diff --git a/lv/ongoing_notes/example_logs_lag.svg b/lv/ongoing_notes/example_logs_lag.svg
new file mode 100644
index 0000000..2e56790
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+++ b/lv/ongoing_notes/example_logs_lag.svg
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+ 2024-04-23T17:01:11.149341
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diff --git a/lv/ongoing_notes/graph_init_2.svg b/lv/ongoing_notes/graph_init_2.svg
new file mode 100644
index 0000000..94a3b22
--- /dev/null
+++ b/lv/ongoing_notes/graph_init_2.svg
@@ -0,0 +1,1519 @@
+
+
+
+
+
+
+%3
+Event clustering
+170 unique codes
+
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+Cluster A
+
+
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+Cluster B
+
+
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+Cluster C
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+
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+Cluster D
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+Cluster E
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+Cluster F
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+Cluster G
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+Cluster H
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+Cluster I
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+Cluster J
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+Cluster K
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+Cluster L
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+Cluster M
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+Cluster N
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+
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+Cluster O
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+Cluster P
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+
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+Cluster Q
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+
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+Cluster R
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+
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+Cluster S
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+
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+Cluster T
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+Cluster U
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+Cluster V
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+Cluster W
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+
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+Cluster X
+
+
+cluster_Y
+Cluster Y
+
+
+cluster_Z
+Cluster Z
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+
+
+0
+sihost.exe
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+
+
+4
+Explorer.EXE
+
+
+
+0->4
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+
+
+1
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+
+
+
+2
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+
+
+
+3
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+
+
+
+39
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+
+
+
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+
+
+
+5
+DllHost.exe
+
+
+
+6
+SearchProtocolHost.exe
+
+
+
+149
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+
+
+
+6->149
+
+
+
+9
+RuntimeBroker.exe
+
+
+
+10
+BackgroundTaskHost.exe
+
+
+
+129
+EXCEL.EXE
+
+
+
+10->129
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+
+
+8
+StartMenuExperienceHost.exe
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+
+
+154
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+
+
+
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+
+
+7
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+
+
+11
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+
+
+12
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+
+
+16
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+
+
+
+179
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+
+
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+15
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+
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+151
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+
+
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+
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+162
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+
+
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+
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+
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+18
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+
+
+20
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+
+
+21
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+
+
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+
+
+22
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+
+
+23
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+
+
+31
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+
+
+
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+
+
+24
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+
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+ShellExperienceHost.exe
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+
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+150
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+
+
+
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+
+
+44
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+
+
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+
+
+29
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+
+
+
+30
+getridof.exe
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+
+
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+
+
+
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+
+
+32
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+
+
+33
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+
+
+
+34
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+
+
+35
+msedge.exe
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+
+
+36
+rundll32.exe
+
+
+
+37
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+
+
+
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+
+
+38
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+43
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+
+
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+40
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+46
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+
+
+96
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+
+
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+
+
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+
+
+
+75
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+
+
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+
+
+
+60
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+
+
+
+78
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+
+
+
+97
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+
+
+80
+OpenWith.exe
+
+
+
+124
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+
+
+
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+
+
+81
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+
+
+
+83
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+
+
+
+84
+cpp.exe
+
+
+
+98
+DevCpp.exe
+
+
+
+87
+DllHost.exe
+
+
+
+88
+g++.exe
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+
+
+90
+collect2.exe
+
+
+
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+
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+99
+as.exe
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+
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+91
+ld.exe
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+
+
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+
+
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+
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+100
+Assgt4Q2.exe
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+
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+68
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+
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+58
+AdskIdentityManager.exe
+
+
+
+134
+AdpSDKUtil.exe
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+
+
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+
+
+59
+AdSSO.exe
+
+
+
+131
+AdpSDKUtil.exe
+
+
+
+59->131
+
+
+
+93
+ADPClientService.exe
+
+
+
+133
+ADPClientService.exe
+
+
+
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+
+
+
+54
+AdskUpdateCheck.exe
+
+
+
+55
+ADPClientService.exe
+
+
+
+101
+ADPClientService.exe
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+
+
+102
+AdpSDKUtil.exe
+
+
+
+76
+MoNotificationUx.exe
+
+
+
+103
+Assgt4Q3.exe
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+
+
+105
+soffice.bin
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+
+
+104
+soffice.exe
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+
+
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+
+
+
+104->105
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+
+
+82
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+
+
+51
+lync.exe
+
+
+
+135
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+
+
+51->135
+
+
+
+63
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+
+
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+
+
+
+79
+Reader_sl.exe
+
+
+
+45
+sdxhelper.exe
+
+
+
+152
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+
+
+
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+
+
+
+61
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+
+
+
+85
+cleanmgr.exe
+
+
+
+86
+sdiagnhost.exe
+
+
+
+92
+Question3Lab4.exe
+
+
+
+94
+ADPClientService.exe
+
+
+
+95
+AdpSDKUtil.exe
+
+
+
+53
+ApplicationFrameHost.exe
+
+
+
+52
+SystemSettings.exe
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+
+
+53->52
+
+
+
+52->53
+
+
+
+124->80
+
+
+
+117
+ADPClientService.exe
+
+
+
+118
+AdpSDKUtil.exe
+
+
+
+110
+rundll32.exe
+
+
+
+48
+NGenTask.exe
+
+
+
+125
+Microsoft.SharePoint.exe
+
+
+
+119
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+
+
+
+120
+setup.exe
+
+
+
+119->120
+
+
+
+120->119
+
+
+
+121
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+
+
+
+122
+chrmstp.exe
+
+
+
+123
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+
+
+
+111
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+
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+114
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+
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+115
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+116
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+
+
+106
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+
+
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+107
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+
+
+
+108
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+
+
+109
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+
+
+
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+
+
+127
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+
+
+128
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+
+
+
+71
+DownloadManager.exe
+
+
+
+72
+ADPClientService.exe
+
+
+
+134->58
+
+
+
+73
+AdskAccessCore.exe
+
+
+
+160
+SecurityHealthSystray.exe
+
+
+
+73->160
+
+
+
+74
+AdskAccessUIHost.exe
+
+
+
+126
+Microsoft.SharePoint.exe
+
+
+
+50
+MATLAB.exe
+
+
+
+42
+MATLABWebUI.exe
+
+
+
+129->10
+
+
+
+130
+ADPClientService.exe
+
+
+
+131->59
+
+
+
+49
+mwdocsearch.exe
+
+
+
+132
+Microsoft.AAD.BrokerPlugin.exe
+
+
+
+140
+chrmstp.exe
+
+
+
+141
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+
+
+
+142
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+
+
+
+143
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+
+
+
+135->51
+
+
+
+136
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+
+
+
+137
+AdpSDKUtil.exe
+
+
+
+138
+Question3-ASCII.exe
+
+
+
+66
+WerFault.exe
+
+
+
+139
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+
+
+149->6
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+151->15
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+
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+150->25
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+
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+153
+MoNotificationUx.exe
+
+
+
+152->153
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+
+
+153->45
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+
+
+154->8
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+
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+64
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+
+
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+148
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+
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+147
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+
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+155
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+
+
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+144
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+
+
+145
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+
+
+
+146
+RdrServicesUpdater.exe
+
+
+
+156
+setup.exe
+
+
+
+157
+Widgets.exe
+
+
+
+158
+msteamsupdate.exe
+
+
+
+159
+msedgewebview2.exe
+
+
+
+160->73
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+
+
+161
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+
+
+164
+SentinelUI.exe
+
+
+
+162->164
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+
+
+163
+AdpSDKUtil.exe
+
+
+
+166
+ActivationNotifier.exe
+
+
+
+164->166
+
+
+
+165
+runonce.exe
+
+
+
+170
+Update.exe
+
+
+
+165->170
+
+
+
+166->14
+
+
+
+167
+Teams.exe
+
+
+
+168
+Update.exe
+
+
+
+167->168
+
+
+
+168->167
+
+
+
+169
+Squirrel.exe
+
+
+
+170->165
+
+
+
+171
+Teams.exe
+
+
+
+172
+GenuineService.exe
+
+
+
+173
+CheckActivationServers.exe
+
+
+
+174
+HxTsr.exe
+
+
+
+175
+maplew.exe
+
+
+
+176
+maplelauncher.exe
+
+
+
+175->176
+
+
+
+177
+javaw.exe
+
+
+
+176->177
+
+
+
+177->175
+
+
+
+178
+mserver.exe
+
+
+
+179->16
+
+
+
diff --git a/lv/ongoing_notes/lag.svg b/lv/ongoing_notes/lag.svg
new file mode 100644
index 0000000..b5d8302
--- /dev/null
+++ b/lv/ongoing_notes/lag.svg
@@ -0,0 +1,10070 @@
+
+
+
+
+
+
+ 2024-04-23T17:25:24.797364
+ image/svg+xml
+
+
+ Matplotlib v3.5.3, https://matplotlib.org/
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diff --git a/lv/ongoing_notes/notes.typ b/lv/ongoing_notes/notes.typ
new file mode 100644
index 0000000..10421f3
--- /dev/null
+++ b/lv/ongoing_notes/notes.typ
@@ -0,0 +1,66 @@
+/*#set text(font: "Essays1743")*/
+
+= Redundancy Check
+
+To cut through the noise in the logs, I am bringing back from retirement the log verification algorithm.
+This algorithm applies hierarchical clustering to the logs using a custom distance metric.
+The main thing to remember is that the only parameter is the ~distance threshold~ that is expressed as a number of second.
+This threshold represents the maximum average time two logs can be apart to be considered redundant.
+A value around 1s should be a pretty good value for this type of data.
+
+Quick stats.: as of April 16, the machine b-06 generated 9002 log entries across 170 unique logs.
+This number is missleading because the uniqueness of the logs is determined based on the path of the application that starts or stops.
+However, this path changes for two may reason:
+
+- When the user changes, the same application start from a different user directory. It is not clear if the same application runing from two different user directory should be considered different applications or not.
+- Sometimes, an application will have a change in capitalization in its name. For example, `C:\\[...]\BackgroundTaskHost.exe` exists also as `C:\\[...]\backgroundTaskHost.exe` or even simply `backgroundTaskHost.exe` without absolute path. This makes it difficult to combine back together the different version of the same app.
+
+#figure(caption: "Initial redundancy graph with threshold 2s",
+image("graph_init_2.svg", width:100%)
+)
+
+The initial exploration does not try to clean the logs.
+The log selection algo runs with a distance threshold of 2 seconds and produces the result in #label("graph_init").
+There are some good results in this graph.
+Mostly, most clusters seems to make sense. For example cluster Z groups together maple-related apps, cluster L groups chrome-related apps, and cluster Q groups things I don't know about but have similar names.
+However, we can identify a number of issues and mainly:
+
+- Some apps name appear twice or more. This is likely due to inconsistencies in the path or user sessions.
+- The clusters do not take into accound the type of log --- starting or stoping the app.
+
+The initial idea would be to clean to logs to get a better or more clustering.
+However I have made this mistake too many time so I first need to assess if the clustering is good or not.
+No need to leak info into the data if the clustering is good.
+If it is not, I need a quantitative way of evaluating if I make it better or not.
+How do you evaluate if a clustering is good? No idea.
+Lets start by visualizing what these clusters look like in a time series.
+
+
+= Lag
+If only this was lab data, we would make sure the timings a synced up before the experiment.
+However, this is the real world and in the real world the university does not consult me when setting up their log collection system.
+As a result, the logs seems to lag behind the power traces (or the other way around, but let's say its them).
+Given that we are considering patterns of logs in the order of < 1s, any lag of more than one second is game breaking.
+Visually, we can estimate that the lag is around 1h (so game is so broken there is no game anymore).
+We can also hypothesized that, for each machine, the lag is constant in time (but may not be constant accross machines).
+
+#figure(caption: "Example of log vs power lag",
+image("example_logs_lag.svg", width:100%)
+)
+
+To estimate a constant lag, the cross-correlation is an obvious choice.
+The cross correlation presents the corelation of two signals for all possible values of lag between them.
+With the strong assumption that the density of logs should be exactly correlated with the power consumption, we can compute the correlation between the log series and the time series.
+
+#align(center)[~Hold up a minute, the log series is not a time series, so it cannot be compared with the power consumption data trivially.~]
+That is true. We first need to convert the log series in a time series to compute the cross-correlation.
+There are many ways to do that so I started with the simplest:
+1. Create an array of all zeros with the same shape as the power trace.
+2. Place a one at each time stamps where a log happens. Add thelm if multiple.
+3. Apply a moving average filter multiple times to smooth the data.
+4. Compute the cross correlation between the power trace and the logs.
+
+
+#figure(caption: "Lag computation using cross correlation.",
+image("lag.svg", width:100%)
+)