Refine
Year of publication
- 2018 (162) (remove)
Document Type
- Part of a Book (65)
- Conference Proceeding (43)
- Article (reviewed) (19)
- Other (15)
- Article (unreviewed) (10)
- Contribution to a Periodical (5)
- Book (4)
- Doctoral Thesis (1)
Conference Type
- Konferenzartikel (37)
- Konferenz-Abstract (4)
- Konferenz-Poster (1)
- Sonstiges (1)
Is part of the Bibliography
- yes (162) (remove)
Keywords
- Data Analytics (7)
- Digitalisierung (7)
- Industrie 4.0 (7)
- Social Media Marketing (7)
- Big Data (6)
- Fraud Analytics (6)
- Smart City (6)
- Surveillance (6)
- Autonomie (3)
- 5G mobile communication (2)
Institute
- Fakultät Medien und Informationswesen (M+I) (bis 21.04.2021) (87)
- Fakultät Elektrotechnik und Informationstechnik (E+I) (bis 03/2019) (32)
- Fakultät Wirtschaft (W) (22)
- Fakultät Maschinenbau und Verfahrenstechnik (M+V) (15)
- ivESK - Institut für verlässliche Embedded Systems und Kommunikationselektronik (14)
- INES - Institut für nachhaltige Energiesysteme (5)
- ACI - Affective and Cognitive Institute (3)
- WLRI - Work-Life Robotics Institute (2)
- CRT - Campus Research & Transfer (1)
- Zentrale Einrichtungen (1)
Open Access
- Closed Access (162) (remove)
The authors claim that location information of stationary ICT components can never be unclassified. They describe how swarm-mapping crowd sourcing is used by Apple and Google to worldwide harvest geo-location information on wireless access points and mobile telecommunication systems' base stations to build up gigantic databases with very exclusive access rights. After having highlighted the known technical facts, in the speculative part of this article, the authors argue how this may impact cyber deterrence strategies of states and alliances understanding the cyberspace as another domain of geostrategic relevance. The states and alliances spectrum of activities due to the potential existence of such databases may range from geopolitical negotiations by institutions understanding international affairs as their core business, mitigation approaches at a technical level, over means of cyber deterrence-by-retaliation.
Covert- and side-channels as well as techniques to establish them in cloud computing are in focus of research for quite some time. However, not many concrete mitigation methods have been developed and even less have been adapted and concretely implemented by cloud providers. Thus, we recently conceptually proposed C 3 -Sched a CPU scheduling based approach to mitigate L2 cache covert-channels. Instead of flushing the cache on every context switch, we schedule trusted virtual machines to create noise which prevents potential covert-channels. Additionally, our approach aims on preserving performance by utilizing existing instead of artificial workload while reducing covert-channel related cache flushes to cases where not enough noise has been achieved. In this work we evaluate cache covert-channel mitigation and performance impact of our integration of C 3 -Sched in the XEN credit scheduler. Moreover, we compare it to naive solutions and more competitive approaches.
Quantification of astaxanthin in salmons by chemiluminescence and absorption after TLC separation
(2018)
Astaxanthin is a keto-carotenoid, belongs to the chemical class of terpenes and is a yellow lipid soluble compound. The compound is present in marine animals like salmons and crustacean. Its colour is due to conjugated double bonds and these double bonds are responsible for its antioxidant effect. Its antioxidant activity is ten times stronger than other carotenoids and nearly 500 fold stronger than vitamin-E. We present a new thin layer chromatography (TLC) method to measure astaxanthin on TLC-plates (Merck, 1.05554) in the visible absorption range as well as by using chemiluminescence. For separation a solvent mixture of cyclohexane and acetone (10 + 2.4, v/v) was used. The RF-value of astaxanthin is 0.14.The limit of detection in vis-absorption is 64 ng / band and the limit of quantification is 92 ng/band. In chemiluminescence the values are 90 ng / band and 115 ng/band. The method offers two independently working measurement modes on a single plate which increase the accuracy of the quantification.
In this paper, we present a frame synchronization method which consists of the non-orthogonal superposition of a synchronization sequence and the data. We derive the optimum detection criterion and compare it to the classical sequential concatenation of synchronization and data sequences. Computer simulations confirm the benefits of the non-orthogonal allocation for the case of short frames, which makes this technique particularly suited for the increasingly important regime of low latency and ultra- reliable communication.
This paper deals with the detection and segmentation of clouds on high-dynamic-range (HDR) images of the sky as well as the calculation of the position of the sun at any time of the year. In order to predict the movement of clouds and the radiation of the sun for a short period of time, the clouds thickness and position have to be known as precisely as possible. Consequently, the segmentation algorithm has to provide satisfactory results regardless of different weather, illumination and climatic conditions. The principle of the segmentation is based on the classification of each pixel as a cloud or as a sky. This classification is usually based on threshold methods, since these are relatively fast to implement and show a low computational burden. In order to predict if and when the sun will be covered by clouds, the position of the sun on the images has to be determined. For this purpose, the zenith and azimuth angles of the sun are determined and converted into XY coordinates.
Solar irradiance prediction is vital for the power management and the cost reduction when integrating solar energy. The study is towards a ground image based solar irradiance prediction which is highly dependent on the cloud coverage. The sky images are collected by using ground based sky imager (fisheye lens). In this work, different algorithms for cloud detection being a preparation step for their segmentation are compared.
The fisheye camera has been widely studied in the field of ground based sky imagery and robot vision since it can capture a wide view of the scene at one time. However, serious image distortion is a major drawback hindering its wider use. To remedy this, this paperproposes a lens calibration and distortion correction method for detecting clouds and forecasting solar radiation. Finally, the radial distortion of the fisheye image can be corrected by incorporating the estimated calibration parameters. Experimental results validate the effectiveness of the proposed method.
Membrane distillation (MD) is a thermal separation process which possesses a hydrophobic, microporous
membrane as vapor space. A high potential application for MD is the concentration of hypersaline brines, such as
e.g. reverse osmosis retentate or other saline effluents to be concentrated to a near saturation level with a Zero
Liquid Discharge process chain. In order to further commercialize MD for these target applications, adapted MD
module designs are required along with strategies for the mitigation of membrane wetting phenomena. This
work presents the experimental results of pilot operation with an adapted Air Gap Membrane Distillation
(AGMD) module for hypersaline brine concentration within a range of 0–240 g NaCl /kg solution. Key performance
indicators such as flux, GOR and thermal efficiency are analyzed. A new strategy for wetting mitigation
by active draining of the air gap channel by low pressure air blowing is tested and analyzed. Only small reductions
in flux and GOR of 1.2% and 4.1% respectively, are caused by air sparging into the air gap channel.
Wetting phenomena are significantly reduced by avoiding stagnant distillate in the air gap making the air blower
a seemingly worth- while additional system component.