>
    <type>article</type>
    <publisherName>Kaunas University of Technology</publisherName>
    <publisherPlace>Kaunas</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2025-04-07</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Autonomous mobile robots for outdoor tasks</title>
    <abstract language="eng">This paper presents a low-cost hardware platform for outdoor robots, being suitable for education, industrial prototyping and private use. The choice of components is&#13;
discussed, including platform, sensors and controller as well as GPS and image processing hardware. Furthermore, a software approach is proposed, allowing students and researchers to easily implement own algorithms for localization, navigation and the tasks to fulfill. Several robots can be integrated in a framework which connects various different hardware platforms, called the BOSPORUS network. Together with other components, they form an intelligent network for gathering sensor and image data, sensor data fusion, navigation and control of mobile platforms. The architecture of a reference platform on the campus of the Brandenburg University of Applied Sciences is presented and evaluated.</abstract>
    <parentTitle language="eng">Mechanika</parentTitle>
    <identifier type="doi">10.5755/j02.mech.36230</identifier>
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    <licence>Creative Commons - CC BY - Namensnennung 4.0</licence>
    <author>Harald Loose</author>
    <collection role="open_access" number="">open_access</collection>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <thesisPublisher>Technische Hochschule Brandenburg</thesisPublisher>
  </doc>
  <doc>
    <id>3311</id>
    <completedYear>2023</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>354-1</pageFirst>
    <pageLast>354-14</pageLast>
    <pageNumber/>
    <edition/>
    <issue>3</issue>
    <volume>35</volume>
    <type>article</type>
    <publisherName>Society for Imaging Science and Technology (IS&amp;T)</publisherName>
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    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2025-04-10</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Importance of OSINT/SOCMINT for modern disaster management evaluation - Australia, Haiti, Japan</title>
    <abstract language="eng">Open-source technologies (OSINT) and Social Media Intelligence (SOCMINT) are becoming increasingly popular with investigative and government agencies, intelligence services, media companies, and corporations. These OSINT and SOCMINT technologies use sophisticated techniques and special tools to efficiently analyze the continually growing sources of information. There is a great need for training and further education in the OSINT field worldwide. This report describes the importance of open source or social media intelligence for evaluating disaster management. It also gives an overview of the government work in Australia, Haiti, and Japan for disaster management using various OSINT tools and platforms. Thus, decision support for using OSINT and SOCMINT tools is given, and the necessary training needs for investigators can be better estimated.</abstract>
    <parentTitle language="eng">Electronic Imaging</parentTitle>
    <identifier type="doi">10.2352/EI.2023.35.3.MOBMU-354</identifier>
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    <enrichment key="opus.source">publish</enrichment>
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    <licence>Keine Nutzungslizenz vergeben - es gilt das deutsche Urheberrecht</licence>
    <author>Nazneen Mansoor</author>
    <author>Klaus Schwarz</author>
    <author>Rainer Creutzburg</author>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <thesisPublisher>Technische Hochschule Brandenburg</thesisPublisher>
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  <doc>
    <id>3316</id>
    <completedYear>2023</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>356-1</pageFirst>
    <pageLast>356-10</pageLast>
    <pageNumber>10</pageNumber>
    <edition/>
    <issue>3</issue>
    <volume>35</volume>
    <type>article</type>
    <publisherName>Society for Imaging Science and Technology (IS&amp;T)</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2025-04-10</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Practical OSINT investigation - Similarity calculation using Reddit user profile data</title>
    <abstract language="eng">This paper presents a practical Open Source Intelligence (OSINT) use case for user similarity measurements with the use of open profile data from the Reddit social network. This PoC work combines the open data from Reddit and the part of the state-of-the-art BERT model. Using the PRAW Python library, the project fetches comments and posts of users. Then these texts are converted into a feature vector - representation of all user posts and comments. The main idea here is to create a comparable user's pair similarity score based on their comments and posts. For example, if we fix one user and calculate scores of all mutual pairs with other users, we will produce a total order on the set of all mutual pairs with that user. This total order can be described as a degree of written similarity with this chosen user. A set of "similar" users for one particular user can be used to recommend to the user interesting for him people. The similarity score also has a "transitive property": if $user_1$ is "similar" to $user_2$ and $user_2$ is similar to $user_3$ then inner properties of our model guarantees that $user_1$ and $user_3$ are pretty "similar" too. In this way, this score can be used to cluster a set of users into sets of "similar" users. It could be used in some recommendation algorithms or tune already existing algorithms to consider a cluster's peculiarities. Also, we can extend our model and calculate feature vectors for subreddits. In that way, we can find similar to the user's subreddits and recommend them to him.</abstract>
    <parentTitle language="eng">Electronic Imaging</parentTitle>
    <identifier type="doi">10.2352/EI.2023.35.3.MOBMU-356</identifier>
    <enrichment key="PeerReviewNachweis">ja</enrichment>
    <enrichment key="opus.source">publish</enrichment>
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    <licence>Keine Nutzungslizenz vergeben - es gilt das deutsche Urheberrecht</licence>
    <author>Valeria Vishnevskaya</author>
    <author>Klaus Schwarz</author>
    <author>Reiner Creutzburg</author>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <thesisPublisher>Technische Hochschule Brandenburg</thesisPublisher>
  </doc>
  <doc>
    <id>3317</id>
    <completedYear>2023</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>355-1</pageFirst>
    <pageLast>355-15</pageLast>
    <pageNumber/>
    <edition/>
    <issue>3</issue>
    <volume>35</volume>
    <type>article</type>
    <publisherName>Society for Imaging Science and Technology (IS&amp;T)</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2025-04-10</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Practical OSINT investigation in Twitter utilizing AI-based aggressiveness analysis</title>
    <abstract language="eng">Open-source intelligence is gaining popularity due to the rapid development of social networks. There is more and more information in the public domain. One of the most popular social networks is Twitter. It was chosen to analyze the dependence of changes in the number of likes, reposts, quotes and retweets on the aggressiveness of the post text for a separate profile, as this information can be important not only for the owner of the channel in the social network, but also for other studies that in some way influence user accounts and their behavior in the social network. Furthermore, this work includes a detailed analysis and evaluation of the Tweety library capabilities and situations in which it can be effectively applied. Lastly, this work includes the creation and description of a compiled neural network whose purpose is to predict changes in the number of likes, reposts, quotes, and retweets from the aggressiveness of the post text for a separate profile.</abstract>
    <parentTitle language="eng">Electronic Imaging</parentTitle>
    <identifier type="doi">10.2352/EI.2023.35.3.MOBMU-355</identifier>
    <enrichment key="PeerReviewNachweis">ja</enrichment>
    <enrichment key="opus.source">publish</enrichment>
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    <licence>Keine Nutzungslizenz vergeben - es gilt das deutsche Urheberrecht</licence>
    <author>Artem Skylar</author>
    <author>Klaus Schwarz</author>
    <author>Reiner Creutzburg</author>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <thesisPublisher>Technische Hochschule Brandenburg</thesisPublisher>
  </doc>
  <doc>
    <id>3314</id>
    <completedYear>2023</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>357-1</pageFirst>
    <pageLast>357-12</pageLast>
    <pageNumber/>
    <edition/>
    <issue>3</issue>
    <volume>35</volume>
    <type>article</type>
    <publisherName>Society for Imaging Science and Technology (IS&amp;T)</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2025-04-10</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Open-source Intelligence (OSINT) investigation in Facebook</title>
    <abstract language="eng">Open Source Intelligence (OSINT) has come a long way, and it is still developing ideas, and lots of investigations are yet to happen in the near future. The main essential requirement for all the OSINT investigations is the information that is valuable data from a good source. This paper discusses various tools and methodologies related to Facebook data collection and analyzes part of the collected data. At the end of the paper, the reader will get a deep and clear insight into the available techniques, tools, and descriptions about tools that are present to scrape the data out of the Facebook platform and the types of investigations and analyses that the gathered data can do.</abstract>
    <parentTitle language="eng">Electronic Imaging</parentTitle>
    <identifier type="doi">10.2352/EI.2023.35.3.MOBMU-357</identifier>
    <enrichment key="PeerReviewNachweis">ja</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <licence>Keine Nutzungslizenz vergeben - es gilt das deutsche Urheberrecht</licence>
    <author>Pranesh Kumar Narasimhan</author>
    <author>Chinmay Bhosale</author>
    <author>Muhammad Hasban Pervez</author>
    <author>Najiba Zainab Naqvi</author>
    <author>Mert Ilhan Ecevit</author>
    <author>Klaus Schwarz</author>
    <author>Reiner Creutzburg</author>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <thesisPublisher>Technische Hochschule Brandenburg</thesisPublisher>
  </doc>
  <doc>
    <id>3309</id>
    <completedYear>2023</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>249</pageFirst>
    <pageLast>257</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>IOS Press</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2025-04-09</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Evaluating Interoperability in German Critical Incident Reporting Systems</title>
    <abstract language="eng">In industrialised countries, one in ten patients suffers harm during hospitalization. Critical Incident Reporting Systems (CIRS) aim to minimize this by learning from errors and identifying potential risks. However, a lack of interoperability among the 16 CIRS in Germany hampers their effectiveness.</abstract>
    <parentTitle language="eng">German Medical Data Sciences 2023 – Science. Close to People. Proceedings of the 68th Annual Meeting of the German Association of Medical Informatics, Biometry, and Epidemiology e.V. (gmds) 2023, Heilbronn, Germany</parentTitle>
    <identifier type="doi">10.3233/SHTI230722</identifier>
    <enrichment key="PeerReviewNachweis">ja</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Creative Commons - CC BY-NC - Namensnennung - Nicht kommerziell 4.0</licence>
    <author>Laura Tetzlaff</author>
    <author>Anne-Maria Purohit</author>
    <author>Jacob Spallek</author>
    <author>Christine Holmberg</author>
    <author>Thomas Schrader</author>
    <collection role="open_access" number="">open_access</collection>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
  </doc>
  <doc>
    <id>3331</id>
    <completedYear>2024</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>7</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>PMLR</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2025-05-08</completedDate>
    <publishedDate>2024-01-23</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Clifford Group Equivariant Neural Network Layers for Protein Structure Prediction</title>
    <abstract language="eng">We employ Clifford Group Equivariant Neural Network (CGENN) layers to predict protein coordinates in a Protein Structure Prediction (PSP) pipeline. PSP is the estimation of the 3D structure of a protein, generally through deep learning architectures. Information about the geometry of the protein chain has been proven to be crucial for accurate predictions of 3D structures. However, this information is usually flattened as machine learning features that are not representative of the geometric nature of the problem. Leveraging recent advances in geometric deep learning, we redesign the 3D projector part of a PSP architecture with the addition of CGENN layers . CGENNs can achieve better generalization and robustness when dealing with data that show rotational or translational invariance such as protein coordinates, which are independent of the chosen reference frame. CGENNs inputs, outputs, weights and biases are objects in the Geometric Algebra of 3D Euclidean space, i.e. G3,0,0, and hence are interpretable from a geometrical perspective. We test 6 approaches to PSP and show that CGENN layers increase the accuracy in term of GDT scores by up to 2.1\%, with fewer trainable parameters compared to linear layers and give a clear geometric interpretation of their outputs.</abstract>
    <parentTitle language="eng">Northern Lights Deep Learning Conference, VOL 233, 09-11 Januar 2024, Tromso, Norwegen</parentTitle>
    <identifier type="url">https://proceedings.mlr.press/v233/pepe24a/pepe24a.pdf</identifier>
    <enrichment key="PeerReviewNachweis">ja</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0</licence>
    <author>Alberto Pepe</author>
    <author>Sven Buchholz</author>
    <author>Joan Lasenby</author>
    <collection role="open_access" number="">open_access</collection>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
  </doc>
  <doc>
    <id>2816</id>
    <completedYear>2022</completedYear>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>24</volume>
    <type>article</type>
    <publisherName>IOP</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2022-11-10</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">The effect of obstacles near a silo outlet on the discharge of soft spheres</title>
    <parentTitle language="deu">New Journal of Physics</parentTitle>
    <identifier type="doi">10.1088/1367-2630/ac8bea</identifier>
    <enrichment key="PeerReviewNachweis">ja</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0</licence>
    <author>Jing Wang</author>
    <author>Kirsten Harth</author>
    <author>Dmitry Puzyrev</author>
    <author>Ralf Stannarius</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>fluid dynamics</value>
    </subject>
    <collection role="ddc" number="532">Mechanik der Fluide; Mechanik der Flüssigkeiten</collection>
    <collection role="ddc" number="621">Angewandte Physik</collection>
    <collection role="open_access" number="">open_access</collection>
    <collection role="institutes" number="">Fachbereich Technik</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <thesisPublisher>Technische Hochschule Brandenburg</thesisPublisher>
  </doc>
  <doc>
    <id>2793</id>
    <completedYear>2022</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>3193</pageFirst>
    <pageLast>3205</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>16</volume>
    <type>article</type>
    <publisherName>Royal Society of Chemistry</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2022-04-25</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Shape instabilities of islands in smectic films under lateral compression</title>
    <parentTitle language="eng">Soft Matter</parentTitle>
    <identifier type="doi">10.1039/D2SM00144F</identifier>
    <identifier type="issn">1744-6848</identifier>
    <enrichment key="PeerReviewNachweis">ja</enrichment>
    <author>Amine Missaoui</author>
    <author>Kirsten Harth</author>
    <author>Torsten Trittel</author>
    <author>Christoph Klopp</author>
    <author>Ralf Stannarius</author>
    <author>Emanuelle Lacaze</author>
    <collection role="ddc" number="540">Chemie und zugeordnete Wissenschaften</collection>
    <collection role="institutes" number="">Fachbereich Technik</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <thesisPublisher>Technische Hochschule Brandenburg</thesisPublisher>
  </doc>
  <doc>
    <id>2995</id>
    <completedYear>2022</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>146</pageFirst>
    <pageLast>155</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName>Royal Society of Chemistry</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2023-12-14</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Smectic free-standing films under fast lateral compression</title>
    <abstract language="eng">Smectic films in a collapsing catenoid develop spontaneous wrinkling patterns like solid sheets.&#13;
&#13;
Smectic freely-suspended films can wrinkle like solid sheets. This has been demonstrated earlier with shape-fluctuating smectic bubbles. Here, we exploit the collapse of smectic catenoid films with a central equatorial film to expose the latter to rapid lateral compression. Wrinkle formation is observed in the planar film and the thickness dependence of the undulation wavelength is measured. In addition to the central film, its border undergoes an undulation instability as well.</abstract>
    <parentTitle language="eng">Soft Matter</parentTitle>
    <identifier type="url">http://xlink.rsc.org/?DOI=D1SM01207J</identifier>
    <identifier type="doi">10.1039/D1SM01207J</identifier>
    <identifier type="issn">1744-683X, 1744-6848</identifier>
    <enrichment key="PeerReviewNachweis">ja</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0</licence>
    <author>Christoph Klopp</author>
    <author>Torsten Trittel</author>
    <author>Kirsten Harth</author>
    <author>Ralf Stannarius</author>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <thesisPublisher>Technische Hochschule Brandenburg</thesisPublisher>
  </doc>
  <doc>
    <id>2974</id>
    <completedYear>2023</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>33</pageFirst>
    <pageLast>49</pageLast>
    <pageNumber>16</pageNumber>
    <edition/>
    <issue>76/2023</issue>
    <volume/>
    <type>article</type>
    <publisherName>Springer Link</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2023-12-12</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Analytical estimation of thermomechanical distortion and interface layer thickness for gas metal arc lap joining of dissimilar sheets</title>
    <parentTitle language="eng">Welding in the World</parentTitle>
    <identifier type="doi">10.1007/s40194-01426-x</identifier>
    <identifier type="issn">432288</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="PeerReviewNachweis">ja</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0</licence>
    <author>Atanu Das</author>
    <author>Prashtan Kumar Chaurasia</author>
    <author>Gopi K. Mandal</author>
    <author>Sven-Frithjof Goecke</author>
    <author>Amitava De</author>
    <collection role="institutes" number="">Fachbereich Technik</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <thesisPublisher>Technische Hochschule Brandenburg</thesisPublisher>
  </doc>
</export-example>
