Decision Maker based on Nanoscale Photo-excitation Transfer View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2013-12

AUTHORS

Song-Ju Kim, Makoto Naruse, Masashi Aono, Motoichi Ohtsu, Masahiko Hara

ABSTRACT

Decision-making is one of the most important intellectual abilities of the human brain. Here we propose an efficient decision-making system which uses optical energy transfer between quantum dots (QDs) mediated by optical near-field interactions occurring at scales far below the wavelength of light. The simulation results indicate that our system outperforms the softmax rule, which is known as the best-fitting algorithm for human decision-making behaviour. This suggests that we can produce a nano-system which makes decisions efficiently and adaptively by exploiting the intrinsic spatiotemporal dynamics involving QDs mediated by optical near-field interactions. More... »

PAGES

2370

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/srep02370

DOI

http://dx.doi.org/10.1038/srep02370

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1038495311

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/23928655


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0205", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Optical Physics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/02", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Physical Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Algorithms", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Biomimetics", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Computer Simulation", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Decision Making", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Energy Transfer", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Light", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Models, Theoretical", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Nanoparticles", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Photons", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Quantum Dots", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Signal Processing, Computer-Assisted", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "National Institute for Materials Science", 
          "id": "https://www.grid.ac/institutes/grid.21941.3f", 
          "name": [
            "WPI Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kim", 
        "givenName": "Song-Ju", 
        "id": "sg:person.01231756453.24", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01231756453.24"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Institute of Information and Communications Technology", 
          "id": "https://www.grid.ac/institutes/grid.28312.3a", 
          "name": [
            "Photonic Network Research Institute, National Institute of Information and Communications Technology, 4-2-1 Nukui-kita, Koganei, Tokyo 184-8795, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Naruse", 
        "givenName": "Makoto", 
        "id": "sg:person.0623123511.31", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0623123511.31"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tokyo Institute of Technology", 
          "id": "https://www.grid.ac/institutes/grid.32197.3e", 
          "name": [
            "Earth-Life Science Institute, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8550, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Aono", 
        "givenName": "Masashi", 
        "id": "sg:person.01322136753.46", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01322136753.46"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Tokyo", 
          "id": "https://www.grid.ac/institutes/grid.26999.3d", 
          "name": [
            "Department of Electrical Engineering and Information Systems / Nanophotonics Research Center, Graduate School of Engineering, The University of Tokyo, 2-11-16 Yayoi, Bunkyo-ku, Tokyo 113-8656, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ohtsu", 
        "givenName": "Motoichi", 
        "id": "sg:person.01046230011.99", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01046230011.99"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tokyo Institute of Technology", 
          "id": "https://www.grid.ac/institutes/grid.32197.3e", 
          "name": [
            "Department of Electronic Chemistry, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, 4259 Nagatsuta, Midori-ku, Yokohama 226-8503, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hara", 
        "givenName": "Masahiko", 
        "id": "sg:person.010321266305.69", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010321266305.69"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/978-3-642-13523-1_10", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002972792", 
          "https://doi.org/10.1007/978-3-642-13523-1_10"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-13523-1_10", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002972792", 
          "https://doi.org/10.1007/978-3-642-13523-1_10"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1098/rstb.2007.2098", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009990002"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature04766", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011628537", 
          "https://doi.org/10.1038/nature04766"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature04766", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011628537", 
          "https://doi.org/10.1038/nature04766"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature04766", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011628537", 
          "https://doi.org/10.1038/nature04766"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00340-011-4596-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028056307", 
          "https://doi.org/10.1007/s00340-011-4596-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00340-010-3999-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028202999", 
          "https://doi.org/10.1007/s00340-010-3999-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00340-010-3999-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028202999", 
          "https://doi.org/10.1007/s00340-010-3999-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jcrysgro.2004.12.119", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028418858"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.biosystems.2010.04.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028585936"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00340-011-4375-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032916242", 
          "https://doi.org/10.1007/s00340-011-4375-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00340-010-3977-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034022499", 
          "https://doi.org/10.1007/s00340-010-3977-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00340-010-3977-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034022499", 
          "https://doi.org/10.1007/s00340-010-3977-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1364/oe.17.019969", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036476553"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1364/oe.17.019969", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036476553"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/11871842_29", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037233025", 
          "https://doi.org/10.1007/11871842_29"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/11871842_29", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037233025", 
          "https://doi.org/10.1007/11871842_29"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1090/s0002-9904-1952-09620-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037264252"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature10610", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037273098", 
          "https://doi.org/10.1038/nature10610"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1013689704352", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039349898", 
          "https://doi.org/10.1023/a:1013689704352"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/2093145.2093149", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039845694"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00340-012-5053-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045650074", 
          "https://doi.org/10.1007/s00340-012-5053-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/la400301p", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056157671"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/nl049322h", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056216042"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/nl049322h", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056216042"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.2968211", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057888331"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.4729003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058053007"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/biomet/25.3-4.285", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059415697"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevb.86.125407", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060640027"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevb.86.125407", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060640027"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.101.116801", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060754046"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.101.116801", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060754046"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.89.186802", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060825522"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.89.186802", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060825522"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.94.137404", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060830145"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.94.137404", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060830145"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/jstqe.2008.918110", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061335716"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/mm.2008.91", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061408631"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tmc.2010.65", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061690603"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1364/oe.18.00a544", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1065193471"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1364/oe.18.00a544", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1065193471"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.15248/proc.1.590", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1067654841"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/icdm.2009.52", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094569393"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/dyspan.2010.5457857", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094623925"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1109726843", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1201/9781584889731", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1109726843"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2013-12", 
    "datePublishedReg": "2013-12-01", 
    "description": "Decision-making is one of the most important intellectual abilities of the human brain. Here we propose an efficient decision-making system which uses optical energy transfer between quantum dots (QDs) mediated by optical near-field interactions occurring at scales far below the wavelength of light. The simulation results indicate that our system outperforms the softmax rule, which is known as the best-fitting algorithm for human decision-making behaviour. This suggests that we can produce a nano-system which makes decisions efficiently and adaptively by exploiting the intrinsic spatiotemporal dynamics involving QDs mediated by optical near-field interactions. ", 
    "genre": "research_article", 
    "id": "sg:pub.10.1038/srep02370", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.6060071", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1045337", 
        "issn": [
          "2045-2322"
        ], 
        "name": "Scientific Reports", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "3"
      }
    ], 
    "name": "Decision Maker based on Nanoscale Photo-excitation Transfer", 
    "pagination": "2370", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "b75ff28a03e427e6068c85c8012f49d03e685e47b3a27e64d546b7a59c21a8e1"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "23928655"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101563288"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/srep02370"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1038495311"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/srep02370", 
      "https://app.dimensions.ai/details/publication/pub.1038495311"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T16:03", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8664_00000591.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://www.nature.com/srep/2013/130809/srep02370/full/srep02370.html"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/srep02370'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/srep02370'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/srep02370'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/srep02370'


 

This table displays all metadata directly associated to this object as RDF triples.

263 TRIPLES      21 PREDICATES      74 URIs      32 LITERALS      20 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/srep02370 schema:about N097044e71f3b4440a498d773f544660c
2 N7c5524ea1d4449c7a544a3d6c5a242d0
3 N81a8ef4a563f421197d41f8e002d5a03
4 N8df2f1b24b054b2c97b73c9c65cf88a6
5 Nb255f0b4bcaf475e9df9b3b023337dc8
6 Ncb7cadc72c2149c6b8bfcab8a476c329
7 Nd4211560702048078b4b645ecda600ff
8 Nf17111a8b9ef49b0a82fcec480652c45
9 Nf321fca6c8704b40a85771bbfde1f1ee
10 Nff6a0fc9fc2b47e791eb5f8b50d66ae1
11 Nff840338a10047bb97d2835bc003fbb4
12 anzsrc-for:02
13 anzsrc-for:0205
14 schema:author N6e8c2e7e16b14ddda4062a533061cf4a
15 schema:citation sg:pub.10.1007/11871842_29
16 sg:pub.10.1007/978-3-642-13523-1_10
17 sg:pub.10.1007/s00340-010-3977-y
18 sg:pub.10.1007/s00340-010-3999-5
19 sg:pub.10.1007/s00340-011-4375-9
20 sg:pub.10.1007/s00340-011-4596-y
21 sg:pub.10.1007/s00340-012-5053-2
22 sg:pub.10.1023/a:1013689704352
23 sg:pub.10.1038/nature04766
24 sg:pub.10.1038/nature10610
25 https://app.dimensions.ai/details/publication/pub.1109726843
26 https://doi.org/10.1016/j.biosystems.2010.04.002
27 https://doi.org/10.1016/j.jcrysgro.2004.12.119
28 https://doi.org/10.1021/la400301p
29 https://doi.org/10.1021/nl049322h
30 https://doi.org/10.1063/1.2968211
31 https://doi.org/10.1063/1.4729003
32 https://doi.org/10.1090/s0002-9904-1952-09620-8
33 https://doi.org/10.1093/biomet/25.3-4.285
34 https://doi.org/10.1098/rstb.2007.2098
35 https://doi.org/10.1103/physrevb.86.125407
36 https://doi.org/10.1103/physrevlett.101.116801
37 https://doi.org/10.1103/physrevlett.89.186802
38 https://doi.org/10.1103/physrevlett.94.137404
39 https://doi.org/10.1109/dyspan.2010.5457857
40 https://doi.org/10.1109/icdm.2009.52
41 https://doi.org/10.1109/jstqe.2008.918110
42 https://doi.org/10.1109/mm.2008.91
43 https://doi.org/10.1109/tmc.2010.65
44 https://doi.org/10.1145/2093145.2093149
45 https://doi.org/10.1201/9781584889731
46 https://doi.org/10.1364/oe.17.019969
47 https://doi.org/10.1364/oe.18.00a544
48 https://doi.org/10.15248/proc.1.590
49 schema:datePublished 2013-12
50 schema:datePublishedReg 2013-12-01
51 schema:description Decision-making is one of the most important intellectual abilities of the human brain. Here we propose an efficient decision-making system which uses optical energy transfer between quantum dots (QDs) mediated by optical near-field interactions occurring at scales far below the wavelength of light. The simulation results indicate that our system outperforms the softmax rule, which is known as the best-fitting algorithm for human decision-making behaviour. This suggests that we can produce a nano-system which makes decisions efficiently and adaptively by exploiting the intrinsic spatiotemporal dynamics involving QDs mediated by optical near-field interactions.
52 schema:genre research_article
53 schema:inLanguage en
54 schema:isAccessibleForFree true
55 schema:isPartOf Nbeb24c89d654488c929f7b12ea0e9465
56 Ndd820ddb774b49d1844cac1fe929ba7a
57 sg:journal.1045337
58 schema:name Decision Maker based on Nanoscale Photo-excitation Transfer
59 schema:pagination 2370
60 schema:productId N3d23c1ad28424b3baec21f6c7605f0d3
61 N570091bfbc104a0e9bbcc962154763e4
62 Nce5f50416b1a455caa9da89ad9059cf9
63 Nd62130a577be43faa17535ad8cd3cfe2
64 Ndf719e6c6a984dc897e1087f7fef6a63
65 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038495311
66 https://doi.org/10.1038/srep02370
67 schema:sdDatePublished 2019-04-10T16:03
68 schema:sdLicense https://scigraph.springernature.com/explorer/license/
69 schema:sdPublisher Nc0ec94a3fa50422fa7c2636f8dc8a148
70 schema:url http://www.nature.com/srep/2013/130809/srep02370/full/srep02370.html
71 sgo:license sg:explorer/license/
72 sgo:sdDataset articles
73 rdf:type schema:ScholarlyArticle
74 N097044e71f3b4440a498d773f544660c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
75 schema:name Models, Theoretical
76 rdf:type schema:DefinedTerm
77 N1eb3d4543f8e48ed86a6a9c63392c8da rdf:first sg:person.01046230011.99
78 rdf:rest Nc6979c6908614760867ca2f87d82775d
79 N3145d8d8bd1d49cc9867caefd7239a9e rdf:first sg:person.01322136753.46
80 rdf:rest N1eb3d4543f8e48ed86a6a9c63392c8da
81 N3d23c1ad28424b3baec21f6c7605f0d3 schema:name nlm_unique_id
82 schema:value 101563288
83 rdf:type schema:PropertyValue
84 N570091bfbc104a0e9bbcc962154763e4 schema:name pubmed_id
85 schema:value 23928655
86 rdf:type schema:PropertyValue
87 N6e8c2e7e16b14ddda4062a533061cf4a rdf:first sg:person.01231756453.24
88 rdf:rest N9b0965c695be442888f228d7ba94546c
89 N7c5524ea1d4449c7a544a3d6c5a242d0 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
90 schema:name Algorithms
91 rdf:type schema:DefinedTerm
92 N81a8ef4a563f421197d41f8e002d5a03 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
93 schema:name Nanoparticles
94 rdf:type schema:DefinedTerm
95 N8df2f1b24b054b2c97b73c9c65cf88a6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
96 schema:name Quantum Dots
97 rdf:type schema:DefinedTerm
98 N9b0965c695be442888f228d7ba94546c rdf:first sg:person.0623123511.31
99 rdf:rest N3145d8d8bd1d49cc9867caefd7239a9e
100 Nb255f0b4bcaf475e9df9b3b023337dc8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
101 schema:name Light
102 rdf:type schema:DefinedTerm
103 Nbeb24c89d654488c929f7b12ea0e9465 schema:issueNumber 1
104 rdf:type schema:PublicationIssue
105 Nc0ec94a3fa50422fa7c2636f8dc8a148 schema:name Springer Nature - SN SciGraph project
106 rdf:type schema:Organization
107 Nc6979c6908614760867ca2f87d82775d rdf:first sg:person.010321266305.69
108 rdf:rest rdf:nil
109 Ncb7cadc72c2149c6b8bfcab8a476c329 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
110 schema:name Biomimetics
111 rdf:type schema:DefinedTerm
112 Nce5f50416b1a455caa9da89ad9059cf9 schema:name doi
113 schema:value 10.1038/srep02370
114 rdf:type schema:PropertyValue
115 Nd4211560702048078b4b645ecda600ff schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
116 schema:name Photons
117 rdf:type schema:DefinedTerm
118 Nd62130a577be43faa17535ad8cd3cfe2 schema:name readcube_id
119 schema:value b75ff28a03e427e6068c85c8012f49d03e685e47b3a27e64d546b7a59c21a8e1
120 rdf:type schema:PropertyValue
121 Ndd820ddb774b49d1844cac1fe929ba7a schema:volumeNumber 3
122 rdf:type schema:PublicationVolume
123 Ndf719e6c6a984dc897e1087f7fef6a63 schema:name dimensions_id
124 schema:value pub.1038495311
125 rdf:type schema:PropertyValue
126 Nf17111a8b9ef49b0a82fcec480652c45 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
127 schema:name Signal Processing, Computer-Assisted
128 rdf:type schema:DefinedTerm
129 Nf321fca6c8704b40a85771bbfde1f1ee schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
130 schema:name Energy Transfer
131 rdf:type schema:DefinedTerm
132 Nff6a0fc9fc2b47e791eb5f8b50d66ae1 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
133 schema:name Decision Making
134 rdf:type schema:DefinedTerm
135 Nff840338a10047bb97d2835bc003fbb4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
136 schema:name Computer Simulation
137 rdf:type schema:DefinedTerm
138 anzsrc-for:02 schema:inDefinedTermSet anzsrc-for:
139 schema:name Physical Sciences
140 rdf:type schema:DefinedTerm
141 anzsrc-for:0205 schema:inDefinedTermSet anzsrc-for:
142 schema:name Optical Physics
143 rdf:type schema:DefinedTerm
144 sg:grant.6060071 http://pending.schema.org/fundedItem sg:pub.10.1038/srep02370
145 rdf:type schema:MonetaryGrant
146 sg:journal.1045337 schema:issn 2045-2322
147 schema:name Scientific Reports
148 rdf:type schema:Periodical
149 sg:person.010321266305.69 schema:affiliation https://www.grid.ac/institutes/grid.32197.3e
150 schema:familyName Hara
151 schema:givenName Masahiko
152 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010321266305.69
153 rdf:type schema:Person
154 sg:person.01046230011.99 schema:affiliation https://www.grid.ac/institutes/grid.26999.3d
155 schema:familyName Ohtsu
156 schema:givenName Motoichi
157 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01046230011.99
158 rdf:type schema:Person
159 sg:person.01231756453.24 schema:affiliation https://www.grid.ac/institutes/grid.21941.3f
160 schema:familyName Kim
161 schema:givenName Song-Ju
162 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01231756453.24
163 rdf:type schema:Person
164 sg:person.01322136753.46 schema:affiliation https://www.grid.ac/institutes/grid.32197.3e
165 schema:familyName Aono
166 schema:givenName Masashi
167 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01322136753.46
168 rdf:type schema:Person
169 sg:person.0623123511.31 schema:affiliation https://www.grid.ac/institutes/grid.28312.3a
170 schema:familyName Naruse
171 schema:givenName Makoto
172 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0623123511.31
173 rdf:type schema:Person
174 sg:pub.10.1007/11871842_29 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037233025
175 https://doi.org/10.1007/11871842_29
176 rdf:type schema:CreativeWork
177 sg:pub.10.1007/978-3-642-13523-1_10 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002972792
178 https://doi.org/10.1007/978-3-642-13523-1_10
179 rdf:type schema:CreativeWork
180 sg:pub.10.1007/s00340-010-3977-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1034022499
181 https://doi.org/10.1007/s00340-010-3977-y
182 rdf:type schema:CreativeWork
183 sg:pub.10.1007/s00340-010-3999-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028202999
184 https://doi.org/10.1007/s00340-010-3999-5
185 rdf:type schema:CreativeWork
186 sg:pub.10.1007/s00340-011-4375-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032916242
187 https://doi.org/10.1007/s00340-011-4375-9
188 rdf:type schema:CreativeWork
189 sg:pub.10.1007/s00340-011-4596-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1028056307
190 https://doi.org/10.1007/s00340-011-4596-y
191 rdf:type schema:CreativeWork
192 sg:pub.10.1007/s00340-012-5053-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045650074
193 https://doi.org/10.1007/s00340-012-5053-2
194 rdf:type schema:CreativeWork
195 sg:pub.10.1023/a:1013689704352 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039349898
196 https://doi.org/10.1023/a:1013689704352
197 rdf:type schema:CreativeWork
198 sg:pub.10.1038/nature04766 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011628537
199 https://doi.org/10.1038/nature04766
200 rdf:type schema:CreativeWork
201 sg:pub.10.1038/nature10610 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037273098
202 https://doi.org/10.1038/nature10610
203 rdf:type schema:CreativeWork
204 https://app.dimensions.ai/details/publication/pub.1109726843 schema:CreativeWork
205 https://doi.org/10.1016/j.biosystems.2010.04.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028585936
206 rdf:type schema:CreativeWork
207 https://doi.org/10.1016/j.jcrysgro.2004.12.119 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028418858
208 rdf:type schema:CreativeWork
209 https://doi.org/10.1021/la400301p schema:sameAs https://app.dimensions.ai/details/publication/pub.1056157671
210 rdf:type schema:CreativeWork
211 https://doi.org/10.1021/nl049322h schema:sameAs https://app.dimensions.ai/details/publication/pub.1056216042
212 rdf:type schema:CreativeWork
213 https://doi.org/10.1063/1.2968211 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057888331
214 rdf:type schema:CreativeWork
215 https://doi.org/10.1063/1.4729003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058053007
216 rdf:type schema:CreativeWork
217 https://doi.org/10.1090/s0002-9904-1952-09620-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037264252
218 rdf:type schema:CreativeWork
219 https://doi.org/10.1093/biomet/25.3-4.285 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059415697
220 rdf:type schema:CreativeWork
221 https://doi.org/10.1098/rstb.2007.2098 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009990002
222 rdf:type schema:CreativeWork
223 https://doi.org/10.1103/physrevb.86.125407 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060640027
224 rdf:type schema:CreativeWork
225 https://doi.org/10.1103/physrevlett.101.116801 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060754046
226 rdf:type schema:CreativeWork
227 https://doi.org/10.1103/physrevlett.89.186802 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060825522
228 rdf:type schema:CreativeWork
229 https://doi.org/10.1103/physrevlett.94.137404 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060830145
230 rdf:type schema:CreativeWork
231 https://doi.org/10.1109/dyspan.2010.5457857 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094623925
232 rdf:type schema:CreativeWork
233 https://doi.org/10.1109/icdm.2009.52 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094569393
234 rdf:type schema:CreativeWork
235 https://doi.org/10.1109/jstqe.2008.918110 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061335716
236 rdf:type schema:CreativeWork
237 https://doi.org/10.1109/mm.2008.91 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061408631
238 rdf:type schema:CreativeWork
239 https://doi.org/10.1109/tmc.2010.65 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061690603
240 rdf:type schema:CreativeWork
241 https://doi.org/10.1145/2093145.2093149 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039845694
242 rdf:type schema:CreativeWork
243 https://doi.org/10.1201/9781584889731 schema:sameAs https://app.dimensions.ai/details/publication/pub.1109726843
244 rdf:type schema:CreativeWork
245 https://doi.org/10.1364/oe.17.019969 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036476553
246 rdf:type schema:CreativeWork
247 https://doi.org/10.1364/oe.18.00a544 schema:sameAs https://app.dimensions.ai/details/publication/pub.1065193471
248 rdf:type schema:CreativeWork
249 https://doi.org/10.15248/proc.1.590 schema:sameAs https://app.dimensions.ai/details/publication/pub.1067654841
250 rdf:type schema:CreativeWork
251 https://www.grid.ac/institutes/grid.21941.3f schema:alternateName National Institute for Materials Science
252 schema:name WPI Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
253 rdf:type schema:Organization
254 https://www.grid.ac/institutes/grid.26999.3d schema:alternateName University of Tokyo
255 schema:name Department of Electrical Engineering and Information Systems / Nanophotonics Research Center, Graduate School of Engineering, The University of Tokyo, 2-11-16 Yayoi, Bunkyo-ku, Tokyo 113-8656, Japan
256 rdf:type schema:Organization
257 https://www.grid.ac/institutes/grid.28312.3a schema:alternateName National Institute of Information and Communications Technology
258 schema:name Photonic Network Research Institute, National Institute of Information and Communications Technology, 4-2-1 Nukui-kita, Koganei, Tokyo 184-8795, Japan
259 rdf:type schema:Organization
260 https://www.grid.ac/institutes/grid.32197.3e schema:alternateName Tokyo Institute of Technology
261 schema:name Department of Electronic Chemistry, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, 4259 Nagatsuta, Midori-ku, Yokohama 226-8503, Japan
262 Earth-Life Science Institute, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8550, Japan
263 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...