Updated README
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@ -7,10 +7,9 @@ output: github_document
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```{r, include = FALSE}
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```{r, include = FALSE}
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knitr::opts_chunk$set(
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knitr::opts_chunk$set(
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collapse = TRUE,
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collapse = TRUE,
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comment = "#>",
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fig.path = "man/figures/README-"
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fig.path = "man/figures/README-",
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out.width = "100%"
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)
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)
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devtools::load_all()
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```
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```
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# R package mtt
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# R package mtt
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@ -512,7 +511,6 @@ the same topic were opened from the same item. See example below for item
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"001".
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"001".
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```{r topics, echo = FALSE}
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```{r topics, echo = FALSE}
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devtools::load_all()
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items <- sprintf("%03d", unique(datlogs$item))
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items <- sprintf("%03d", unique(datlogs$item))
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topics <- extract_topics(items, xmlfiles = paste0(items, ".xml"),
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topics <- extract_topics(items, xmlfiles = paste0(items, ".xml"),
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xmlpath = "../../MDS/2023ss/60100_master_thesis/analysis/data/haum/ContentEyevisit/eyevisit_cards_light/")
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xmlpath = "../../MDS/2023ss/60100_master_thesis/analysis/data/haum/ContentEyevisit/eyevisit_cards_light/")
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175
README.md
175
README.md
@ -273,7 +273,7 @@ be added. If the event spans more than two log files, a multiple of
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$600,000$ must be taken, e.g. for three log files it must be:
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$600,000$ must be taken, e.g. for three log files it must be:
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$2 \times 600,000 - timeMs.start + timeMs.stop$ and so on.
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$2 \times 600,000 - timeMs.start + timeMs.stop$ and so on.
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<img src="man/figures/README-timems-1.png" width="100%" />
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![](man/figures/README-timems-1.png)<!-- -->
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The boxplot shows that we have a continuous range of values within one
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The boxplot shows that we have a continuous range of values within one
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log file but that `timeMs` does not increase over log files. I kept
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log file but that `timeMs` does not increase over log files. I kept
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@ -371,13 +371,13 @@ plot(y.stop ~ x.stop, datlogs)
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abline(v = c(0, 3840), h = c(0, 2160), col = "blue", lwd = 2)
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abline(v = c(0, 3840), h = c(0, 2160), col = "blue", lwd = 2)
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```
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```
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<img src="man/figures/README-xycoord-1.png" width="100%" />
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![](man/figures/README-xycoord-1.png)<!-- -->
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``` r
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``` r
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aggregate(cbind(x.start, x.stop, y.start, y.stop) ~ 1, datlogs, mean)
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aggregate(cbind(x.start, x.stop, y.start, y.stop) ~ 1, datlogs, mean)
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#> x.start x.stop y.start y.stop
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## x.start x.stop y.start y.stop
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#> 1 1978.202 1975.876 1137.481 1133.494
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## 1 1978.202 1975.876 1137.481 1133.494
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```
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```
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## Pop-ups from glossar cannot be assigned to a specific item
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## Pop-ups from glossar cannot be assigned to a specific item
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@ -504,14 +504,13 @@ if the same topic card was opened several times or if different topic
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cards with the same topic were opened from the same item. See example
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cards with the same topic were opened from the same item. See example
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below for item “001”.
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below for item “001”.
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#> ℹ Loading mtt
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## item file_name topic
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#> item file_name topic
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## 1 001 001_dargestellte.xml thema
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#> 1 001 001_dargestellte.xml thema
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## 2 001 001_thema1.xml thema
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#> 2 001 001_thema1.xml thema
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## 3 001 001_leben.xml leben des kunstwerks
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#> 3 001 001_leben.xml leben des kunstwerks
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## 4 001 001_leben3.xml leben des kunstwerks
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#> 4 001 001_leben3.xml leben des kunstwerks
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## 5 001 001_thema2.xml thema
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#> 5 001 001_thema2.xml thema
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## 6 001 001_thema.xml thema
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#> 6 001 001_thema.xml thema
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## New artworks “504” and “505” starting October 2022
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## New artworks “504” and “505” starting October 2022
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@ -521,8 +520,8 @@ artworks appear on October 21, 2022.
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``` r
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``` r
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summary(as.Date(datraw[datraw$item %in% c("504", "505"), "date"]))
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summary(as.Date(datraw[datraw$item %in% c("504", "505"), "date"]))
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#> Min. 1st Qu. Median Mean 3rd Qu. Max.
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## Min. 1st Qu. Median Mean 3rd Qu. Max.
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#> "2022-10-21" "2023-01-11" "2023-03-08" "2023-03-09" "2023-05-21" "2023-07-05"
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## "2022-10-21" "2023-01-11" "2023-03-08" "2023-03-09" "2023-05-21" "2023-07-05"
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```
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```
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The artworks seem to be have updated in general after October 21, 2022.
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The artworks seem to be have updated in general after October 21, 2022.
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@ -530,80 +529,80 @@ The following table shows which items were presented in which years.
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``` r
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``` r
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xtabs(~ item + lubridate::year(date.start), datlogs)
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xtabs(~ item + lubridate::year(date.start), datlogs)
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#> lubridate::year(date.start)
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## lubridate::year(date.start)
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#> item 2016 2017 2018 2019 2020 2022 2023
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## item 2016 2017 2018 2019 2020 2022 2023
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#> 1 277 4082 1912 1434 424 394 1315
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## 1 277 4082 1912 1434 424 394 1315
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#> 3 485 6730 3126 2356 528 457 1124
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## 3 485 6730 3126 2356 528 457 1124
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#> 19 714 8656 4028 2743 660 698 1595
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## 19 714 8656 4028 2743 660 698 1595
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#> 20 595 8461 3996 2983 938 657 1355
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## 20 595 8461 3996 2983 938 657 1355
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#> 24 497 6638 2912 2251 649 439 1028
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## 24 497 6638 2912 2251 649 439 1028
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#> 27 567 5959 3112 2318 651 711 1324
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## 27 567 5959 3112 2318 651 711 1324
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#> 28 601 9329 4394 3056 778 762 1570
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## 28 601 9329 4394 3056 778 762 1570
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#> 29 425 6865 3830 2365 516 615 1174
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## 29 425 6865 3830 2365 516 615 1174
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#> 31 289 4118 2051 1218 291 296 675
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## 31 289 4118 2051 1218 291 296 675
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#> 32 562 7016 3477 2253 726 766 1647
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## 32 562 7016 3477 2253 726 766 1647
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#> 33 509 4936 2242 1449 555 358 666
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## 33 509 4936 2242 1449 555 358 666
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#> 36 434 4505 2276 1668 373 387 976
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## 36 434 4505 2276 1668 373 387 976
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#> 37 242 4478 2182 1554 339 423 1168
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## 37 242 4478 2182 1554 339 423 1168
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#> 38 480 4617 2144 1397 371 381 784
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## 38 480 4617 2144 1397 371 381 784
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#> 39 395 3227 1313 1003 237 161 622
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## 39 395 3227 1313 1003 237 161 622
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#> 41 282 3329 1303 1022 225 209 701
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## 41 282 3329 1303 1022 225 209 701
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#> 42 203 3113 1307 903 242 191 421
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## 42 203 3113 1307 903 242 191 421
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#> 43 115 2420 1089 806 176 219 486
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## 43 115 2420 1089 806 176 219 486
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#> 45 1491 13561 5924 4474 966 585 1828
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## 45 1491 13561 5924 4474 966 585 1828
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#> 46 903 9181 5340 3812 961 944 1648
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## 46 903 9181 5340 3812 961 944 1648
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#> 47 306 4949 2395 1510 750 297 675
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## 47 306 4949 2395 1510 750 297 675
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#> 48 723 10455 5384 4162 1328 948 2031
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## 48 723 10455 5384 4162 1328 948 2031
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#> 49 433 4326 2124 1414 434 431 809
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## 49 433 4326 2124 1414 434 431 809
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#> 51 564 7837 4577 2991 884 659 1370
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## 51 564 7837 4577 2991 884 659 1370
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#> 52 447 5021 2104 1729 471 349 840
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## 52 447 5021 2104 1729 471 349 840
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#> 54 424 5068 2816 2008 529 370 918
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## 54 424 5068 2816 2008 529 370 918
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#> 55 358 4859 2069 1428 341 403 1303
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## 55 358 4859 2069 1428 341 403 1303
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#> 57 860 14264 6625 5092 1410 1221 2714
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## 57 860 14264 6625 5092 1410 1221 2714
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#> 60 555 6865 3539 2336 639 586 1415
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## 60 555 6865 3539 2336 639 586 1415
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#> 62 547 6736 3803 2210 795 633 1322
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## 62 547 6736 3803 2210 795 633 1322
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#> 63 251 3677 1827 1241 300 282 527
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## 63 251 3677 1827 1241 300 282 527
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#> 66 552 6004 2774 1977 505 373 932
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## 66 552 6004 2774 1977 505 373 932
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#> 69 394 3730 1827 1438 272 206 680
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## 69 394 3730 1827 1438 272 206 680
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#> 70 226 3766 1843 973 293 268 703
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## 70 226 3766 1843 973 293 268 703
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#> 71 557 6160 2490 1846 570 323 839
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## 71 557 6160 2490 1846 570 323 839
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#> 72 426 6194 2857 2129 508 635 1553
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## 72 426 6194 2857 2129 508 635 1553
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#> 73 432 6125 2880 1821 583 395 939
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## 73 432 6125 2880 1821 583 395 939
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#> 75 258 5885 2418 1562 369 257 645
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## 75 258 5885 2418 1562 369 257 645
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#> 76 861 12435 6253 4214 1753 1153 2268
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## 76 861 12435 6253 4214 1753 1153 2268
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#> 77 816 8595 4197 2897 699 674 1452
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## 77 816 8595 4197 2897 699 674 1452
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#> 78 410 5632 2498 1924 394 408 850
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## 78 410 5632 2498 1924 394 408 850
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#> 80 1650 25687 12429 7782 1975 1712 4433
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## 80 1650 25687 12429 7782 1975 1712 4433
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#> 83 644 8618 4720 3026 987 1027 2294
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## 83 644 8618 4720 3026 987 1027 2294
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#> 84 184 2121 1231 759 231 254 465
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## 84 184 2121 1231 759 231 254 465
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#> 87 149 1618 722 632 99 0 0
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## 87 149 1618 722 632 99 0 0
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#> 88 513 6996 3493 2272 539 533 1420
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## 88 513 6996 3493 2272 539 533 1420
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#> 89 214 2204 950 723 156 0 0
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## 89 214 2204 950 723 156 0 0
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#> 90 281 3756 1372 1143 403 320 932
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## 90 281 3756 1372 1143 403 320 932
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#> 93 613 8528 4224 3015 696 1174 2058
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## 93 613 8528 4224 3015 696 1174 2058
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#> 98 462 6662 3265 2565 704 670 1453
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## 98 462 6662 3265 2565 704 670 1453
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#> 99 180 4162 1653 1454 363 411 868
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## 99 180 4162 1653 1454 363 411 868
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#> 101 414 4209 1859 1282 392 411 981
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## 101 414 4209 1859 1282 392 411 981
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#> 103 677 8758 4366 3165 1045 909 1871
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## 103 677 8758 4366 3165 1045 909 1871
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#> 104 423 5256 2381 1865 463 467 933
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## 104 423 5256 2381 1865 463 467 933
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#> 107 181 2101 1106 788 205 146 339
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## 107 181 2101 1106 788 205 146 339
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#> 109 321 4001 1619 1106 292 188 453
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## 109 321 4001 1619 1106 292 188 453
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#> 110 489 5846 2785 2008 494 387 923
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## 110 489 5846 2785 2008 494 387 923
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#> 125 640 8435 4519 3334 926 0 0
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## 125 640 8435 4519 3334 926 0 0
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#> 129 598 11322 5046 3369 910 1131 1682
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## 129 598 11322 5046 3369 910 1131 1682
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#> 145 419 7821 3945 2694 706 740 1396
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## 145 419 7821 3945 2694 706 740 1396
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#> 176 507 8465 3968 2787 687 552 1544
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## 176 507 8465 3968 2787 687 552 1544
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#> 180 516 7563 3720 2765 585 550 1272
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## 180 516 7563 3720 2765 585 550 1272
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#> 183 377 4014 1819 1741 346 251 675
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## 183 377 4014 1819 1741 346 251 675
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#> 187 340 4222 2165 1753 319 312 734
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## 187 340 4222 2165 1753 319 312 734
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#> 197 426 7710 3603 2510 671 602 1217
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## 197 426 7710 3603 2510 671 602 1217
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#> 229 303 4872 2360 1891 482 389 1005
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## 229 303 4872 2360 1891 482 389 1005
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#> 231 271 3606 1851 1239 318 236 467
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## 231 271 3606 1851 1239 318 236 467
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#> 501 1915 15968 7849 5060 1157 890 2989
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## 501 1915 15968 7849 5060 1157 890 2989
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#> 502 1212 14550 7111 4749 1105 883 2752
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## 502 1212 14550 7111 4749 1105 883 2752
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#> 503 1308 15218 8632 6399 1626 870 2558
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## 503 1308 15218 8632 6399 1626 870 2558
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#> 504 0 0 0 0 0 363 662
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## 504 0 0 0 0 0 363 662
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#> 505 0 0 0 0 0 426 1533
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## 505 0 0 0 0 0 426 1533
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```
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```
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It shows that the artworks haven been updated after the Corona pandemic.
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It shows that the artworks haven been updated after the Corona pandemic.
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