Zum Hauptinhalt

Course site for "Automated Theorem Proving" in the winter term 2017/18

Die Kommunikationsfähigkeit der Bevölkerung untereinander ist für die Bewältigung von Krisen von höchster Bedeutung. In dieser Veranstaltung wird der Aufbau von drahtlosen Kommunikationsnetzen von Null behandelt, d.h. unter der Annahme, dass keinerlei Kommunikationsinfrastruktur mehr vorhanden ist. Die Veranstaltung vermittelt theoretische Grundlagen aus den Bereichen der Nachrichtentechnik und des Amateurfunks und vertieft diese um die nötigen Kenntnisse, um Netze für den Krisenfall zu entwerfen und praktisch zu realisieren. Die vorgestellten Verfahren umfassen dabei Reichweiten von lokaler Kommunikation bis hin zur Kommunikation um den ganzen Globus, ohne auf bestehende Infrastruktur angewiesen zu sein. 
Theoretische Übungen sowie das Durchführen von Messungen, der Aufbau von Schaltungen und die Vorführung von Funkverfahren in unserer Laborumgebung vertiefen die Veranstaltung. 

  • Signale, Wellenausbreitung, Antennen und elektrotechnische Grundlagen 
  • Verfahren zur Modulation und Demodulation analoger und digitaler Signale (OFDM, ATV/SSTV, Packet Radio, SSB, ...) 
  • Systemaspekte für Kommunikation im Krisenfall 
  • Entwurf und praktischer Aufbau von drahtlosen Kommunikationssystemen für den Krisenfall von Null

The lecture offers an introduction into the perspectives, problems, methods and techniques of text technology. All examples and tutorials are based on the programming language Python.

More information: https://www.ukp.tu-darmstadt.de/teaching/courses/ws-1718/foundations-of-language-technologies/

Lehrinhalte:
Die Vorlesung gliedert sich in zwei Teile. In der ersten Hälfte der Vorlesung wird die Funktionsweise von Geräten, welche medizinische Bilder liefern (CT, MRI, PET, SPECT, Ultraschall), erklärt.
In der zweiten Hälfte werden verschiedene Bildverarbeitungsmethoden erklärt, welche typischerweise für die Bearbeitung medizinischer Bilder eingesetzt werden.

Qualifikationsziele / Lernergebnisse:
Nach erfolgreichem Besuch der Veranstaltung haben die Studierenden einen Überblick über die Funktionsweise und die Möglichkeiten der modernen medizinischen Bildverarbeitung. Studierende sind dazu in der Lage, einfache bis mittlere medizinische Bildverarbeitungsaufgaben selbständig zu lösen.

Literatur:
1) Heinz Handels: Medizinische Bildverarbeitung
2) Gonzalez/Woods: Digital Image Processing (last edition)
3) Bernd Jähne: Digitale Bildverarbeitung. 6. überarbeitete und erweiterte Auflage. Springer, Berlin u. a. 2005, ISBN 3-540-24999-0
4) Kristian Bredies, Dirk Lorenz: Mathematische Bildverarbeitung. Einführung in Grundlagen und moderne Theorie. Vieweg+Teubner, Wiesbaden 2011, ISBN 978-3-8348-1037-3

Voraussetzungen:
Mathematische Grundlagen sind dringend empfehlenswert. Ferner wird empfohlen, die Vorlesung „Bildverarbeitung“ vorher besucht zu haben.

Weitere Informationen:
V 3CP/2SWS, jedes Wintersemester

Natural Language Processing and the Web

Teaching Staff

We currently do not have fixed office hours, so please contact us by mail to get an appointment.

Organization

  • Lecture: Tuesday 08:00-09:40, Room S202 / C205 starting October 17
  • Practice class: Thursday 16:15-17:55, Room S202/C120 starting October 26

The learning material is available from the Moodle eLeaning platform.

Registration

If you plan to participate in this course, please register on Tucan.

Requirements

To pass, each student has to take the written exam at the end of the semester.

There will also be a project in the practice class which will contribute to your overall grade.

Exam

  • Date/Time: 27/2/2018 15:00-17:00
  • Room: S202/C205 - Bosch Hörsaal

Course content

The Web contains more than 10 billion indexable web pages, which can be retrieved via search queries. The lecture will present Natural Language Processing (NLP) methods to (1) automatically process large amounts of unstructured text from the web and (2) analyse the use of Web data as a resource for other NLP tasks.

Processing of unstructured web content

  • Introduction
  • NLP Basics - Tokenisation, Part of Speech Tagging, Chunking, Stemming, Lemmatization
  • Web contents and their characteristics - diverse genres of web contents, e.g. personal web sites, news sites, blogs, forums, wikis
  • Web contents and their characteristics - continued

NLP applications for the web

  • Information retrieval - introduction to the basics of information retrieval
  • Web information retrieval - natural language interfaces for web information retrieval
  • Question answering (QA): Factoid QA, Knowledge Base QA, Community QA
  • Crowdsourcing
  • Text Structuring

    Literature

    • Kai-Uwe Carstensen, Christian Ebert, Cornelia Endriss, Susanne Jekat, Ralf Klabunde, Computerlinguistik und Sprachtechnologie. Eine Einführung, Heidelberg: Spektrum-Verlag, März 2010. (3. Auflage) I
    • T. Götz & O. Suhre, Design and implementation of the UIMA Common Analysis System, IBM Systems Journal, 2004, 43, 476-489.
    • Adam Kilgarriff & Gregory Grefenstette, Introduction to the special issue on the web as corpus, Computational Linguistics, MIT Press, 2003, 29, 333-347
    • Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze, Introduction to Information Retrieval, Cambridge University Press. 2008.

    Physical Layer Security Verfahren zur Absicherung drahtloser Kommunikation versprechen eine informationstheoretische Sicherheit auf der Bitübertragungsschicht (Physical Layer). Die integrierte Veranstaltung betrachtet die Theorie und Praxis von Physical Layer Security. Hierzu werden ausgewählte theoretische Grundlagen eingeführt und die Übertragung dieser Grundlagen hin zu praktikablen Lösungen diskutiert. Angriffe auf (praktische) Physical Layer Security-Verfahren werden erörtert. Theoretische und praktische Übungen sowie die Vorstellung ausgewählter Forschungsergebnisse in Seminarvorträgen vertiefen die Veranstaltung.

    Lerninhalte:
    - Eigenschaften des Physical Layer
    - Grundlagen informationstheorischer Sicherheit und Abgrenzung zur Kryptographie
    - Physical Layer Security Verfahren (u.a. Cooperative Jamming, Orthogonal Blinding, Zero-Forcing, Interference Alignment, Key Extraction)
    - Praktische Aspekte von Physical Layer Security Verfahren
    - Praktische Implementierung von Physical Layer Security-Verfahren mit Software Defined Radios
    - Ausgewählte aktuelle Ansätze zu Physical Layer Security


    Objectives

    The integrated course Protection in Networked Systems - Trust, Resilience, and Privacy covers the topics of computational trust, resilient and anonymous networks, and collaborative defense mechanisms. By attending this course, the students will be able to understand the problems and solutions in the context of networked systems. The course content will consider the concept of End-to-End systems emphasizing on users, devices, networks, and applications or services.

    Content

    • Protection in Networked Systems: background, motivation, challenges
    • Trust (Computational Trust): models and mechanisms
    • Trust (Computational Trust): application in PKI, Cloud Computing, Reputation Systems, and Web Services
    • Trust: regret management and device comfort
    • Privacy: privacy definitions, models, data anonymity, communication anonymity
    • Privacy & Trust: privacy-preserving trust models, mechanisms, and application to IDM
    • Resilience: models, network intrusion detection systems, collaborative intrusion detection systems, honeypots, botnets, secure routing

    Literature

    • Trust and Reputation for Service-Oriented Environments: Technologies For Building Business Intelligence And Consumer Confidence, Elizabeth Chang, Tharam Dillon, and Farookh K. Hussain, 374 pages, 2006. ISBN: 978-0-470-01547-6
    • Detailing Reviews and Ratings for Trust-Enhanced Composition, Florian Volk, 272 pages, 2015, ISBN: 9783736991668 (print), 9783736981669 (e-book)
    • On anonymity in an electronic society: A survey of anonymous communication systems, Matthew Edman and Bülent Yener, ACM Computing Surveys, Vol. 42, Issue 1, 2009.
    • Taxonomy and Survey of Collaborative Intrusion Detection, Emmanouil Vasilomanolakis, Shankar Karuppayah, Max Mühlhäuser, Mathias Fischer, ACM Computing Surveys, Vol. 47 Issue 4, 2015.
    • Selected book chapters and scientific publications

    Prerequisites

    Knowledge of IT Security and Mathematics according to 1-4 semester of B.Sc. Computer Science

    This course introduces the fundamental concepts and computational paradigms of scalable data management systems. The focus of this course is on the systems-oriented aspects and internals of such systems for storing, updating, querying, and analyzing large datasets. 

    Topics include: 

    Database Architectures 
    Parallel and Distributed Databases 
    Data Warehousing 
    MapReduce and Hadoop 
    Spark and its Ecosystem 
    Optional: NoSQL Databases, Stream Processing, Graph Databases, Scalable Machine Learning

    Welcome to the Secure Mobile Networking Project (20-00-0553-pp) and Lab Exercise (20-00-0552-pr). These courses deal with cutting edge development topics in the area of network security with particular focus on mobile networked systems. Beside a general overview it provides a deep insight into a special development topic. The topics are selected according to the specific working areas of the participating researchers and convey technical and basic scientific competences in one or more research topics.

    The Seminar and Advanced Seminar on Networking, Security, Mobility, and Wireless Communications cover current research that is considered highly relevant for the future development of the given topic areas. Goal of the seminar is to explore the aforementioned research area by studying, critically analyzing and discussing, summarizing, and presenting selected first-rate research articles. This instance of the learning platform Moodle serves as the central information hub for both courses. 

    Arguing is a fundamental aspect of human communication and reasoning. We may argue with our friends about which movie to watch, with experts about the long-term effects of global warming, or with ourselves about which of various job offers to take. But what exactly is an argument? What components is it made of? What is the interplay between different arguments? And what makes an argument convincing?

    In recent years, Natural Language Processing (NLP) and Machine Learning methods have been applied to try and answer these question, resulting in a new research area called “Argument Mining”. This seminar will introduce some theoretical ideas and assumptions underlying many of the works in Argument Mining and review in depth the latest research in the field.

    Topics covered in the seminar are, among others, the automatic detection of claims and evidence in text, the identification of contradictory and supporting arguments in debates, how to predict the convincingness of arguments, and how to judge if two arguments are making the same point. We will also discuss exciting applications of Argument Mining research, including detecting deceptive reviews, predicting the winner of a debate, and automatically grading essays.


    In this course, you will ...

    • learn how companies, public administration, and end-consumers can benefit from state-of-the-art ubiquitous computing technologies, incl. auto-id, smart labels, sensors, embedded devices, etc. attached to everyday objects and things.
    • understand underlying technologies, their advantages, and limitations.
    • identify technologies' economic potential for business processes.
    • demonstrate how integration works between the real and the virtual world as it is modeled in software systems today.


    This course is only used for group exercise! Information regarding lectures, exam, etc., will be published on the course website. (https://www.tk.informatik.tu-darmstadt.de/de/teaching/wintersemester-201718/ubiquitous-computing-in-geschaeftsprozessen/)


    Course Type:

    Lab

    Course:

    P4 / 4 SWS / 6 CP (ECTS)

    Lecturer: 

    Prof. Dr. Melanie Volkamer

    Number of the lecture: 

    20-00-0787

    Organisation:Karola Marky


    Requirements: 

    See below


    Our Lab is for students of computer science, mathematics, business information systems and electrical engineering and information technology (etit).

    Available Topics

    The available topics will be presented in the Kick-Off meeting. The slides will be available here and on our website for reference after the Kick-Off. The general areas of interest in this semester will be Privacy Friendly Android Apps (have a look at those already in the PlayStore and F-Droid (look for "Privacy Friendly App")).

    In case you missed the Kick-Off meeting, you can still contact us if you would like to participate in the lab, but please look at the slides first!

    Learning Goal

    The skill to complete a development task professionally meeting prior specifications and adequately presenting the results. The task is focussed on the extension or development of a mobile application for Android. Examples for apps developed within this lab can be found in the Playstore or F-Droid (look for "Privacy Friendly App").

    Requirements

    • Experiences with the respective programming languages (Java, Android is a plus)
    • Knowledge in the field of usability and social aspects of technology are a plus
    • Knowledge in the field of it security are a plus
    • Experiences with Git are a plus (usage is expected)
    • Approval to distribute the code under an open source license (if not stated otherwise, we will publish the results on GitHub when development is complete)