TY  - GEN
A1  - Krawietz, Marian
A1  - Goebel, Jan
A1  - Albrecht, Sophia
A1  - Class, Fabian
A1  - Kohler, Ulrich
T1  - Leben in der ehemaligen DDR
BT  - Zusatzfragebogen im Rahmen der Befragung "Leben in Deutschland 2018" / Living in the GDR
Y1  - 2019
U6  - https://doi.org/10.5684/soep.ddr18
PB  - German Institute for Economic Research (DIW Berlin)
CY  - Berlin
ER  - 
TY  - GEN
A1  - Bin Tareaf, Raad
A1  - Berger, Philipp
A1  - Hennig, Patrick
A1  - Meinel, Christoph
T1  - Personality exploration system for online social networks
BT  - Facebook brands as a use case
T2  - 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI)
N2  - User-generated content on social media platforms is a rich source of latent information about individual variables. Crawling and analyzing this content provides a new approach for enterprises to personalize services and put forward product recommendations. In the past few years, brands made a gradual appearance on social media platforms for advertisement, customers support and public relation purposes and by now it became a necessity throughout all branches. This online identity can be represented as a brand personality that reflects how a brand is perceived by its customers. We exploited recent research in text analysis and personality detection to build an automatic brand personality prediction model on top of the (Five-Factor Model) and (Linguistic Inquiry and Word Count) features extracted from publicly available benchmarks. The proposed model reported significant accuracy in predicting specific personality traits form brands. For evaluating our prediction results on actual brands, we crawled the Facebook API for 100k posts from the most valuable brands' pages in the USA and we visualize exemplars of comparison results and present suggestions for future directions.
KW  - Big Five Model
KW  - Brand Personality
KW  - Personality Prediction
KW  - Machine Learning
KW  - Social Media Analysis
Y1  - 2019
SN  - 978-1-5386-7325-6
U6  - https://doi.org/10.1109/WI.2018.00-76
SP  - 301
EP  - 309
PB  - IEEE
CY  - New York
ER  - 
TY  - GEN
A1  - Andjelkovic, Marko
A1  - Babic, Milan
A1  - Li, Yuanqing
A1  - Schrape, Oliver
A1  - Krstić, Miloš
A1  - Kraemer, Rolf
T1  - Use of decoupling cells for mitigation of SET effects in CMOS combinational gates
T2  - 2018 25th IEEE International Conference on Electronics, Circuits and Systems (ICECS)
N2  - This paper investigates the applicability of CMOS decoupling cells for mitigating the Single Event Transient (SET) effects in standard combinational gates. The concept is based on the insertion of two decoupling cells between the gate's output and the power/ground terminals. To verify the proposed hardening approach, extensive SPICE simulations have been performed with standard combinational cells designed in IHP's 130 nm bulk CMOS technology. Obtained simulation results have shown that the insertion of decoupling cells results in the increase of the gate's critical charge, thus reducing the gate's soft error rate (SER). Moreover, the decoupling cells facilitate the suppression of SET pulses propagating through the gate. It has been shown that the decoupling cells may be a competitive alternative to gate upsizing and gate duplication for hardening the gates with lower critical charge and multiple (3 or 4) inputs, as well as for filtering the short SET pulses induced by low-LET particles.
KW  - decoupling cells
KW  - radiation hardening
KW  - SET effects
KW  - CMOS technology
KW  - combinational logic
Y1  - 2019
SN  - 978-1-5386-9562-3
U6  - https://doi.org/10.1109/ICECS.2018.8617996
SP  - 361
EP  - 364
PB  - IEEE
CY  - New York
ER  - 
TY  - GEN
A1  - Sianipar, Johannes Harungguan
A1  - Willems, Christian
A1  - Meinel, Christoph
T1  - Virtual machine integrity verification in Crowd-Resourcing Virtual Laboratory
T2  - 2018 IEEE 11th Conference on Service-Oriented Computing and Applications (SOCA)
N2  - In cloud computing, users are able to use their own operating system (OS) image to run a virtual machine (VM) on a remote host. The virtual machine OS is started by the user using some interfaces provided by a cloud provider in public or private cloud. In peer to peer cloud, the VM is started by the host admin. After the VM is running, the user could get a remote access to the VM to install, configure, and run services. For the security reasons, the user needs to verify the integrity of the running VM, because a malicious host admin could modify the image or even replace the image with a similar image, to be able to get sensitive data from the VM. We propose an approach to verify the integrity of a running VM on a remote host, without using any specific hardware such as Trusted Platform Module (TPM). Our approach is implemented on a Linux platform where the kernel files (vmlinuz and initrd) could be replaced with new files, while the VM is running. kexec is used to reboot the VM with the new kernel files. The new kernel has secret codes that will be used to verify whether the VM was started using the new kernel files. The new kernel is used to further measuring the integrity of the running VM.
KW  - Virtual Machine
KW  - Integrity Verification
KW  - Crowd-Resourcing
KW  - Cloud Computing
Y1  - 2019
SN  - 978-1-5386-9133-5
U6  - https://doi.org/10.1109/SOCA.2018.00032
SN  - 2163-2871
SP  - 169
EP  - 176
PB  - IEEE
CY  - New York
ER  - 
TY  - GEN
A1  - Brand, Thomas
A1  - Giese, Holger Burkhard
T1  - Towards Generic Adaptive Monitoring
T2  - 2018 IEEE 12th International Conference on Self-Adaptive and Self-Organizing Systems (SASO)
N2  - Monitoring is a key prerequisite for self-adaptive software and many other forms of operating software. Monitoring relevant lower level phenomena like the occurrences of exceptions and diagnosis data requires to carefully examine which detailed information is really necessary and feasible to monitor. Adaptive monitoring permits observing a greater variety of details with less overhead, if most of the time the MAPE-K loop can operate using only a small subset of all those details. However, engineering such an adaptive monitoring is a major engineering effort on its own that further complicates the development of self-adaptive software. The proposed approach overcomes the outlined problems by providing generic adaptive monitoring via runtime models. It reduces the effort to introduce and apply adaptive monitoring by avoiding additional development effort for controlling the monitoring adaptation. Although the generic approach is independent from the monitoring purpose, it still allows for substantial savings regarding the monitoring resource consumption as demonstrated by an example.
Y1  - 2019
SN  - 978-1-5386-5172-8
U6  - https://doi.org/10.1109/SASO.2018.00027
SN  - 1949-3673
SP  - 156
EP  - 161
PB  - IEEE
CY  - New York
ER  - 
TY  - GEN
A1  - Sianipar, Johannes Harungguan
A1  - Sukmana, Muhammad Ihsan Haikal
A1  - Meinel, Christoph
T1  - Moving sensitive data against live memory dumping, spectre and meltdown attacks
T2  - 26th International Conference on Systems Engineering (ICSEng)
N2  - The emergence of cloud computing allows users to easily host their Virtual Machines with no up-front investment and the guarantee of always available anytime anywhere. But with the Virtual Machine (VM) is hosted outside of user's premise, the user loses the physical control of the VM as it could be running on untrusted host machines in the cloud. Malicious host administrator could launch live memory dumping, Spectre, or Meltdown attacks in order to extract sensitive information from the VM's memory, e.g. passwords or cryptographic keys of applications running in the VM. In this paper, inspired by the moving target defense (MTD) scheme, we propose a novel approach to increase the security of application's sensitive data in the VM by continuously moving the sensitive data among several memory allocations (blocks) in Random Access Memory (RAM). A movement function is added into the application source code in order for the function to be running concurrently with the application's main function. Our approach could reduce the possibility of VM's sensitive data in the memory to be leaked into memory dump file by 2 5% and secure the sensitive data from Spectre and Meltdown attacks. Our approach's overhead depends on the number and the size of the sensitive data.
KW  - Virtual Machine
KW  - Memory Dumping
KW  - Security
KW  - Cloud Computing
KW  - Spectre
KW  - Meltdown
Y1  - 2019
SN  - 978-1-5386-7834-3
PB  - IEEE
CY  - New York
ER  - 
TY  - GEN
A1  - Richly, Keven
T1  - Leveraging spatio-temporal soccer data to define a graphical query language for game recordings
T2  - IEEE International Conference on Big Data (Big Data)
N2  - For professional soccer clubs, performance and video analysis are an integral part of the preparation and post-processing of games. Coaches, scouts, and video analysts extract information about strengths and weaknesses of their team as well as opponents by manually analyzing video recordings of past games. Since video recordings are an unstructured data source, it is a complex and time-intensive task to find specific game situations and identify similar patterns. In this paper, we present a novel approach to detect patterns and situations (e.g., playmaking and ball passing of midfielders) based on trajectory data. The application uses the metaphor of a tactic board to offer a graphical query language. With this interactive tactic board, the user can model a game situation or mark a specific situation in the video recording for which all matching occurrences in various games are immediately displayed, and the user can directly jump to the corresponding game scene. Through the additional visualization of key performance indicators (e.g.,the physical load of the players), the user can get a better overall assessment of situations. With the capabilities to find specific game situations and complex patterns in video recordings, the interactive tactic board serves as a useful tool to improve the video analysis process of professional sports teams.
KW  - Spatio-temporal data analysis
KW  - soccer analytics
KW  - graphical query language
Y1  - 2019
SN  - 978-1-5386-5035-6
U6  - https://doi.org/10.1109/BigData.2018.8622159
SN  - 2639-1589
SP  - 3456
EP  - 3463
PB  - IEEE
CY  - New York
ER  - 
TY  - GEN
A1  - Richly, Keven
T1  - A survey on trajectory data management for hybrid transactional and analytical workloads
T2  - IEEE International Conference on Big Data (Big Data)
N2  - Rapid advances in location-acquisition technologies have led to large amounts of trajectory data. This data is the foundation for a broad spectrum of services driven and improved by trajectory data mining. However, for hybrid transactional and analytical workloads, the storing and processing of rapidly accumulated trajectory data is a non-trivial task. In this paper, we present a detailed survey about state-of-the-art trajectory data management systems. To determine the relevant aspects and requirements for such systems, we developed a trajectory data mining framework, which summarizes the different steps in the trajectory data mining process. Based on the derived requirements, we analyze different concepts to store, compress, index, and process spatio-temporal data. There are various trajectory management systems, which are optimized for scalability, data footprint reduction, elasticity, or query performance. To get a comprehensive overview, we describe and compare different exciting systems. Additionally, the observed similarities in the general structure of different systems are consolidated in a general blueprint of trajectory management systems.
KW  - Trajectory Data Management
KW  - Spatio-Temporal Data
KW  - Survey
Y1  - 2019
SN  - 978-1-5386-5035-6
U6  - https://doi.org/10.1109/BigData.2018.8622394
SN  - 2639-1589
SP  - 562
EP  - 569
PB  - IEEE
CY  - New York
ER  - 
TY  - GEN
A1  - Zarriess, Sina
A1  - Schlangen, David
T1  - Objects of Unknown Categories
T2  - The 57th Annual Meeting of the Association for Computational Linguistics
N2  - Zero-shot learning in Language & Vision is the task of correctly labelling (or naming) objects of novel categories. Another strand of work in L&V aims at pragmatically informative rather than "correct" object descriptions, e.g. in reference games. We combine these lines of research and model zero-shot reference games, where a speaker needs to successfully refer to a novel object in an image. Inspired by models of "rational speech acts", we extend a neural generator to become a pragmatic speaker reasoning about uncertain object categories. As a result of this reasoning, the generator produces fewer nouns and names of distractor categories as compared to a literal speaker. We show that this conversational strategy for dealing with novel objects often improves communicative success, in terms of resolution accuracy of an automatic listener.
Y1  - 2019
SN  - 978-1-950737-48-2
SP  - 654
EP  - 659
PB  - Association for Computational Linguistics
CY  - Stroudsburg
ER  - 
TY  - GEN
A1  - Finch, Nicolle L.
A1  - Braker, I. P.
A1  - Reindl, Nicole
A1  - Barstow, Martin A.
A1  - Casewell, Sarah L.
A1  - Burleigh, M.
A1  - Kupfer, Thomas
A1  - Kilkenny, D.
A1  - Geier, Stephan Alfred
A1  - Schaffenroth, Veronika
A1  - Bertolami Miller, Marcelo Miguel
A1  - Taubenberger, Stefan
A1  - Freudenthal, Joseph
T1  - Spectral Analysis of Binary Pre-white Dwarf Systems
T2  - Radiative signatures from the cosmos
N2  - Short period double degenerate white dwarf (WD) binaries with periods of less than similar to 1 day are considered to be one of the likely progenitors of type Ia supernovae. These binaries have undergone a period of common envelope evolution. If the core ignites helium before the envelope is ejected, then a hot subdwarf remains prior to contracting into a WD. Here we present a comparison of two very rare systems that contain two hot subdwarfs in short period orbits. We provide a quantitative spectroscopic analysis of the systems using synthetic spectra from state-of-the-art non-LTE models to constrain the atmospheric parameters of the stars. We also use these models to determine the radial velocities, and thus calculate dynamical masses for the stars in each system.
Y1  - 2019
SN  - 978-1-58381-925-8
SN  - 1050-3390
VL  - 519
SP  - 231
EP  - 238
PB  - Astronomical soc pacific
CY  - San Fransisco
ER  -