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 - 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 - Staubitz, Thomas A1 - Meinel, Christoph T1 - Graded Team Assignments in MOOCs BT - Effects of Team Composition and Further Factors on Team Dropout Rates and Performance T2 - SCALE N2 - The ability to work in teams is an important skill in today's work environments. In MOOCs, however, team work, team tasks, and graded team-based assignments play only a marginal role. To close this gap, we have been exploring ways to integrate graded team-based assignments in MOOCs. Some goals of our work are to determine simple criteria to match teams in a volatile environment and to enable a frictionless online collaboration for the participants within our MOOC platform. The high dropout rates in MOOCs pose particular challenges for team work in this context. By now, we have conducted 15 MOOCs containing graded team-based assignments in a variety of topics. The paper at hand presents a study that aims to establish a solid understanding of the participants in the team tasks. Furthermore, we attempt to determine which team compositions are particularly successful. Finally, we examine how several modifications to our platform's collaborative toolset have affected the dropout rates and performance of the teams. KW - Teamwork KW - MOOCs KW - Team-based Learning KW - Team Assessment KW - Peer Assessment KW - Project-based learning Y1 - 2019 SN - 978-1-4503-6804-9 U6 - https://doi.org/10.1145/3330430.3333619 PB - Association for Computing Machinery CY - New York ER - TY - GEN A1 - Bock, Benedikt A1 - Matysik, Jan-Tobias A1 - Krentz, Konrad-Felix A1 - Meinel, Christoph T1 - Link Layer Key Revocation and Rekeying for the Adaptive Key Establishment Scheme T2 - 2019 IEEE 5TH World Forum on internet of things (WF-IOT) N2 - While the IEEE 802.15.4 radio standard has many features that meet the requirements of Internet of things applications, IEEE 802.15.4 leaves the whole issue of key management unstandardized. To address this gap, Krentz et al. proposed the Adaptive Key Establishment Scheme (AKES), which establishes session keys for use in IEEE 802.15.4 security. Yet, AKES does not cover all aspects of key management. In particular, AKES comprises no means for key revocation and rekeying. Moreover, existing protocols for key revocation and rekeying seem limited in various ways. In this paper, we hence propose a key revocation and rekeying protocol, which is designed to overcome various limitations of current protocols for key revocation and rekeying. For example, our protocol seems unique in that it routes around IEEE 802.15.4 nodes whose keys are being revoked. We successfully implemented and evaluated our protocol using the Contiki-NG operating system and aiocoap. KW - IEEE 802.15.4 KW - key management KW - key establishment KW - key revocation KW - rekeying KW - link layer security KW - MAC security Y1 - 2019 SN - 978-1-5386-4980-0 U6 - https://doi.org/10.1109/WF-IoT.2019.8767211 SP - 374 EP - 379 PB - IEEE CY - New York ER - TY - JOUR A1 - Schlosser, Rainer A1 - Walther, Carsten A1 - Boissier, Martin A1 - Uflacker, Matthias T1 - Automated repricing and ordering strategies in competitive markets JF - AI communications : AICOM ; the European journal on artificial intelligence N2 - Merchants on modern e-commerce platforms face a highly competitive environment. They compete against each other using automated dynamic pricing and ordering strategies. Successfully managing both inventory levels as well as offer prices is a challenging task as (i) demand is uncertain, (ii) competitors strategically interact, and (iii) optimized pricing and ordering decisions are mutually dependent. We show how to derive optimized data-driven pricing and ordering strategies which are based on demand learning techniques and efficient dynamic optimization models. We verify the superior performance of our self-adaptive strategies by comparing them to different rule-based as well as data-driven strategies in duopoly and oligopoly settings. Further, to study and to optimize joint dynamic ordering and pricing strategies on online marketplaces, we built an interactive simulation platform. To be both flexible and scalable, the platform has a microservice-based architecture and allows handling dozens of competing merchants and streams of consumers with configurable characteristics. KW - Dynamic pricing KW - inventory management KW - demand learning KW - oligopoly competition KW - e-commerce Y1 - 2019 U6 - https://doi.org/10.3233/AIC-180603 SN - 0921-7126 SN - 1875-8452 VL - 32 IS - 1 SP - 15 EP - 29 PB - IOS Press CY - Amsterdam ER - TY - JOUR A1 - Omotosho, Adebayo A1 - Ayegba, Peace A1 - Emuoyibofarhe, Justice A1 - Meinel, Christoph T1 - Current State of ICT in Healthcare Delivery in Developing Countries JF - International Journal of Online and Biomedical Engineering N2 - Electronic health is one of the most popular applications of information and communication technologies and it has contributed immensely to health delivery through the provision of quality health service and ubiquitous access at a lower cost. Even though this mode of health service is increasingly becoming known or used in developing nations, these countries are faced with a myriad of challenges when implementing and deploying e-health services on both small and large scale. It is estimated that the Africa population alone carries the highest percentage of the world’s global diseases despite its certain level of e-health adoption. This paper aims at analyzing the progress so far and the current state of e-health in developing countries particularly Africa and propose a framework for further improvement. KW - E-health KW - developing countries KW - framework KW - ICT KW - healthcare Y1 - 2019 U6 - https://doi.org/10.3991/ijoe.v15i08.10294 SN - 2626-8493 VL - 15 IS - 8 SP - 91 EP - 107 PB - Kassel University Press CY - Kassel ER -