Institution
Hosei University
Education•Tokyo, Japan•
About: Hosei University is a education organization based out in Tokyo, Japan. It is known for research contribution in the topics: Antenna (radio) & Radiation pattern. The organization has 4139 authors who have published 7810 publications receiving 84297 citations. The organization is also known as: Hōsei daigaku.
Papers published on a yearly basis
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TL;DR: In this article, the authors present possible observing scenarios for the Advanced LIGO, Advanced Virgo and KAGRA gravitational-wave detectors over the next decade, with the intention of providing information to the astronomy community to facilitate planning for multi-messenger astronomy with gravitational waves.
Abstract: We present possible observing scenarios for the Advanced LIGO, Advanced Virgo and KAGRA gravitational-wave detectors over the next decade, with the intention of providing information to the astronomy community to facilitate planning for multi-messenger astronomy with gravitational waves. We estimate the sensitivity of the network to transient gravitational-wave signals, and study the capability of the network to determine the sky location of the source. We report our findings for gravitational-wave transients, with particular focus on gravitational-wave signals from the inspiral of binary neutron star systems, which are the most promising targets for multi-messenger astronomy. The ability to localize the sources of the detected signals depends on the geographical distribution of the detectors and their relative sensitivity, and 90% credible regions can be as large as thousands of square degrees when only two sensitive detectors are operational. Determining the sky position of a significant fraction of detected signals to areas of 5– 20 deg2 requires at least three detectors of sensitivity within a factor of ∼2 of each other and with a broad frequency bandwidth. When all detectors, including KAGRA and the third LIGO detector in India, reach design sensitivity, a significant fraction of gravitational-wave signals will be localized to a few square degrees by gravitational-wave observations alone.
804 citations
University of Saskatchewan1, Centre for Environment, Fisheries and Aquaculture Science2, Natural History Museum3, University of Rhode Island4, Sewanee: The University of the South5, Academy of Sciences of the Czech Republic6, National Institutes of Health7, Saint Petersburg State University8, University of Salzburg9, Centre national de la recherche scientifique10, Mississippi State University11, Science for Life Laboratory12, Uppsala University13, Charles University in Prague14, Spanish National Research Council15, University of Duisburg-Essen16, Kaiserslautern University of Technology17, University of Oslo18, Dalhousie University19, Pierre-and-Marie-Curie University20, American Museum of Natural History21, University of Michigan22, University of Warsaw23, University of São Paulo24, University of Paris25, University of Guelph26, University of British Columbia27, Royal Botanic Garden Edinburgh28, Kyungpook National University29, University of Geneva30, University of Alabama31, Pompeu Fabra University32, Edinburgh Napier University33, University of Arkansas34, Hosei University35, Oklahoma State University–Stillwater36, Chinese Academy of Sciences37
TL;DR: It is confirmed that eukaryotes form at least two domains, the loss of monophyly in the Excavata, robust support for the Haptista and Cryptista, and suggested primer sets for DNA sequences from environmental samples that are effective for each clade are provided.
Abstract: This revision of the classification of eukaryotes follows that of Adl et al., 2012 [J. Euk. Microbiol. 59(5)] and retains an emphasis on protists. Changes since have improved the resolution of many ...
750 citations
TL;DR: There are two approaches to the problem of powder compression: (a) an observation of the relationship between pressure and volume, and (b) the distribution of internal stress and density as mentioned in this paper.
720 citations
TL;DR: It is shown that the solvability of a set of matrix inequalities is necessary and sufficient to the existence of a proper controller that satisfies a prescribed H ∞ norm condition as well as stabilizing the closed-loop system and eliminating all impulsive modes.
667 citations
TL;DR: The unique features and novel application areas of MCSC are characterized and a reference framework for building human-in-the-loop MCSC systems is proposed, which clarifies the complementary nature of human and machine intelligence and envision the potential of deep-fused human--machine systems.
Abstract: With the surging of smartphone sensing, wireless networking, and mobile social networking techniques, Mobile Crowd Sensing and Computing (MCSC) has become a promising paradigm for cross-space and large-scale sensing. MCSC extends the vision of participatory sensing by leveraging both participatory sensory data from mobile devices (offline) and user-contributed data from mobile social networking services (online). Further, it explores the complementary roles and presents the fusion/collaboration of machine and human intelligence in the crowd sensing and computing processes. This article characterizes the unique features and novel application areas of MCSC and proposes a reference framework for building human-in-the-loop MCSC systems. We further clarify the complementary nature of human and machine intelligence and envision the potential of deep-fused human--machine systems. We conclude by discussing the limitations, open issues, and research opportunities of MCSC.
650 citations
Authors
Showing all 4175 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Sadanori Okamura | 99 | 323 | 58592 |
| Akira Ishihama | 82 | 418 | 23173 |
| Kazuo Tanaka | 63 | 535 | 27559 |
| Hidetoshi Kubo | 60 | 477 | 16110 |
| Zhiqiang Zhang | 60 | 595 | 16675 |
| Mihajlo Jakovljevic | 55 | 242 | 52734 |
| W. Glöckle | 55 | 382 | 11247 |
| Edward C. Chang | 51 | 246 | 9006 |
| Mami Yamazaki | 51 | 172 | 9325 |
| Tomoaki Matsumoto | 49 | 186 | 7013 |
| Leonard Barolli | 47 | 1145 | 9969 |
| Hiroyuki Kamada | 47 | 316 | 7487 |
| Masafumi Yagi | 46 | 171 | 7627 |
| Toru Tanimori | 46 | 377 | 10160 |
| Satoru Matsuda | 46 | 246 | 6507 |