Gesamtliste aus der Hochschulbibliographie

Anzahl der Treffer: 246
Erstellt: Thu, 30 Jun 2022 23:44:50 +0200 in 0.0811 sec

Zhang, Chen; Gebhart, Ingo; Kühmstedt, Peter; Rosenberger, Maik; Notni, Gunther;
Enhanced contactless vital sign estimation from real-time multimodal 3D image data. - In: Journal of imaging, ISSN 2313-433X, Volume 6 (2020), issue 11, 123, Seite 1-15
Glombiewski, Nikolaus; Götze, Philipp; Körber, Michael; Morgen, Andreas; Seeger, Bernhard;
Designing an event store for a modern three-layer storage hierarchy. - In: Datenbank-Spektrum, ISSN 1610-1995, Bd. 20 (2020), 3, S. 211-222

Event stores face the difficult challenge of continuously ingesting massive temporal data streams while satisfying demanding query and recovery requirements. Many of todays systems deal with multiple hardware-based trade-offs. For instance, long-term storage solutions balance keeping data in cheap secondary media (SSDs, HDDs) and performance-oriented main-memory caches. As an alternative, in-memory systems focus on performance, while sacrificing monetary costs, and, to some degree, recovery guarantees. The advent of persistent memory (PMem) led to a multitude of novel research proposals aiming to alleviate those trade-offs in various fields. So far, however, there is no proposal for a PMem-powered specialized event store.
Xu, Rui; Wen, Liaoyong; Wang, Zhijie; Zhao, Huaping; Mu, Guannan; Zeng, Zhiqiang; Zhou, Min; Bohm, Sebastian; Zhang, Huanming; Wu, Yuhan; Runge, Erich; Lei, Yong;
Programmable multiple plasmonic resonances of nanoparticle superlattice for enhancing photoelectrochemical activity. - In: Advanced functional materials, ISSN 1616-3028, Bd. 30 (2020), 48, 2005170, insges. 10 S.
Schricker, Klaus; Alhomsi, Mohammad; Bergmann, Jean Pierre;
Thermal efficiency in laser-assisted joining of polymer-metal composites. - In: Materials, ISSN 1996-1944, Bd. 13 (2020), 21, 4875, insges. 16 S.
Raake, Alexander; Borer, Silvio; Satti, Shahid M.; Gustafsson, Jörgen; Ramachandra Rao, Rakesh Rao; Medagli, Stefano; List, Peter; Göring, Steve; Lindero, David; Robitza, Werner; Heikkilä, Gunnar; Broom, Simon; Schmidmer, Christian; Feiten, Bernhard; Wüstenhagen, Ulf; Wittmann, Thomas; Obermann, Matthias; Bitto, Roland;
Multi-model standard for bitstream-, pixel-based and hybrid video quality assessment of UHD/4K: ITU-T P.1204. - In: IEEE access, ISSN 2169-3536, Bd. 8 (2020), S. 193020-193049
Zhang, Qingcheng; Zhao, Junping; Wu, Yechao; Li, Jun; Jin, Huile; Zhao, Shiqiang; Chai, Lulu; Wang, Yahui; Lei, Yong; Wang, Shun;
Rapid and controllable synthesis of nanocrystallized nickel-cobalt boride electrode materials via a mircoimpinging stream reaction for high performance supercapacitors. - In: Small, ISSN 1613-6829, Bd. 16 (2020), 39, 2003342, insges. 13 S.

Nickel-cobalt borides (denoted as NCBs) have been considered as a promising candidate for aqueous supercapacitors due to their high capacitive performances. However, most reported NCBs are amorphous that results in slow electron transfer and even structure collapse during cycling. In this work, a nanocrystallized NCBs-based supercapacitor is successfully designed via a facile and practical microimpinging stream reactor (MISR) technique, composed of a nanocrystallized NCB core to facilitate the charge transfer, and a tightly contacted Ni-Co borates/metaborates (NCBi) shell which is helpful for OH^- adsorption. These merits endow NCBNCBi a large specific capacity of 966 C g^-1 (capacitance of 2415 F g^-1) at 1 A g^-1 and good rate capability (633.2 C g^-1 at 30 A g^-1), as well as a very high energy density of 74.3 Wh kg^-1 in an asymmetric supercapacitor device. More interestingly, it is found that a gradual in situ conversion of core NCBs to nanocrystallized Ni-Co (oxy)-hydroxides inwardly takes place during the cycles, which continuously offers large specific capacity due to more electron transfer in the redox reaction processes. Meanwhile, the electron deficient state of boron in metal-borates shells can make it easier to accept electrons and thus promote ionic conduction.
Angermeier, Sebastian; Ketterer, Jonas; Karcher, Christian;
Liquid-based battery temperature control of electric buses. - In: Energies, ISSN 1996-1073, Volume 13 (2020), issue 19, 4990, Seite 1-20

Previous research identified that battery temperature control is critical to the safety, lifetime, and performance of electric vehicles. In this paper, the liquid-based battery temperature control of electric buses is investigated subject to heat transfer behavior and control strategy. Therefore, a new transient calculation method is proposed to simulate the thermal behavior of a coolant-cooled battery system. The method is based on the system identification technique and combines the advantage of low computational effort and high accuracy. In detail, four transfer functions are extracted by a thermo-hydraulic 3D simulation model comprising 12 prismatic lithium nickel manganese cobalt oxide (NMC) cells, housing, arrestors, and a cooling plate. The transfer functions describe the relationship between heat generation, cell temperature, and coolant temperature. A vehicle model calculates the power consumption of an electric bus and thus provides the input for the transient calculation. Furthermore, a cell temperature control strategy is developed with respect to the constraints of a refrigerant-based battery cooling unit. The data obtained from the simulation demonstrate the high thermal inertia of the system and suggest sufficient control of the battery temperature using a quasi-stationary cooling strategy. Thereby, the study reveals a crucial design input for battery cooling systems in terms of heat transfer behavior and control strategy.
Solf, Benjamin; Schramm, Stefan; Blum, Maren-Christina; Klee, Sascha;
The influence of the stimulus design on the harmonic components of the steady-state visual evoked potential. - In: Frontiers in human neuroscience, ISSN 1662-5161, Bd. 14 (2020), 343, insges. 11 S.
Lasch, Robert; Oukid, Ismail; Dementiev, Roman; May, Norman; Demirsoy, Suleyman S.; Sattler, Kai-Uwe;
Faster & strong: string dictionary compression using sampling and fast vectorized decompression. - In: The VLDB journal, ISSN 0949-877X, Bd. 29 (2020), 6, S. 1263-1285

String dictionaries constitute a large portion of the memory footprint of database applications. While strong string dictionary compression algorithms exist, these come with impractical access and compression times. Therefore, lightweight algorithms such as front coding (PFC) are favored in practice. This paper endeavors to make strong string dictionary compression practical. We focus on Re-Pair Front Coding (RPFC), a grammar-based compression algorithm, since it consistently offers better compression ratios than other algorithms in the literature. To accelerate compression times, we propose block-based RPFC (BRPFC) which consists in independently compressing small blocks of the dictionary. For further accelerated compression times especially on large string dictionaries, we also propose an alternative version of BRPFC that uses sampling to speed up compression. Moreover, to accelerate access times, we devise a vectorized access method, using Intel® Advanced Vector Extensions 512 (Intel® AVX-512). Our experimental evaluation shows that sampled BRPFC offers compression times up to 190 × faster than RPFC, and random string lookups 2.3 × faster than RPFC on average. These results move our modified RPFC into a practical range for use in database systems because the overhead of Re-Pair-based compression for access times can be reduced by 2 ×.
Al-Sayeh, Hani; Hagedorn, Stefan; Sattler, Kai-Uwe;
A gray-box modeling methodology for runtime prediction of Apache Spark jobs. - In: Distributed and parallel databases, ISSN 1573-7578, Bd. 38 (2020), 4, S. 819-839

Apache Spark jobs are often characterized by processing huge data sets and, therefore, require runtimes in the range of minutes to hours. Thus, being able to predict the runtime of such jobs would be useful not only to know when the job will finish, but also for scheduling purposes, to estimate monetary costs for cloud deployment, or to determine an appropriate cluster configuration, such as the number of nodes. However, predicting Spark job runtimes is much more challenging than for standard database queries: cluster configuration and parameters have a significant performance impact and jobs usually contain a lot of user-defined code making it difficult to estimate cardinalities and execution costs. In this paper, we present a gray-box modeling methodology for runtime prediction of Apache Spark jobs. Our approach comprises two steps: first, a white-box model for predicting the cardinalities of the input RDDs of each operator is built based on prior knowledge about the behavior and application parameters such as applied filters data, number of iterations, etc. In the second step, a black-box model for each task constructed by monitoring runtime metrics while varying allocated resources and input RDD cardinalities is used. We further show how to use this gray-box approach not only for predicting the runtime of a given job, but also as part of a decision model for reusing intermediate cached results of Spark jobs. Our methodology is validated with experimental evaluation showing a highly accurate prediction of the actual job runtime and a performance improvement if intermediate results can be reused.