Institution
Tallinn University of Technology
Education•Tallinn, Estonia•
About: Tallinn University of Technology is a education organization based out in Tallinn, Estonia. It is known for research contribution in the topics: European union & Oil shale. The organization has 3688 authors who have published 10313 publications receiving 145058 citations. The organization is also known as: Tallinn Technical University & Tallinna Tehnikaülikool.
Topics: European union, Oil shale, Thin film, Nonlinear system, Microstructure
Papers published on a yearly basis
Papers
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TL;DR: The role of carbon dioxide in regulating climate during the early Paleozoic, when severe glaciations occurred during a putative greenhouse world, remains unclear as discussed by the authors, and the limitations of applying this approach to the reconstruction of the early Katian pCO2.
48 citations
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TL;DR: It was found that adding recombinantly produced fish type III IBPs at a concentration 3 mg·L-1 made ice cream hard and crystalline with improved shape preservation during melting.
48 citations
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TL;DR: It is shown how a software diagnosis model can be built automatically that can be integrated with the hardware model to diagnose the complete system and empirically that on Autosub 6000 this allows us to diagnose real vehicle faults that could potentially lead to the loss of the vehicle.
Abstract: This paper reports our results in using a discrete fault diagnosis system Livingstone 2 (L2), onboard an autonomous underwater vehicle (AUV) Autosub 6000. Due to the difficulty of communicating between an AUV and its operators, AUVs can benefit particularly from increased autonomy, of which fault diagnosis is a part. However, they are also restricted in their power consumption. We show that a discrete diagnosis system can detect and identify a number of faults that would threaten the health of an AUV, while also being sufficiently lightweight computationally to be deployed onboard the vehicle. Since AUVs also often have their missions designed just before deployment in response to data from previous missions, a diagnosis system that monitors the software as well as the hardware of the system is also very useful. We show how a software diagnosis model can be built automatically that can be integrated with the hardware model to diagnose the complete system. We show empirically that on Autosub 6000 this allows us to diagnose real vehicle faults that could potentially lead to the loss of the vehicle.
48 citations
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TL;DR: A cross-organizational collaboration ontology is mapped as a proof-of-concept evaluation to the eSourcing Markup Language (eSML) and the latter is tested in a feasibility case study to meaningfully support the automation of business collaboration.
Abstract: Meaningfully automating sociotechnical business collaboration promises efficiency-, effectiveness-, and quality increases for realizing next-generation decentralized autonomous organizations. For automating business-process aware cross-organizational operations, the development of existing choreography languages is technology driven and focuses less on sociotechnical suitability and expressiveness concepts and properties that recognize the interaction between people in organizations and technology in workplaces. This gap our suitability- and expressiveness exploration fills by means of a cross-organizational collaboration ontology that we map as a proof-of-concept evaluation to the eSourcing Markup Language (eSML). The latter we test in a feasibility case study to meaningfully support the automation of business collaboration. The developed eSourcing ontology and eSML is replicable for exploring strengths and weaknesses of other choreography languages.
48 citations
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TL;DR: In this article, thin-film buffer layers were prepared by ultrasonic spray pyrolysis at various substrate temperatures and X-ray Diffraction measurements confirmed that the films contained primarily the tetragonal In 2 S 3 phase.
48 citations
Authors
Showing all 3757 results
Name | H-index | Papers | Citations |
---|---|---|---|
James Chapman | 82 | 483 | 36468 |
Alexandre Alexakis | 67 | 540 | 17247 |
Bernard Waeber | 56 | 370 | 35335 |
Peter A. Andrekson | 54 | 573 | 12042 |
Charles S. Peirce | 51 | 167 | 11998 |
Lars M. Blank | 49 | 301 | 8011 |
Fushuan Wen | 49 | 465 | 9189 |
Mati Karelson | 48 | 207 | 10210 |
Ago Samoson | 46 | 119 | 8807 |
Zebo Peng | 45 | 359 | 7312 |
Petru Eles | 44 | 300 | 6749 |
Vijai Kumar Gupta | 43 | 301 | 6901 |
Eero Vasar | 43 | 263 | 6930 |
Rik Ossenkoppele | 42 | 192 | 6839 |
Tõnis Timmusk | 41 | 105 | 11056 |