Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Sign up for free
Menu
Search
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Pricing
Search
Sign in
Sign up for free
疎構造学習およびグラフ畳み込みニューラルネットワークによる異常検知 / Anomaly ...
Search
kumagallium
March 16, 2019
Research
2.7k
0
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
疎構造学習およびグラフ畳み込みニューラルネットワーク による異常検知 / Anomaly detection by the method combined with sparse structure learn- ing and graph convolutional neural network
情報処理学会 第81回全国大会
https://www.ipsj.or.jp/event/taikai/81/
kumagallium
March 16, 2019
More Decks by kumagallium
See All by kumagallium
研究所が作る実験科学者向けノート eureco
kumagallium
0
180
ITRCmeet48_MasayaKUMAGAI
kumagallium
0
140
FIT2020_MasayaKUMAGAI
kumagallium
1
260
(長尺版)超個体型データセンターにおける群知能クラスタリングの利用構想 / [Long version] Clustering using swarm intelligence for data center like superorganism
kumagallium
0
3.3k
超個体型データセンターにおける群知能クラスタリングの利用構想 / Clustering using swarm intelligence for data center like superorganism
kumagallium
0
390
私の研究のこれまでとこれから2019 / My past research and my future research
kumagallium
1
280
分野横断的思考を活かした機械学習の取り組み〜材料工学×情報工学〜 / Application of cross-disciplinary thinking for machine learning
kumagallium
2
3.5k
侵入検知システムのためのグラフ構造に基づいた機械学習および可視化 / Graph Based Machine Learning and Visualization for Intrusion Detection System
kumagallium
0
1.9k
Other Decks in Research
See All in Research
[ACL 2026 Demo] Fast-MIA: Efficient and Scalable Membership Inference for LLMs
upura
0
130
マーケットストリート 社会実験2024 in 秋葉原ジャンク通り 調査報告書
izumiyama_lab
1
150
[Fishers] DIVER OSINT CTF 2026 特化AIエージェントハーネスで挑戦するOSINT CTF
analokmaus
0
600
Ghost in the 7‑Zip: The Shadow of Residential Proxies Creeping into Your Life
nttcom
0
2.1k
COMETAを用いたデータ民主化運動の歴史
sazimai
0
250
XDPerf: A High-Performance Traffic Generator Built with WASM and eBPF
takehaya
1
300
多様なデータを許容し学習し続ける模倣学習 / Advanced Imitation Learning for VLA
prinlab
0
330
ros2-perf-multihost: 分散システムにおける客観的なアーキテクチャ評価フレームワーク
takasehideki
0
270
J-STAGEの現況と全文XML登載必須化について
xspa2012
0
270
[IR Reading 2026春 論文紹介] LLM-based Listwise Reranking under the Effect of Positional Bias (ECIR 2026) /IR-Reading-2026-Spring
koheishinden
PRO
0
430
Visual SLAM未来予測 / Future Prediction in Visual SLAM
koide3
1
1k
視覚若手の会LENSって何??
mickey_0226
0
210
Featured
See All Featured
JavaScript: Past, Present, and Future - NDC Porto 2020
reverentgeek
52
6.1k
StorybookのUI Testing Handbookを読んだ
zakiyama
31
6.9k
Design and Strategy: How to Deal with People Who Don’t "Get" Design
morganepeng
133
19k
Templates, Plugins, & Blocks: Oh My! Creating the theme that thinks of everything
marktimemedia
31
2.9k
Rails Girls Zürich Keynote
gr2m
96
14k
Why You Should Never Use an ORM
jnunemaker
PRO
61
10k
Scaling GitHub
holman
464
140k
Build your cross-platform service in a week with App Engine
jlugia
234
19k
The Success of Rails: Ensuring Growth for the Next 100 Years
eileencodes
47
8.3k
[RailsConf 2023] Rails as a piece of cake
palkan
59
7k
Design in an AI World
tapps
1
320
Paper Plane
katiecoart
PRO
4
53k
Transcript
1 6 0 0 89 13 - 24 89 -
24 89
എܠ త ఏҊख๏ ࣮ݧ݁Ռ τϥϑΟοΫσʔλͷάϥϑԽ ৵ೖݕ͓ΑͼՄࢹԽ
·ͱΊ
എܠ త ఏҊख๏ ࣮ݧ݁Ռ τϥϑΟοΫσʔλͷάϥϑԽ ৵ೖݕ͓ΑͼՄࢹԽ
·ͱΊ
ਤ μʔΫωοτʹ͓͚Δؒ૯؍ଌύέοτ ԯԯԯ ԯ ԯ ԯ ԯ ԯ
ԯ ԯ ԯ ਤ Πϯλʔωοτʹଓ͕Մೳͳػثٴͼηϯαʔ ωοτϫʔΫͷͱͯ͠ΘΕΔͷ ૯লใ௨৴നॻɿIUUQXXXTPVNVHPKQNFOV@TFJTBLVIBLVTZPJOEFYIUNM /*$5&3؍ଌϨϙʔτɿ IUUQTXXXOJDUHPKQDZCFSSFQPSU/*$5&3@SFQPSU@QEG զʑ͕ීஈར༻͢ΔΠϯλʔωοτɼεϚϗ*P5σόΠεͷٸͳීٴ ʹ͍ɼࠓ͔ܽ͢͜ͱ͕Ͱ͖ͳ͍ࣾձج൫ͱͳ͍ͬͯΔɽͱ͜Ζ͕ɼαΠό ʔ߈ܸͷڴҖʑ૿Ճ͍ͯ͠ΔɽͦͷͨΊɼαΠόʔ߈ܸରࡦͷඞཁੑ͕ߴ ·͖͍ͬͯͯΔɽ
α Π ό ʔ ߈ ܸ ର ࡦ
ͷ ̍ ͭ ͱ ͠ ͯ ɼ ෆ ਖ਼ ͳ ௨ ৴ Λ ݕ ͢ Δ ৵ೖݕγεςϜ *%4 *OUSVTJPO %FUFDUJPO 4ZTUFN ͕ଘࡏ͢Δɽ ಛʹ࠷ۙͰɼػցֶशܕ*%4ͷݚڀ͕ΜʹߦΘΕ͍ͯΔɽ σʔλͷେଟਖ਼ৗͰ͋ΔͱԾఆͯ͠ɼ ਖ਼ৗσʔλͷΈΛֶश͢Δख๏ • LNFBOT๏ • 0OFDMBTT47. ͳͲ ڭࢣͳֶ͠शܕ ϥϕϧͷ༩͕ෆཁ ֶश ৽نσʔλ ਖ਼ৗσʔλ ਖ਼ৗϞσϧ ਖ਼ৗϞσϧ ਖ਼ৗͷԾఆ͕͍͠ ڭࢣ͋Γֶशܕ ϥϕϧͷ͍ͭͨڭࢣσʔλΛֶश͢ Δख๏ • Lۙ๏ • χϡʔϥϧωοτϫʔΫ ͳͲ ਖ਼ৗσʔλ ҟৗσʔλ ֶश Ϟσϧ ৽نσʔλ Ϟσϧ ط߈ܸʢ·ͨྨࣅ߈ܸʣ ʹରͯ͠ߴ͍ݕ
ҟৗݕ τϥϑΟοΫ ݕূ ରॲ ͲΜͳҟৗʁ ຊʹҟৗʁ ਖ਼ৗҟৗ
ҟৗͷछྨ ख๏ ༧ଌਫ਼ ֶशର จݙ χϡʔϥϧωοτϫʔΫ ਖ਼ৗҟৗ αϙʔτϕΫλʔϚγϯ ਖ਼ৗҟৗ -45. ҟৗͷछྨʢछʣ ϕΠδΞϯωοτϫʔΫ ҟৗͷछྨʢछʣ ද ػցֶशܕ*%4ͷઌߦݚڀͷྫ ͢Ͱʹߴ͍༧ଌਫ਼͕ใࠂ͕ଘࡏ ଟ͘ͷ࣌ؒΛඅ͢ 4.VLLBNBMB FUBM 5SBJOJOH +,JNFUBM ``JO1SPD*OU$POG1MBUGPSN5FDIOPM4FSWJDF r 4$IFCSPMV FUBM $PNQVUFST4FDVSJUZ ݕূʹଟ͘ͷ࣌ؒΛඅ͢͜ͱΛආ͚ΔͨΊɼݕূͷॿ͚ʹͳΔஅࡐྉͷ ఏڙ͕ඞཁͰ͋Δɽ
ը૾ॲཧͷͰɼೖྗը૾ͷͲͷ෦͕ॏཁͰ͋Δ͔Λఆྔత͓Αͼ ͦΕʹج͍ͮͨՄࢹԽʹΑͬͯఆ݁ՌΛઆ໌͢Δख๏͕͢ͰʹఏҊ͞Ε͍ͯΔ ਤ ఆ݁ՌͷՄࢹԽʹΑΔઆ໌ΛՄೳʹͨ͠ઌߦݚڀ .3JCFJSP 44JOHIBOE$(VFTUSJO *O1SPDFFEJOHTPGUIFOE"$.4*(,%%*OUFS
OBUJPOBM$POGFSFODFPO,OPXMFEHF%JTDPWFSZBOE %BUB.JOJOH ,%% 3'POH "7FEBMEJ *O1SPDFFEJOHTPG1SPDFFEJOHTPGUIF*&&&*OUFSOBUJPOBM$POGFSFODFPO$PNQVUFS7JTJPO *$$7 ਤ ఆ݁ՌͷՄࢹԽʹΑΔઆ໌ΛՄೳʹͨ͠ઌߦݚڀ
ը૾ॲཧͷͰɼೖྗը૾ͷͲͷ෦͕ॏཁͰ͋Δ͔Λఆྔత͓Αͼ ͦΕʹج͍ͮͨՄࢹԽʹΑͬͯఆ݁ՌΛઆ໌͢Δख๏͕͢ͰʹఏҊ͞Ε͍ͯΔ ਤ ఆ݁ՌͷՄࢹԽʹΑΔઆ໌ΛՄೳʹͨ͠ઌߦݚڀ .3JCFJSP 44JOHIBOE$(VFTUSJO *O1SPDFFEJOHTPGUIFOE"$.4*(,%%*OUFS
OBUJPOBM$POGFSFODFPO,OPXMFEHF %JTDPWFSZBOE%BUB.JOJOH ,%% 3'POH "7FEBMEJ *O1SPDFFEJOHTPG1SPDFFEJOHTPGUIF*&&&*OUFSOBUJPOBM$POGFSFODFPO$PNQVUFS7JTJPO *$$7 ਤ ఆ݁ՌͷՄࢹԽʹΑΔઆ໌ΛՄೳʹͨ͠ઌߦݚڀ *%4ʹ͓͍ͯɼ τϥϑΟοΫͷͲͷཁૉ͕ݕ݁Ռʹରͯ͠Өڹ͍͔ͯͨ͠ Λ ఆྔతʹج͍ͮͨՄࢹԽʹΑͬͯઆ໌ Ͱ͖Εɼݕূͷॿ͚ͱͳΔ
DARPA 1998 Dataset
*1 5$1 )551 4:/ "$, ྫʣ ֤ϑΟʔϧυใɼϓϩτίϧʹैͬͨ࣌ܥྻతڍಈΛࣔ͢ɽ 4ZO 4ZO "DL "DL ྫ ΣΠϋϯυγΣΠΫ τϥϑΟοΫσʔλΛෳͷཁૉͱͦΕΒͷؔੑΛײతʹཧղͰ͖Δ άϥϑߏͰදݱ͢Δ͜ͱʹணͨ͠ɽ ҎԼͷఆٛʹΑΓɼτϥϑΟοΫΛάϥϑߏԽ͢Δɽ ϊʔυɿϑΟʔϧυใ ΤοδɿϑΟʔϧυใͷ࣌ܥྻతڍಈͷ૬ؔ άϥϑߏԽ
*1
5$1 )551 4:/ "$, 4ZO 4ZO "DL "DL 4ZO 4ZO "DL *1 5$1 )551 4:/ "$, ૬ؔؔͷ่Ε ڭࢣͳֶ͠श ˠ ҟৗ ˠ ਖ਼ৗ άϥϑߏԽ ྫʣ ϥϕϧͷ༩ ڭࢣ͋Γֶश τϥϑΟοΫͷάϥϑߏԽΛར༻͠ɼఆྔతʹج͍ͮͨՄࢹԽʹΑ ͬͯݕ݁Ռʢҟৗʣͷઆ໌͕Ͱ͖Δػցֶशܕ*%4ͷ࣮ݱΛతͱ͢Δɽ ຊݚڀͰண ՄࢹԽͷྫʣ ϊʔυ ෦άϥϑ 5*EF "$-P[BOP /"CFBOE:-JV 4QFFDIBOE4JHOBM1SPDFTTJOH *$"441
എܠ త ఏҊख๏ ࣮ݧ݁Ռ τϥϑΟοΫσʔλͷάϥϑԽ ৵ೖݕ͓ΑͼՄࢹԽ
·ͱΊ
ՄࢹԽ %"31" ෳͷ࣌ܥྻಛྔΛநग़ ରࠩܥྻσʔλͷม ඪ४Խ ૄߏֶशʢ(SBQIJDBM-BTTPʣ dڭࢣ͋Γֶश
d άϥϑΈࠐΈχϡʔϥϧωοτϫʔΫ άϥϑߏԽͨ͠τϥϑΟοΫσʔλʹج͍ͮͨػցֶशख๏Λར༻͢Δ ͜ͱʹΑΓɺ৵ೖݕ͓ΑͼՄࢹԽͷ྆ํΛ࣮ݱ͢Δɽ લॲཧ σʔληοτ άϥϑߏԽ ৵ೖݕ ֶशϞσϧ 'JOHFS1SJOU ػցֶशख๏
ि ༵ ߈໊ܸ ࣌ؒ ݄ GPSNBU
݄ GGC Ր MPBENPEVMF ʜ ʜ ʜ ʜ ۚ OFQUVOF ۚ TNVSG ۚ OFQUVOF ۚ CBDL ද %"31"%BUBTFUͷ߈ܸใ ఏҊख๏Ͱɼϥϕϧ͕༩͞ΕͨύέοτΩϟϓνϟܕͷτϥϑΟοΫ͕ ඞཁͰ͋ΔͨΊɼ%"31"Λ༻ͨ͠ɽຊσʔληοτɼԾతʹߏங ͨ͠ωοτϫʔΫͷ߈ܸΛఆͨ͠ͱ͖ͷ5DQEVNQσʔλ͓Αͼ߈ܸใΛ ఏڙ͍ͯ͠Δɽ 4:/GMPPE 4NVSG %"31"σʔληοτ dि ͷ͏ͪɼ िͷ༵ۚͷσʔλΛ༻ͨ͠ 4ZO 4ZO "DL QJOH
छྨͷ࣌ܥྻಛྔʹղ ରࠩ ࠩ ՄࢹԽ %"31" ෳͷ࣌ܥྻಛྔΛநग़ ରࠩܥྻσʔλͷม
ඪ४Խ ૄߏֶशʢ(SBQIJDBM-BTTPʣ dڭࢣ͋Γֶश d άϥϑΈࠐΈχϡʔϥϧωοτϫʔΫ ৵ೖݕ ֶशϞσϧ 'JOHFS1SJOU
ʜ ʜ ΟϯυαΠζ ຊݚڀͰɼ-੍͖ͷૄߏֶशख ๏Ͱ͋Δ(SBQIJDBM-BTTPΛར༻͠ɼͷ ΟϯυαΠζͰάϥϑߏԽͨ͠ɽ ՄࢹԽ %"31"
ෳͷ࣌ܥྻಛྔΛநग़ ରࠩܥྻσʔλͷม ඪ४Խ ૄߏֶशʢ(SBQIJDBM-BTTPʣ dڭࢣ͋Γֶश d άϥϑΈࠐΈχϡʔϥϧωοτϫʔΫ ৵ೖݕ ֶशϞσϧ 'JOHFS1SJOU
ʜ ʜ ΟϯυαΠζ
ग़ྗ: ʢਖ਼ৗҟৗʣ ྨ 1PPMJOH 'JOHFSQSJOU 1PPMJOH 'JOHFSQSJOU ̍ۙ ۙ ʜ ʜ // ˎ 8 ˎ 8 ˎ 8 $POW $POW ˎ 8 ˎ 8 ˎ 8 ೖྗ άϥϑΈࠐΈχϡʔϥϧωοτϫʔΫ 'JOHFSQSJOUɿ ࠷େۙɿ ӅΕαΠζɿ όοναΠζɿ ΤϙοΫɿ σʔλͷׂ߹ʢ܇࿅ɿݕূʣɿ70:30 ($//ͷֶशύϥϝʔλ %"31" ෳͷ࣌ܥྻಛྔΛநग़ ରࠩܥྻσʔλͷม ඪ४Խ ૄߏֶशʢ(SBQIJDBM-BTTPʣ dڭࢣ͋Γֶश d άϥϑΈࠐΈχϡʔϥϧωοτϫʔΫ ՄࢹԽ ৵ೖݕ ֶशϞσϧ 'JOHFS1SJOU
άϥϑΈࠐΈχϡʔϥϧωοτϫʔΫʢ($//ʣ IUUQTMJCSBSZOBJTUKQNZMJNFEJPEMMJNFEJPTIPXQEGDHJ%-1%'3@1 $//ͷ߹ ($//ͷ߹ $//ͷ߹ɼݩը૾ͱϑΟϧλʔͱͷΈࠐΈԋࢉʹΑΓɼಛఆըૉͱपΓ ͷըૉͱͷؔੑʢಛʣΛ࣍ͷͱ͢ɽ($//ɼϊʔυʹΑͬͯۙϊ ʔυͷҟͳΔ͕ɼ$//ͱಉ༷ʹϊʔυͱͦͷपΓͷϊʔυͱͷؔੑΛ ΈࠐΈԋࢉʹΑΓ࣍ͷͱ͢ɽ
ਤ άϥϑΈࠐΈχϡʔϥϧωοτϫʔΫͷུ֓ਤ͓Αͼάϥϑදݱ ਤ ΈࠐΈԋࢉͷྫ͓Αͼάϥϑදݱ ग़ྗ: ʢਖ਼ৗҟৗʣ ྨ 1PPMJOH 'JOHFSQSJOU 1PPMJOH 'JOHFSQSJOU ̍ۙ ۙ ʜ ʜ // ˎ 8 ˎ 8 ˎ 8 $POW $POW ˎ 8 ˎ 8 ˎ 8 ೖྗ ݩը૾ ϑΟϧλʔ I I I I
άϥϑΈࠐΈχϡʔϥϧωοτϫʔΫʢ($//ʣ %BWJE%VWFOBVE FUBM *OUIF1SPD/*14 .POUSFBM $BOBEB %FDFNFCFS
ຊݚڀͰɼ($//ͷதͰ/'1 /FVSBM 'JOHFS 1SJOUΛར༻͢Δɽઌߦݚڀ ͰɼಟੑͳͲͷߴਫ਼ͳ༧ଌʹޭ͠ɼ'JOHFS 1SJOUͷੜʹޭͨ͠ɽ 'JOHFS 1SJOUɼೖྗͨ͠άϥϑߏΛ࣍ݩϕΫτϧͰදݱͨ͠ͷͰ͋Δɽ ֤Ϗοτ͕෦άϥϑʹ૬͠ɼ͕݁Ռʢಟੑʣʹର͢ΔӨڹ ʹ૬͢Δɽ ਤ ಟੑΛ༧ଌ͢ΔͨΊʹ࠷దԽ͞Εͨ'JOHFS1SJOUͷՄࢹԽ ग़ྗ: ʢਖ਼ৗҟৗʣ ྨ 1PPMJOH 'JOHFSQSJOU 1PPMJOH 'JOHFSQSJOU ̍ۙ ۙ ʜ ʜ // ˎ 8 ˎ 8 ˎ 8 $POW $POW ˎ 8 ˎ 8 ˎ 8 ೖྗ ಟ ੑ ʜ ˞ਖ਼֬ʹɼͰͳ͘d·Ͱͷ 'JOHFS1SJOU ਤ /'1ͷωοτϫʔΫུ֓ਤ
άϥϑΈࠐΈχϡʔϥϧωοτϫʔΫʢ($//ʣ %BWJE%VWFOBVE FUBM *OUIF1SPD/*14 .POUSFBM $BOBEB %FDFNFCFS
ຊݚڀͰɼ($//ͷதͰ/'1 /FVSBM 'JOHFS 1SJOUΛར༻͢Δɽઌߦݚڀ ͰɼಟੑͳͲͷߴਫ਼ͳ༧ଌʹޭ͠ɼ'JOHFS 1SJOUͷੜʹޭͨ͠ɽ 'JOHFS 1SJOUɼೖྗͨ͠άϥϑߏΛ࣍ݩϕΫτϧͰදݱͨ͠ͷͰ͋Δɽ ֤Ϗοτ͕෦άϥϑʹ૬͠ɼ͕݁Ռʢಟੑʣʹର͢ΔӨڹ ʹ૬͢Δɽ ਤ ಟੑΛ༧ଌ͢ΔͨΊʹ࠷దԽ͞Εͨ'JOHFS1SJOUͷՄࢹԽ ग़ྗ: ʢਖ਼ৗҟৗʣ ྨ 1PPMJOH 'JOHFSQSJOU 1PPMJOH 'JOHFSQSJOU ̍ۙ ۙ ʜ ʜ // ˎ 8 ˎ 8 ˎ 8 $POW $POW ˎ 8 ˎ 8 ˎ 8 ೖྗ ಟ ੑ ʜ ˞ਖ਼֬ʹɼͰͳ͘d·Ͱͷ 'JOHFS1SJOU ਤ /'1ͷωοτϫʔΫུ֓ਤ άϥϑԽͨ͠τϥϑΟοΫσʔλΛ($//Ͱֶश͢Δ͜ͱʹΑΓɼ ݕ݁ՌʢҟৗʣΛઆ໌Ͱ͖Δ෦άϥϑͷՄࢹԽ͕Ͱ͖Δͱߟ͑ΒΕΔɽ
ʜ ʜ ΟϯυαΠζ
ग़ྗ: ʢਖ਼ৗҟৗʣ ྨ 1PPMJOH 'JOHFSQSJOU 1PPMJOH 'JOHFSQSJOU ̍ۙ ۙ ʜ ʜ // ˎ 8 ˎ 8 ˎ 8 $POW $POW ˎ 8 ˎ 8 ˎ 8 ೖྗ άϥϑΈࠐΈχϡʔϥϧωοτϫʔΫ 'JOHFSQSJOUɿ ࠷େۙɿ ӅΕαΠζɿ όοναΠζɿ ΤϙοΫɿ σʔλͷׂ߹ʢ܇࿅ɿݕূʣɿ70:30 ($//ͷֶशύϥϝʔλ ՄࢹԽ %"31" ෳͷ࣌ܥྻಛྔΛநग़ ରࠩܥྻσʔλͷม ඪ४Խ ૄߏֶशʢ(SBQIJDBM-BTTPʣ dڭࢣ͋Γֶश d άϥϑΈࠐΈχϡʔϥϧωοτϫʔΫ ৵ೖݕ ֶशϞσϧ 'JOHFS1SJOU
എܠ త ఏҊख๏ ࣮ݧ݁Ռ τϥϑΟοΫσʔλͷάϥϑԽ ৵ೖݕ͓ΑͼՄࢹԽ
·ͱΊ
τϥϑΟοΫσʔλͷάϥϑԽ छྨͷ࣌ܥྻಛྔʹ- ੍͖ͷૄߏֶशख๏(SBQIJDBM -BTTPΛద ༻ͨ݁͠Ռɼૄͳ૬ؔؔͷάϥϑߏ͕ಘΒΕΔ͜ͱΛ֬ೝͨ͠ɽ ૄͳάϥϑߏʹ͢Δ͜ͱʹΑΓɼใྔͷѹॖϊΠζͷؤڧੑʹ༗ޮͰ ͋Δͱߟ͑ΒΕΔɽ (SBQIJDBM-BTTP ਤ
τϥϑΟοΫσʔλ͔Β࡞ͨ͠άϥϑߏ(SBQIJDBM-BTTPͷద༻લ͓Αͼ ద༻ޙ
എܠ త ఏҊख๏ ࣮ݧ݁Ռ τϥϑΟοΫσʔλͷάϥϑԽ ৵ೖݕ͓ΑͼՄࢹԽ
·ͱΊ
ਖ਼ղσʔλ ༧ଌ݁Ռ άϥϑߏԽͨ͠τϥϑΟοΫσʔλΛ($//Ͱֶशͨ݁͠Ռɼ༧ଌਫ਼͕ ͱͳͬͨɽ͜ͷઌߦݚڀͰใࠂ͞Ε͍ͯΔͱಉఔʹߴ͍Ͱ͋Δɽ ਤ ਖ਼ղσʔλ͓ΑͼֶशϞσϧʹΑΔ༧ଌ݁Ռ
ख๏ ༧ଌਫ਼ จݙ χϡʔϥϧωοτϫʔΫ αϙʔτϕΫλʔϚγϯ -45. ϕΠδΞϯωοτϫʔΫ ද ػցֶशܕ*%4ͷઌߦݚڀͷྫ 4.VLLBNBMB FUBM 5SBJOJOH +,JNFUBM ``JO1SPD*OU$POG1MBUGPSN5FDIOPM4FSWJDF r 4$IFCSPMV FUBM $PNQVUFST4FDVSJUZ
($//Ͱֶशͨ͠ϞσϧΛར༻͠ɼ'JOHFS 1SJOUͷऔಘʹޭͨ͠ɽ 4:/GMPPE߈ܸ࣌ɼҟৗ͕ݕ͞Εɼ'JOHFS 1SJOUͰߴ͍ӨڹΛࣔ͢෦ άϥϑɼ)551ͱ4:/ͷ૬ؔؔʹؔ࿈͢ΔͷͰ͋ͬͨɽ (a)
(b) ਤ 'JOHFSQSJOU͓ΑͼҟৗͷཁҼͱͳͬͨ෦άϥϑͷҰྫ4:/qPPE߈ܸ ෦άϥϑ 'JOHFS1SJOU Өڹ
4NVSG߈ܸ࣌ɼ'JOHFS1SJOUͷӨڹͷߴ͍෦άϥϑɼૹ৴ݩ*1͓Αͼ *$.1ͷ૬ؔؔʹؔ࿈͢ΔͷͰ͋ͬͨɽ ఏҊख๏ᶄͰϊʔυؒͷ૬ؔؔʢ෦άϥϑʣͷՄࢹԽͰ͖ΔͨΊɼϊ ʔυͷՄࢹԽͷΈͰ͋ͬͨఏҊख๏ᶃΑΓ۩ମతͳઆ໌ੑ͕ظͰ͖Δɽ (b) ਤ
'JOHFSQSJOU͓ΑͼҟৗͷཁҼͱͳͬͨ෦άϥϑͷҰྫ4:/GMPPE߈ܸ ෦άϥϑ 'JOHFS1SJOU Өڹ
ग़ྗ: ʢਖ਼ৗҟৗʣ ྨ 1PPMJOH 'JOHFSQSJOU 1PPMJOH 'JOHFSQSJOU ̍ۙ ۙ ʜ ʜ // ˎ 8 ˎ 8 ˎ 8 $POW $POW ˎ 8 ˎ 8 ˎ 8 ೖྗ ($//Ͱɺ ਖ਼ৗঢ়ଶ͓Αͼҟৗঢ়ଶΛ෦άϥϑ୯ҐͰֶश͢ΔͨΊɼෳͷਖ਼ৗঢ় ଶ͕ଘࡏ͢Δ߹ʹؤڧͳݕ͕ظͰ͖Δɽ ਤ /'1ͷωοτϫʔΫུ֓ਤ Ұൠతͳڭࢣͳֶ͠शͰɺ ୯Ұͷਖ਼ৗঢ়ଶΛԾఆ͢Δ߹ɼෳͷਖ਼ৗঢ়ଶʢ࣌ؒґଘڥґଘͳͲʣ ͕ଘࡏͨ͠ࡍʹޡݕ͢Δ߹͕༧͞ΕΔɽ
എܠ త ఏҊख๏ ࣮ݧ݁Ռ τϥϑΟοΫσʔλͷάϥϑԽ ৵ೖݕ͓ΑͼՄࢹԽ
·ͱΊ
·ͱΊ • τϥϑΟοΫσʔλͷάϥϑߏԽʹޭͨ͠ɽ • άϥϑߏʹج͍ͮͨػցֶशख๏ΛఏҊͨ͠ɽ • ৵ೖݕͷΈͳΒͣɼݕ݁ՌΛఆྔతͳ ʹج͍ͮͨϊʔυ෦άϥϑͷՄࢹԽʹΑͬ
ͯઆ໌Ͱ͖Δ*%4࣮ݱͷՄೳੑΛࣔͨ͠ɽ ࠓޙͷ՝ • ࠷৽σʔληοτͰͷ༗ޮੑݕূ • ϊʔυʢ࣌ܥྻಛྔʣͷछྨͷ࠶ݕ౼ • 'JOHFS1SJOUͷΫϥελϦϯάʹΑΔઆ໌ੑͷ ্ • άϥϑߏʹର͢Δ"VUP&ODPSEFSͳͲɺڭࢣ ͳֶ͠शΛར༻ͨ͠*%4ͷݕ౼ ͝ਗ਼ௌ͋Γ͕ͱ͏͍͟͝·ͨ͠ %"31" ෳͷ࣌ܥྻಛྔΛநग़ ରࠩܥྻσʔλͷม ඪ४Խ ૄߏֶशʢ(SBQIJDBM-BTTPʣ ՄࢹԽ dڭࢣ͋Γֶश d άϥϑΈࠐΈχϡʔϥϧωοτϫʔΫ ৵ೖݕ ֶशϞσϧ 'JOHFS1SJOU