Institution
Academy of Finland
Government•Helsinki, Finland•
About: Academy of Finland is a government organization based out in Helsinki, Finland. It is known for research contribution in the topics: Population & Health care. The organization has 286 authors who have published 419 publications receiving 15304 citations. The organization is also known as: Finlands Akademi & Suomen Akatemia.
Papers published on a yearly basis
Papers
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01 Jan 2001TL;DR: The Zurich series of Wolf numbers as discussed by the authors extends back to 1749 and is defined as W = k(10g + f where g is the number of sunspot groups, f is the total number of spots and k is a factor allowing comparison between different observation series.
Abstract: Since the discovery by Schwabe in 1843 of the cyclic nature of sunspot activity, there has been a great deal of attention paid to the nature of these cycles. In 1849 Wolf established a measure of sunspot activity, the Wolf number, defined as W = k(10g + f where g is the number of sunspot groups, f is the total number of spots and k is a factor allowing comparison between different observation series. Based on this measure we have the Zurich series of Wolf numbers which extends back to 1749. Since the counts for W are taken over the whole visible surface of the sun, all information about the spatial distribution of the sunspot activity is lost. Realising the importance of such spatial information, Carrington in 1853 began the recording of the latitudes and longitudes of spots and this eventually resulted in the Greenwich series of photographic recordings of the solar surface which lasted from 1874 to 1976. Maunder introduced the famous Maunder or butterfly diagram (so called because the pattern of the cycles resembles the wings of a butterfly) which shows spot activity as a travelling wave beginning in the higher latitudes and proceeding to the equator.
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TL;DR: In this article, the surface state densities of ultrathin silicon dioxide layers have been fabricated by the room temperature plasma oxidation of silicon in ultrahigh vacuum. But the oxide charge, however, is then quite high.
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17 Dec 2010TL;DR: A significantly improved strategy for accelerating the method calls in the REALJava coprocessor, which allows measurements of real life performance increase, and validates the whole co-processor concept.
Abstract: This paper presents a significantly improved strategy for accelerating the method calls in the REALJava coprocessor. The hardware assisted virtual machine architecture is described shortly to provide context for the method call acceleration. The strategy is implemented in an FPGA prototype. It allows measurements of real life performance increase, and validates the whole co-processor concept. The system is intended to be used in embedded environments, with limited CPU performance and memory available to the virtual machine. The co-processor is designed in a highly modular fashion, especially separating the communication from the actual core. This modularity of the design makes the co-processor more reusable and allows system level scalability. This work is a part of a project focusing on design of a hardware accelerated multicore Java Virtual Machine for embedded systems.
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TL;DR: Language is a tool for thinking and telling that combines representation and processing of information about the environment, and information transferral between users between users.
Abstract: Language is a tool for thinking and telling Its two main functions are representation and processing of information about the environment, and information transferral between users (communication)1
Authors
Showing all 290 results
Name | H-index | Papers | Citations |
---|---|---|---|
Jaakko Kaprio | 163 | 1532 | 126320 |
Olli Kallioniemi | 90 | 353 | 42021 |
Leena Peltonen | 87 | 195 | 33605 |
Mika Gissler | 85 | 1021 | 28366 |
Juha Hyyppä | 73 | 473 | 18625 |
Taina Pihlajaniemi | 68 | 258 | 14443 |
Christina Salmivalli | 66 | 161 | 17032 |
Timo Teräsvirta | 62 | 224 | 20403 |
Mikael Fogelholm | 62 | 263 | 17477 |
Moncef Gabbouj | 58 | 886 | 16860 |
Elina Hemminki | 56 | 369 | 11136 |
Matti Laine | 56 | 239 | 10256 |
Arto Salomaa | 56 | 374 | 17706 |
Mika Lindén | 53 | 229 | 10141 |
Heikki Tenhu | 53 | 252 | 10012 |