Personal Software Process /Team Software Process (PSP/TSP) Watts Humphrey PSP/TSP PSP/TSP TaskPit TaskPit PSP/TSP TaskiPit PSP/TSP 5 5

Size: px
Start display at page:

Download "Personal Software Process /Team Software Process (PSP/TSP) Watts Humphrey PSP/TSP PSP/TSP TaskPit TaskPit PSP/TSP TaskiPit PSP/TSP 5 5"

Transcription

1

2 Personal Software Process /Team Software Process (PSP/TSP) Watts Humphrey PSP/TSP PSP/TSP TaskPit TaskPit PSP/TSP TaskiPit PSP/TSP 5 5

3 PSP/TSP TaskPit

4 1 Personal Software Process /Team Software Process (PSP/TSP) Watts Humphrey [1] PSP/TSP PSP/TSP [2][3][4] TaskPit[6] TaskPit WINWORD.EXE.docx.docx 1 1 Random Forests 5 1

5 2 2.1 PSP/TSP Watts PSP/TSP PSP/TSP PSP/TSP 1996 Process Dashboard[2] Task Coach[3] Slim Timer[4] TaskPit[6] Task Pit TaskPit 2.2 Michael [5] Michael Web PowerPoint Naive Bayes(NB) Linear Support Vector Machine(SVM) k-nearest Neighbor(k-NN) Michael NB -NN Michael Web 2

6 3

7 3 Random Forests TaskPit = [ B C ] (1) = [ ] = [ ] = [ ] 1 4

8 仕様書上での作業設計書上での作業開発環境上での作業 作業目的 = 実装 仕様書上での作業 設計書上での作業 作業目的 = 設計 作業目的 = テスト 仕様書上での作業設計書上での作業開発環境上での作業 :: クリックの多さ :: 打鍵の多さ TaskPit TaskPit PSP/TSP 2 TaskPit 1 Word Eclipse Word Word spec TaskPit 3 TaskPit TaskPit 4 TaskLog 5

9 TaskPit 2 TaskPit = TeraPad.exe notepad.exe WINWORD.EXE Acrobat.exe LabyTex.exe = POWERPNT.EXE = EXCEL.EXE Rgui.exe javaw.exe:weka javaw.exe:gemx = eclipse.exe devenv.exe EXCEL.EXE:Microsoft Visual Basic = devenv.exe: TaskPit = TaskPit.exe TaskAnalyzer.exe = iexplore.exe firefox.exe Safari.exe chrome.exe = thunderbird.exe Outlook.exe iexplore.exe:gmail 3,,,,,, , ,0,0,0 TaskPit, , ,3,0,0, , ,2,0,0, , ,1,0,0, , ,5,0,2, , ,24,0,64, , ,2,0,0 TaskPit, , ,1,0,0, , ,2,0,0 4 6

10 3.3 Random Forests[7] Random Forests R Random Forests ntree mtry M Breiman ntree = 500 mtry = M Random Forests P M 1. P P N N B1 B2 Bi BN 1/3 OOB(Out- Of-Bag) 2. Bi Ti Random Forests OOB OOB Ti mtry 3. Bi OOB 7

11 4 5 TaskPit TaskPit TaskPit 12/16 12/22 5 OS CPU 5 3 Windows7 Core2 Duo E Windows Vista Core2 Duo E Microsoft Office Word Microsoft VisualStudio Eclipse 4.3 TaskPit 5 6 TaskPit 8

12 PSP/TSP TaskPit,,,, TaskPit,19,12,0, TaskPit,3,0,0,,35,3,153,,2,0,0,,12,0,0,,9,0,0,,9,0,4,,1,0,0,,1,0,0, 6 / 9

13 ) 2) 1 3) 2 3) 3 2-fold-cross-validation 1 1 recall( ) precision( ) F1-value(F1 ) X 2 A X X B X X C X X D X X 1 ( ) ( ) ( ) ( ) ( ) ( )

14 2 X X X A B X C D 2 X X precision A B 1 precision = A A + B precision 0 1 X X X recall A C 3 recall = A A + C recall 0 1 X X recall precision X X X X X X F1-value F1-value precision recall 4 F 1 value = 2 1 precision + 1 recall F1-value 0 1 precision recall F1-value 11 (2) (3) (4)

15 10 12

16 precision recall F1-value precision 13

17 8 recall 9 F1-value F1-value recall % Twitter Twitter 14

18 11 Twitter 3 Twitter 4 3 precision recall ,,,, Twitter,1,0,0,,1,0,1, Twitter,3,0,7,,11,0,14, Twitter,1,0,8,,26,0,0, Twitter,1,0,0,,53,10,52, Twitter,1,0,0,,1,0,0, Twitter,1,0,0,,1,0,0, Twitter,1,0,0,,19,2,1, Twitter,1,0,5,,1,0,0, Twitter,2,0,74, 10 ( ) 15

19 6 3 F1-value ,,,, Twitter,1,0,0, ( ),1,0,0, ( ),3,0,0, ( ) Twitter,1,0,2, ( ),1,0,0, ( ),4,0,0, ( ),1,0,0, ( ) or,1,0,0, ( ) Twitter,1,0,0, ( ),1,0,0, ( ) or,1,0,0, ( ),2,0,0, ( ),1,0,0, ( ) or,1,0,0, ( ),11,0,5, ( ),2,0,0, ( ),0,0,0, ( ),0,0,0, ( ) Random Forests

20 PSP/TSP TaskPit TaskPit 17

21 18

22 6 TaskPit TaskPit TaskPit PSP/TSP TaskPit 19

23 1 20

24 [1] Humphrey Watts S May 2001 [2] Process Dashboard [3] Task Coach Your friendly task manager [4] SlimTimer Time Tracking without the Timesheet [5] Granitzer Michael and Rath Andreas S and Kroll Mark and Seifert Christin and Ipsmiller Doris and Devaurs Didier and Weber Nicolas and Lindstaedt Stefanie N Machine Learning based Work Task Classification Journal of Digital Information Management October 2009 pp (2009) [6] XV FOSE2008 pp , Nov [7] Breiman, L Random Forests, Machine Learning Vol.45 No.1 pp.5 32 (2001) 21

Vol. 29 No. 1 Feb. 2012 79,,, PC TaskPit Manic Time [3] 4 TaskPit Task Task Aim Task Aim Task Aim Aim Task Task Task Random Forests Aim Task Task Aim

Vol. 29 No. 1 Feb. 2012 79,,, PC TaskPit Manic Time [3] 4 TaskPit Task Task Aim Task Aim Task Aim Aim Task Task Task Random Forests Aim Task Task Aim 78 PSP (Task) (Aim) Task Task Aim Task RandomForest Task 97 In this paper we propose a method to support Personal Software Process (PSP), which is a well known software process improvement framework for

More information

TaskPit TaskPit TaskPit TaskPit 3 TaskPit Windows OS PC CPU 2 TaskPit TaskPit Windows OS CPU 1 10 TaskPit

TaskPit TaskPit TaskPit TaskPit 3 TaskPit Windows OS PC CPU 2 TaskPit TaskPit Windows OS CPU 1 10 TaskPit 28 29 2 16 TaskPit TaskPit TaskPit TaskPit 3 TaskPit Windows OS PC CPU 2 TaskPit TaskPit Windows OS CPU 1 10 TaskPit 1 3 2 4 3 6 3.1............... 6 3.2............................... 6 3.3...............................

More information

Microsoft PowerPoint - TaskPit_Introduction_V04.ppt [互換モード]

Microsoft PowerPoint - TaskPit_Introduction_V04.ppt [互換モード] http://taskpit.jpn.org/ ソフトウェア開発行動記録システム Taskpit 2011 年 12 月 8 日 門田暁人奈良先端科学技術大学院大学 akito-m@is.naist.jp 研究の背景 近年あらゆるデスクワークはコンピュータによって効率化されてきた. 例 : 情報検索, 文書作成, データ分析 一方, コンピュータを利用するが故に増えた無駄な作業も存在する. 例 :Webサーフィン,

More information

PSP/TSP 27 35% Word Eclipse c 21 Information Processing Society of Japan

PSP/TSP 27 35% Word Eclipse c 21 Information Processing Society of Japan 1 1 1 1 11 3 7 1 28%, 62% 86% Working Time Measurement for Improving Awareness in Deskwork Yosuke Shimomura, 1 Tatsuya Kuramoto, 1 Akito Monden 1 and Ken-ichi Matsumoto 1 To increase productivity of any

More information

Microsoft Word - fose2013_V12short.docx

Microsoft Word - fose2013_V12short.docx ソフトウェア開発企業における開発タスクの自動計測 Automatic Measurement of Software Development Tasks in Software Companies *1 門田暁人 *2 上野秀剛 *3 荒木健史 *4 山田欣吾 *5 松本健一 あらまし本稿では, 開発行動記録システム TaskPit を開発組織に適用した結果について報告する.12 名の開発者を 6

More information

立ち読みページ

立ち読みページ 1 Word 1-1 33 1-2 45 1-3 54 1-4 Office Word 2007 66 1 1-1 1-1-1 33 Word FAX 1 1 2 1 Office Windows 7 Windows Vista Windows XP 3 4 5 6 34 2 Office Microsoft Office Online 35 1-1-2 1 2 3 4 5 6 2 1 1 36 37

More information

untitled

untitled MS-PowerPoint 2007 2009 8 Microsoft Office PowerPoint 2007 Microsoft Office PowerPoint 2007 PowerPoint 1 PowerPoint 1.1 PowerPoint 1.2 PowerPoint PowerPoint 2 . 2.1 PowerPoint 3 2.2 PowerPoint 4 2.3 5

More information

-1-1 1 1 1 1 12 31 2 2 3 4

-1-1 1 1 1 1 12 31 2 2 3 4 2007 -1-1 1 1 1 1 12 31 2 2 3 4 -2-5 6 CPU 3 Windows98 1 -3-2. 3. -4-4 2 5 1 1 1 -5- 50000 50000 50000 50000 50000 50000 50000 50000 50000 50000-6- -7-1 Windows 2 -8-1 2 3 4 - - 100,000 200,000 500,000

More information

蜷咲ァー譛ェ險ュ螳・3

蜷咲ァー譛ェ險ュ螳・3 2011. October vol.606 2 3 2011. October vol.606 4 5 ' 2011. October vol.606 6 7 2011. October vol.606 8 毎 月 18 日 は 9 2011. October vol.606 10 4 4 11 2011. October vol.606 12 39 12 254 13 2011. October

More information

untitled

untitled 16 4 1 17 1 50 -1- -2- -3- -4- -5- -6- -7- 1 2-8- -9- -10- -11- Web -12- (1) (2)(1) (3) (4) (1)()(2) (3)(4) -13- -14- -15- -16- -17- -18- -19- -20- -21- -22- -23- (2)(1) (3) -24- -25- -26- -27- -28- -29-

More information

untitled

untitled 2007 55 2 255 268 c 2007 2007 1 24 2007 10 30 k 10 200 11 110 6 60 3 1. 1 19 Mendenhall 1887 Dickens, 1812 1870 Thackeray, 1811 1863 Mill, 1806 1873 1960 610 0394 1 3 256 55 2 2007 Sebastiani 2002 k k

More information

インテル® VTune™ パフォーマンス・アナライザー 9.1 Windows* 版

インテル® VTune™ パフォーマンス・アナライザー 9.1 Windows* 版 VTune 9.1 Windows* ................................. 3...................... 3.................................................. 3............................................ 4 :.........................4................................................

More information

imageWARE Prepress Manager V1カタログ

imageWARE Prepress Manager V1カタログ imageware Prepress Manager 1 Word Excel PowerPoint imageware Prepress Manager 2 imageware Prepress Manager 2 imageware Prepress Manager 2 imageware Prepress Manager 2 3 4 imageware Prepress Manager 5 imageware

More information

2

2 2 3 4 5 6 1 2 7 Windows Me Microsoft Office XP Personal Easy CD Creator4 8 9 DIGITAL 10 11 12 1 3 2 13 1 2 14 3 15 1 2 3 16 4 17 1 2 18 3 1 4 5 1 2 3 4 19 1 2 3 20 4 5 21 1 2 1 22 2 3 1 23 1 2 3 4 24 1

More information

bag-of-words bag-of-keypoints Web bagof-keypoints Nearest Neighbor SVM Nearest Neighbor SIFT Nearest Neighbor bag-of-keypoints Nearest Neighbor SVM 84

bag-of-words bag-of-keypoints Web bagof-keypoints Nearest Neighbor SVM Nearest Neighbor SIFT Nearest Neighbor bag-of-keypoints Nearest Neighbor SVM 84 Bag-of-Keypoints Web G.Csurka bag-of-keypoints Web Bag-of-keypoints SVM 5.% Web Image Classification with Bag-of-Keypoints Taichi joutou and Keiji yanai Recently, need for generic image recognition is

More information

24 SPAM Performance Comparison of Machine Learning Algorithms for SPAM Discrimination

24 SPAM Performance Comparison of Machine Learning Algorithms for SPAM Discrimination 24 SPAM Performance Comparison of Machine Learning Algorithms for SPAM Discrimination 1130378 2013 3 9 SPAM SPAM SPAM SPAM SVM AdaBoost RandomForest SPAM SPAM UCI Machine Learning Repository Spambase 4601

More information

Visual Studio ( )

Visual Studio ( ) 2013 2 (2014 9 ) IT IT 1 IT & UI UI + IT Application Insights Team Foundation Server + Web 2 Windows Web C#Visual Basic 4 6 Team Foundation Server 1 8 10 3 Windows Windows Windows C#Visual BasicVisual

More information

RubyWorld Conference 2011, Sep 5 2011 [6] 1 2 3 4-2SD -2SD -2SD -2SD [s] 56.9 68.8 33.7 36.6 27.1 29.1 22.5 24.0 21.8 20.5 22.9 22.3 24.3 24.0 24.4 24.2 [s] 101.9 115.1 85.2 92.8 57.1 62.9 42.5 46.3

More information

P24-25.eps

P24-25.eps Contents 1 24 26 32 44 23 24 25 2-1 1 2 3 1: 2: 3: 26 27 28 29 Action A Thinking T Team Work W A Action W T Thinking Team Work 30 31 3-1 3-2 32 33 b. c. 1 d. e. 1 a. 2 2 34 35 3 4 36 37 38 39 3-3 3-4 1

More information

: : : : ) ) 1. d ij f i e i x i v j m a ij m f ij n x i =

: : : : ) ) 1. d ij f i e i x i v j m a ij m f ij n x i = 1 1980 1) 1 2 3 19721960 1965 2) 1999 1 69 1980 1972: 55 1999: 179 2041999: 210 211 1999: 211 3 2003 1987 92 97 3) 1960 1965 1970 1985 1990 1995 4) 1. d ij f i e i x i v j m a ij m f ij n x i = n d ij

More information

15ol

15ol 2010. October vol.594 2 3 2010. October vol.594 4 (営業時間:10 時~18 時) (営業時間:11 時~22 時) (営業時間:9時~18 時) (開館時間:9時~21 時30 分) 5 6 2010. October vol.594 ' 4 4 4 7 8 2010. October vol.594 9 11 12 2010. October vol.594

More information

講習案内パンフレット2000.PDF

講習案内パンフレット2000.PDF 1 OA Visio Visio 1 Visio VI2000-N Microsoft Visio2000 Web IN50-N Projcet2000 1 PR2000-O Project Outlook Outlook OL98-O Outlook Outlook OL98-M Outlook Access Excel PowerPoint PowerPoint Word Word 2 AC2000-O

More information

Windows PC/ BCP () PC (BYOD: Bring Your Own Device) Windows 8 2 Windows 8 Windows 8 Windows Windows 8 Windows 8 Windows 8 PC/ 2

Windows PC/ BCP () PC (BYOD: Bring Your Own Device) Windows 8 2 Windows 8 Windows 8 Windows Windows 8 Windows 8 Windows 8 PC/ 2 Windows 8 1 (2012 10 ) Windows PC/ BCP () PC (BYOD: Bring Your Own Device) Windows 8 2 Windows 8 Windows 8 Windows Windows 8 Windows 8 Windows 8 PC/ 2 PC/ IT 4 5 PC 6 7 PC 8 9 3 1 SharePoint PC PC Windows

More information

i

i 2012 2013 3 29 (: A9TB2133) i 1 1 2 5 2.1.............................. 5 2.2.............................. 6 3 1-7 3.1................................. 7 3.2.................................. 8 3.3.................................

More information

Oracle Policy Automation 10.0システム要件

Oracle Policy Automation 10.0システム要件 Oracle Policy Automation 10.0 システム要件 2009 年 12 月 - バージョン 1.01 Oracle Policy Automation 製品 バージョン 10.00 の概要 製品 プラットフォーム Oracle Policy Modeling Microsoft Windows( デスクトップ ) Oracle Policy Automation( ランタイム

More information

ViewSonic Corporation, Macintosh Power Macintosh Microsoft Windows Windows ViewSonic 3 OnView ViewMatch ViewMeter ViewSonic ViewSonic, ViewSonic

ViewSonic Corporation, Macintosh Power Macintosh Microsoft Windows Windows ViewSonic 3 OnView ViewMatch ViewMeter ViewSonic ViewSonic, ViewSonic PJ-PEN-003 IR VS15219 ViewSonic Corporation, 2013. Macintosh Power Macintosh Microsoft Windows Windows ViewSonic 3 OnView ViewMatch ViewMeter ViewSonic ViewSonic, ViewSonic ViewSonic i ViewSonic ViewSonic

More information

[1] SBS [2] SBS Random Forests[3] Random Forests ii

[1] SBS [2] SBS Random Forests[3] Random Forests ii Random Forests 2013 3 A Graduation Thesis of College of Engineering, Chubu University Proposal of an efficient feature selection using the contribution rate of Random Forests Katsuya Shimazaki [1] SBS

More information

,,, Twitter,,, ( ), 2. [1],,, ( ),,.,, Sungho Jeon [2], Twitter 4 URL, SVM,, , , URL F., SVM,, 4 SVM, F,.,,,,, [3], 1 [2] Step Entered

,,, Twitter,,, ( ), 2. [1],,, ( ),,.,, Sungho Jeon [2], Twitter 4 URL, SVM,, , , URL F., SVM,, 4 SVM, F,.,,,,, [3], 1 [2] Step Entered DEIM Forum 2016 C5-1 182-8585 1-5-1 E-mail: saitoh-ryoh@uec.ac.jp, terada.minoru@uec.ac.jp Twitter,, Twitter,,, Bag of Words, Latent Semantic Indexing,.,,,, Twitter,, Twitter,, 1. SNS, SNS Twitter 1,,,

More information

InterSafe Personal_v2.3 ユーザーズガイド_初版

InterSafe Personal_v2.3 ユーザーズガイド_初版 InterSafe Personal v2.3 1. 3 1-1. 4 1-2. 5 InterSafe Personal 5 1-3. InterSafe Personal 6 6 7 8 2. 9 2-1. 10 2-2. 14 2-3. 17 17 17 2 18 19 21 3. 22 3-1. 23 23 3-2. [ ] 24 [ ] 24 [ ] 24 3-3. [ ] 25 [ ]

More information

untitled

untitled PC 2010 12 PC A PC BDay 1 B PC B * B* B Easy * B B B B B C C PC CD/DVD C PC PC PC PC PC () ( ) -1- *) -2- PC PC PC PC PC 0120-97-1048 043-298-8780 PC PC PC PC PC PDA PC PC 0120-97-1048 043-298-8780 PC

More information

Twitter 2016 3 201413127

Twitter 2016 3 201413127 Twitter Twitter Twitter Twitter 2 2 Twitter Twitter Twitter SVM(Support Vector Machine) Distant Supervision 2 1000 F. Twitter 2016 3 201413127 1 1 1.1....................................... 1 1.2.......................................

More information

N N 1,, N 2 N N N N N 1,, N 2 N N N N N 1,, N 2 N N N 8 1 6 3 5 7 4 9 2 1 12 13 8 15 6 3 10 4 9 16 5 14 7 2 11 7 11 23 5 19 3 20 9 12 21 14 22 1 18 10 16 8 15 24 2 25 4 17 6 13 8 1 6 3 5 7 4 9 2 1 12 13

More information

Microsoft SharePoint Server 2010SharePoint Server 2010Web SharePointSharePoint Server 2010 SharePoint SharePoint Server 2010 SharePoint SharePoint Sha

Microsoft SharePoint Server 2010SharePoint Server 2010Web SharePointSharePoint Server 2010 SharePoint SharePoint Server 2010 SharePoint SharePoint Sha この電子書籍に関する Web サイトによる情報提供について この電子書籍に関するご質問方法や訂正情報は 最終ページに記載した Web ページをご参照いただくようお願いいたします 本文 はじめに などに記載している Web ページやFAX 番号は古い情報ですので ご使用にならないようお願いいたします Microsoft SharePoint Server 2010SharePoint Server 2010Web

More information

1 1.1 PC PC PC PC PC workstation PC hardsoft PC PC CPU 1 Gustavb, Wikimedia Commons.

1 1.1 PC PC PC PC PC workstation PC hardsoft PC PC CPU 1 Gustavb, Wikimedia Commons. 1 PC PC 1 PC PC 1 PC PC PC PC 1 1 1 1.1 PC PC PC PC PC workstation PC 1.1.1 hardsoft 1.1.2 PC PC 1.1 1 1. 2. 3. CPU 1 Gustavb, Wikimedia Commons.http://en.wikipedia.org/wiki/Image:Personal_computer,_exploded_5.svg

More information

13 Excel VBA PowerPoint, Word Excel Excel Excel Excel VBA VBA VBA Visual Basic for Application Microsoft Office Visual Basic Visual Basic VBA Excel Ac

13 Excel VBA PowerPoint, Word Excel Excel Excel Excel VBA VBA VBA Visual Basic for Application Microsoft Office Visual Basic Visual Basic VBA Excel Ac \n Title Excel 実 技 試 験 の 採 点 プログラムの 実 施 について Author(s) 五 月 女, 仁 子 ; Soutome, Hiroko Citation 商 経 論 叢, 46(3): 13-24 Date 2011-02-28 Type Departmental Bulletin Paper Rights publisher KANAGAWA University

More information

EPSON EasyMP Multi PC Projection Ver.1.10 Operation Guide

EPSON EasyMP Multi PC Projection Ver.1.10 Operation Guide EasyMP Multi PC Projection EasyMP Multi PC Projection EasyMP Multi PC Projection... 5...5...5... 6...6...6... 9... 14... 14... 14... 15 EasyMP Multi PC Projection...15...16...17... 17... 18...18...19...20...

More information

Adobe Experience Manager Document Security 11.0 Extension for Microsoft Office ヘルプ

Adobe Experience Manager Document Security 11.0 Extension for Microsoft Office ヘルプ ADOBE EXPERIENCE MANAGER DOCUMENT SECURITY EXTENSION FOR MICROSOFT OFFICE http://help.adobe.com/ja_jp/legalnotices/index.html 2014/5/15 iii 1 Document Security Extension for Microsoft Office Document Security

More information

写真集計くん+ for Mac ユーザーズガイド

写真集計くん+ for Mac ユーザーズガイド DPOF + Plus for Mac + for Mac 1 + for Mac 1 + for Mac 2 3 3 5 5 5 FTP 5 7 7 7 8 11 11 13 16 18 DPOF 23 23 FTP 24 25 26 26 26 26 + for Mac + for Mac + for Mac + for Mac ( ) DPE (DPOF) Microsoft Excel Visual

More information

aca-mk23.dvi

aca-mk23.dvi E-Mail: matsu@nanzan-u.ac.jp [13] [13] 2 ( ) n-gram 1 100 ( ) (Google ) [13] (Breiman[3] ) [13] (Friedman[5, 6]) 2 2.1 [13] 10 20 200 11 10 110 6 10 60 [13] 1: (1892-1927) (1888-1948) (1867-1916) (1862-1922)

More information

「情報処理」を受講して身に付いたこと

「情報処理」を受講して身に付いたこと 14 1 40 (FD) 4 (1) (2) (3) Word, Excel, PowerPoint (4) 1 Power Point ph p Power Point Word Power Point Power Point Excel Word Excel, PowerPoint Word Excel Word Excel Excel Word Excel Power Point Power

More information

PX-403A

PX-403A NPD4403-00 ...6... 6...10 Mac OS X...11 Mac OS X v10.5.x v10.6.x...11 Mac OS X v10.4.x...15...18...19...19...21...22!ex...22 /...23 P.I.F. PRINT Image Framer...23...24...27...27...28...28...28...32 Web...32...32...35...35...35...37...37...37...39...39...40...43...46

More information

EPSON EasyMP Multi PC Projection Ver.1.11 Operation Guide

EPSON EasyMP Multi PC Projection Ver.1.11 Operation Guide EasyMP Multi PC Projection EasyMP Multi PC Projection EasyMP Multi PC Projection... 5...5...5... 6...6...6... 9... 14... 14... 14... 15 EasyMP Multi PC Projection...15...16...17... 17... 18...18...19...20...

More information

untitled

untitled Microsoft Wod/PowerPoint Dr. Dr. Dr. Microsoft Office ( Dr.WordPowerPoint) Dr. Microsoft Office Word Microsoft Office PowerPoint Dr. / Office MS-WordMS-PowerPoint Dr. Microsoft Office Word Microsoft Office

More information

PowerPoint 2007 PowerPoint 2007 PowerPoint 2007

PowerPoint 2007 PowerPoint 2007 PowerPoint 2007 PowerPoint 2007 PowerPoint 2007 PowerPoint 2007 PowerPoint 2007 PowerPoint 1 PowerPoint PowerPoint PowerPoint PowerPoint PowerPoint PowerPoint 2000 PowerPoint 2007 PowerPoint 2002OS Windows XP PowerPoint

More information

EPSON PX-503A ユーザーズガイド

EPSON PX-503A ユーザーズガイド NPD4296-00 ...6... 6...10 Mac OS X...11 Mac OS X v10.5.x v10.6.x...11 Mac OS X v10.4.x...15...18...19...19...21...22...23!ex...23 /...24 P.I.F. PRINT Image Framer...24...25...28...28...29...29...30...33

More information

EPSON EasyMP Multi PC Projection Ver.1.00 Operation Guide

EPSON EasyMP Multi PC Projection Ver.1.00 Operation Guide EasyMP Multi PC Projection EasyMP Multi PC Projection EasyMP Multi PC Projection... 5...5...5... 6...6...6... 9... 14... 14... 14... 15 EasyMP Multi PC Projection...15...16...17... 17... 18...18...19...20...

More information

今から間にあう仮想化入門とXenについて

今から間にあう仮想化入門とXenについて Xen Linux 2006 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice Agenda IA Xen. Xen 4. Xen 2 19 10 1 IA IA Server Linux Windows Linux Linux

More information

EPSON EP-803A/EP-803AW ユーザーズガイド

EPSON EP-803A/EP-803AW ユーザーズガイド NPD4293-00 ...6... 6...10 Mac OS X...11 Mac OS X v10.5.x v10.6.x...11 Mac OS X v10.4.x...15...18...19...19...22...23...24!ex...24 /...25 P.I.F. PRINT Image Framer...25...26...30...30...31...31...31...35

More information

EPSON EP-703A ユーザーズガイド

EPSON EP-703A ユーザーズガイド NPD4295-00 ...6... 6...10 Mac OS X...11 Mac OS X v10.5.x v10.6.x...11 Mac OS X v10.4.x...15...18...19...19...22...23...24!ex...24 /...25 P.I.F. PRINT Image Framer...25...26...29...30...30...31...31...34

More information

TOP MESSAGE 1

TOP MESSAGE 1 TOP MESSAGE 1 2 MISSION 3 4 HOW TO ENJOY YOUR BATH TIME 125 12 115 11 15 1 95 9 5 6 1 2 3 4 TOPICS 7 CSR WEB INFORMATION 8 WEB 8, 6, 6,35 6,369 7,4 75 5 627 45 3 36 331 198 4, 25 15 2, 25 95 15 16 9 74,57

More information

PX-673F

PX-673F NPD4385-00 ...6... 6...10 Mac OS X...11 Mac OS X v10.5.x v10.6.x...11 Mac OS X v10.4.x...15...18...19...19...21...22...23!ex...23 /...24 P.I.F. PRINT Image Framer...24...25...28...29...29...30...30...33

More information

インストールMNL_LAN.indd

インストールMNL_LAN.indd 2 1 1 2 3 4 Vista 3 2 4 1 2 3 4 3 5 5 1 2 3 4 5 6 6 3 1 Vista 2 7 3 4 3 4 3 5 Vista 5 7 6 7 8 6 9 7 8 Vista 10 1 1 2 Vista 3 4 11 2 3 1 2 12 4 13 5 1 2 3 2 14 6 1 2 3 4 5 6 15 7 1 2 3 4 2 5 5 6 1 16 8

More information

IT活用事例解説書

IT活用事例解説書 14 15 17 Information Technology ( ) 15 16 2 25 14 readme.txt index.html katsuyou.doc.doc.doc.doc.doc.doc.doc.doc.doc IT Access97 Access2000.xls.mdb.exe.mdb.exe IT.pdf 110 1114 1518 1922 2326 3952 2730

More information

パーソナルコンピュータに関するヘドニック回帰式(再推計結果)

パーソナルコンピュータに関するヘドニック回帰式(再推計結果) 2007 9 1 1. 2 2 8 2 2007 8 2. 121011 AV 1 6 BOX 2001 01-24 2007 1 2 1 3 n.a. 2 KB HDD GB CPU Core 2 Duo 2 4MB LAN 1000 BASE LAN LAN TV TV OS Windows XP Professional / Media Center Edition Windows XP Professional

More information

H1-4

H1-4 AcerWindows Vista Home Premium 00. G0 M0 M X00 M0 L00 L00 0-00--F http://www.acer.co.jp/ 00 Acer Inc. All rights reserved. Acer, the Acer logo, and are registered trademarks of Acer Inc. Other trademarks,

More information

main.dvi

main.dvi DEIM Forum 2018 J7-3 305-8573 1-1-1 305-8573 1-1-1 305-8573 1-1-1 () 151-0053 1-3-15 6F URL SVM Identifying Know-How Sites basedonatopicmodelandclassifierlearning Jiaqi LI,ChenZHAO, Youchao LIN, Ding YI,ShutoKAWABATA,

More information

12研究資料02.indd

12研究資料02.indd 3 2 Journal of Multimedia Aided Education Research 2007, Vol. 3, No. 2, 8594 e 2002 1 e 2002 e e e e e e VOD e e e e SCORM VODVideo On Demand e 20042002 2004 GP e e e e 1 23 Learning Management System4

More information

Support Vector Machine (SVM) 4 SVM SVM 2 80% 100% SVM SVM SVM 4 SVM 2 2 SVM 4

Support Vector Machine (SVM) 4 SVM SVM 2 80% 100% SVM SVM SVM 4 SVM 2 2 SVM 4 Analysis of Groove Feelings of Drums Plays 47 56340 19 1 31 Support Vector Machine (SVM) 4 SVM SVM 2 80% 100% SVM SVM SVM 4 SVM 2 2 SVM 4 1 1 1.1........................................ 1 1.1.1.............................

More information

untitled

untitled ISSN - ..................... 7............... Web........................ SVM... 7..... 7..........................7...................... Web........... ....... 7 7..... 7 7..... 7 7..... 7 7..............

More information

IS1-09 第 回画像センシングシンポジウム, 横浜,14 年 6 月 2 Hough Forest Hough Forest[6] Random Forest( [5]) Random Forest Hough Forest Hough Forest 2.1 Hough Forest 1 2.2

IS1-09 第 回画像センシングシンポジウム, 横浜,14 年 6 月 2 Hough Forest Hough Forest[6] Random Forest( [5]) Random Forest Hough Forest Hough Forest 2.1 Hough Forest 1 2.2 IS1-09 第 回画像センシングシンポジウム, 横浜,14 年 6 月 MI-Hough Forest () E-mail: ym@vision.cs.chubu.ac.jphf@cs.chubu.ac.jp Abstract Hough Forest Random Forest MI-Hough Forest Multiple Instance Learning Bag Hough Forest

More information

EPSON ES-D200 パソコンでのスキャンガイド

EPSON ES-D200 パソコンでのスキャンガイド NPD4271-00 ...4...7 EPSON Scan... 7...11 PDF...12 / EPSON Scan...13 EPSON Scan...13 EPSON Scan...14 EPSON Scan...14 EPSON Scan...15 Epson Event Manager...16 Epson Event Manager...16 Epson Event Manager...16

More information