diff --git a/resources/tests/readability/pixnet/expected.html b/resources/tests/readability/pixnet/expected.html new file mode 100644 index 0000000..ec634cb --- /dev/null +++ b/resources/tests/readability/pixnet/expected.html @@ -0,0 +1,280 @@ +
+

+ 12-IMG_3886.jpg +

+

一波波接續性低溫寒流報到 已將新竹尖石鄉後山一帶層層山巒披上嫣紅的彩衣 +

+

玉峰道路一路上雲氣山嵐滯留山頭 順路下切蜿蜒道路後不久即抵達來到"玉峰國小" +

+

"美樹"美如其名偌大楓香樹早已呈現金黃 泛紅色彩也是愛攝人仕所喜愛造訪之地

+

第二次造訪美樹發現到營區變了 印象中以前生冷招牌換成了原木招牌可謂匠心獨運 +

+

燻黑原木加上金黃色醒目字體 加上了貓頭鷹原木創作也充分發揮了裝飾藝術功力 +

+

營區內除了露營、民宿、餐飲賞楓項目多了許多原木飾品更有畫龍點睛加乘效果 +

+ +

30-IMG_4228.jpg

+

廣受歡迎的美樹營地有個很大特色就是楓紅時期楓香樹由綠轉黃、轉紅到楓紅層層 +

+

一來到"美樹"馬上眼睛為之一亮 也會深深地為那多種顏色多層次渲染之下楓紅而迷惑 +

+

不同格調就是從入口處這塊招牌第一眼開始 + + 木頭招牌 + + + 、貓頭鷹裝飾品勾勒出美樹的風格 + +

+ + +

31-IMG_4231.jpg

+

每年12月向來是攝影班外拍的絕佳場所之一 楓紅期間入園費$50元

+

園區給愛攝一族淨空場景而不是散搭帳蓬之下反而影響拍照畫面與構圖取景

+

露營的話則須待中午過後再進場搭帳的彈性做法個人也相當支持這樣的權宜之計

+ + +

+ P1610088.jpg +

+

來到現場已是落葉飄飄堆疊滿地 不時隨著風吹雨襲而葉落垂地

+ + +

+ P1610069.jpg +

+

不忍踩過剛剛掉落的樹葉 沿著前人足跡踏痕輕踩而行

+

雖然只是一廂情願的想法 終究還是不可避免地將會化為塵土

+ + +

02-P1610080.jpg

+

葉落繽紛顯得幾分蕭瑟氣息 空氣中可以嗅得出來依然瀰漫著濕寒水氣 +

+

偶而還會飄下來一些霧氣水滴 不時張望尋找最佳楓葉主題

+ + +

04-P1610087.jpg

+

外拍的攝影班學員一堆早已不時穿梭其間

+

各自努力地找尋自認為最好的拍攝角度

+ + +

05-P1610099.jpg

+ + +

P1610095.jpg

+ + +

13-IMG_3891.jpg

+ + +

15-IMG_3906.jpg

+

"水槽"上面的這幾隻彩繪版貓頭鷹也太可愛了

+

同樣的造型加上不同色彩宛如賦予不同的生命力一般 cool!

+ + +

16-IMG_3916.jpg

+

雨水洗塵後的枝頭固然掉落些葉片是否也洗去塵勞憂傷

+ + +

17-IMG_3919.jpg

+ + +

06-IMG_3853.jpg

+

喜歡拍照的不論是平面掃描、天空搜尋、地上地毯式搜索

+

有如小說偵探一般 不放過蛛絲馬跡地用力尋尋覓覓找尋最美角度

+ + +

07-P1610104.jpg

+ + +

08-IMG_3862.jpg

+

原本這周是由小朱團長早在一年前就跟"簍信"預定下來的場子

+

早上從台北出門之際還是小雨不斷細雨紛飛來到此地雖雨已停

+

但多日來的雨勢不斷已有部分區域水漬成攤並不適合落置帳篷

+

這個季節正是"控溪吊橋"一帶的楓紅變葉時刻 先行走一趟秀巒賞景 + + +

+ + +

18-P1610141.jpg

+

午後從"秀巒"回到美樹之際已經全數撤退只剩下我們三車留下來

+

唯有"離開地球表面"睡車上的才可以不受到地上泥濘而影響

+ + +

19-IMG_3933.jpg

+ + +

14-P1610134.jpg

+

午後山嵐興起雲氣遊蕩盤旋在對岸山頭 人潮來來去去似乎也沒有減少 +

+ + +

44-P1610283.jpg

+

美樹民宿有開設餐廳 室內簡單佈置提供伙食餐飲

+ + +

+ P1610212.jpg +

+

這兩間是民宿房間 跟著民宿主人"簍信"聊起來還提到日後將改變成兩層木屋

+

一樓則是咖啡飲料/賣店提供訪客來賓有個落腳席座之地 二樓才會是民宿房間

+

心中有了計畫想法才會有日後的夢想藍圖 相信將會改變得更好的民宿露營環境

+ +

+ P1610219.jpg +

+

民宿前這一大區楓香林為土質營位 大致區分前、後兩個營區

+

前面這一區約可搭上十二帳/車/廳 後面那區也大約4~5帳/車/廳

+

正前方小木屋即是衛浴區 男女分別以左右兩側分開(燒材鍋爐) +

+ + +

10-P1610114.jpg

+

營區水電方便 水槽也很有特色

+ + +

22-P1610245.jpg

+

這次選擇左側地勢高些以防午夜下雨泥濘

+ + +

20-P1610238.jpg

+

"野馬"特地帶來了冬至應景食材ㄜ---湯圓 +

+

這家還是最近被評比第一名氣的湯圓專賣店

+ + +

21-P1610241.jpg

+

向來對於湯圓是敬謝不敏 沒想到是出乎意料之外的好吃 沒話說!
+

+ + +

24-IMG_4113.jpg

+

喜歡原住民朋友的坦率、真誠 要將民宿營地經營的有聲有色並非容易之事

+

午茶時間與"簍信"閒聊分享著他的觀點理念之時很支持對於環境應有生態保護 +

+

環保維護是人人有責 勿以善小而不為不計涓滴之水才可匯集成河  + +

+ + +

32-IMG_4248.jpg

+ + +

25-IMG_4152.jpg

+

入夜前雨絲終於漸漸緩和下來 雖然氣溫很低卻沒感受到寒冷的跡象

+

是山谷中少了寒氣還是美樹營區裡的人熱情洋溢暖化了不少寒意

+ +

IMG_4158.jpg

+

聖誕前夕裝點些聖誕飾品 感受一下節慶的氛圍

+ + +

26-P1610261.jpg

+

晚餐準備了砂鍋魚頭

+ + +

46-1021221美樹露營.jpg

+

"蒯嫂"還特地準備著羊肩排、鹹豬肉、柳葉魚...哇!這哩澎湃哩...

+

 "永老爺"早已備妥了好酒為遠自台南來的蒯兄嫂敬一杯囉

+

感謝蒯嫂精心準備的好料理 食指大動好菜色感恩ㄟ!

+ + +

27-IMG_4173.jpg

+

吃得快精光之際...才想到忘了拍合照...(哇哩咧 ^&*()

+ +

28-IMG_4178.jpg

+ + +

29-IMG_4188.jpg

+

隔日睡到很晚才起床 不用拍日出晨光的營地對我來說都是個幸福的睡眠

+

哪怕是葉落飄零落滿地還是睡夢周公召見而去 起床的事~差點都忘記了

+ + +

+ IMG_4205.jpg +

+

昨天細雨紛飛依然打落了不少落葉中間這株整個都快變成枯枝了

+

昨天依稀凋零稀疏的楓葉殘留今兒個完全不復存在(上周是最美的代名詞)

+ + +

33-IMG_4255.jpg

+

上回來得太早沒能見到楓葉泛紅 這次晚了一周已陸續落葉也無從比對楓葉差異性  +

+

另一種角度看不論青楓、金黃葉紅的楓香、葉落飄零秋滿霜、落葉枯枝的蕭瑟 +

+

只要心中自認為是最美最浪漫的一刻 都是美的表徵也是最美的時分 +

+ + +

34-P1610269.jpg

+

早起的"蒯嫂"已經備好熱騰騰中式稀飯、包子、蔬果 頓時~有幸福的感覺

+ + +

35-IMG_4303.jpg

+

星期天早上趁著攝影團還沒入場先來人物場景特寫

+

野馬家兩張新"座椅"就當作是試坐囉!拍謝哩

+ + +

38-IMG_4330.jpg

+ + +

+ P1610279.jpg +

+

難得有此無人美景在楓樹下的聖誕氛圍也一定要來一張才行

+ + +

37-IMG_4323.jpg

+

三家合照(Hero也一定要入鏡的)

+ + +

40-IMG_4342.jpg

+

接著攝影團入場帶隊老師請求借個時間也來讓學員練習楓樹下的聖誕飾品

+

此時剛好也遇到早在FB社團相互回應卻頭一次謀面的Mr."大雄"真是幸會了

+ + +

42-IMG_4382.jpg

+

接近中午時分陽光漸露 藍天帷幕再次嶄露頭角 ~ 久違了!

+

期盼下的天空終於放晴 沒有缺席的藍天還是準時赴約如期出席

+ + +

41-IMG_4366.jpg

+

這兩天肉肉(Hero)天雨濕滑無法自由奔跑都快悶壞了

+

天晴後"蒯嫂"帶著散步遊園也好解解悶

+ + +

43-IMG_4383.jpg

+

收拾好裝備準備離開營地 亮麗的天空鮮明對比下的楓樹林又讓人覺得有點捨不得離開

+

道別了"美樹營地"準備前往而行"石磊國小"一個很生疏的小學座落在這深山部落裡 +

+

北橫"石磊部落" 一個從未踏入的陌生之地因為露營之故否則畢生大概也不會路過

+

三位大叔同行準備走著這段遙遠的路段 下次找機會再來重溫舊夢了.......

+ +

美樹營地 + + 資訊 +

+

聯絡電話:03-584-7231  行動: 0937-141993
林錦武 (泰雅族名: 摟信)
營地地址:新竹縣尖石鄉玉峰村6鄰20號 + +
+
+

+

每帳$600 兩間衛浴使用燒材鍋爐/ 兩間全天瓦斯 廁所蹲式X 3 +

+

楓紅期間須過中午才可搭帳 水電便利

+

GPS: N24 39 16.4 E121 18 19.5

+ + +

如果您喜歡"史蒂文的家"圖文分享 邀請您到 FB 粉絲團 + 按個"讚"! +

+

內文有不定期的更新旅遊、露營圖文訊息 謝謝! + +

+ + + + + +
diff --git a/resources/tests/readability/pixnet/source.html b/resources/tests/readability/pixnet/source.html new file mode 100644 index 0000000..e1849a9 --- /dev/null +++ b/resources/tests/readability/pixnet/source.html @@ -0,0 +1,4372 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 新竹尖石_美樹營地賞楓 (2) @ 史蒂文的家_藍天 :: 痞客邦 PIXNET :: + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+ + + + +
+ + + +
+ +
+ + +
+
+ +
+ +
+ +
+ +
+ +
+ +
+ +
+ +
+
+
+ + +
+
+
+
相關文章
+
+
+ + +
+ +
+ +
+
+
+ +
+

+ +
+

+ 12-IMG_3886.jpg +

+

一波波接續性低溫寒流報到 已將新竹尖石鄉後山一帶層層山巒披上嫣紅的彩衣 +

+

玉峰道路一路上雲氣山嵐滯留山頭 順路下切蜿蜒道路後不久即抵達來到"玉峰國小" +

+

"美樹"美如其名偌大楓香樹早已呈現金黃 泛紅色彩也是愛攝人仕所喜愛造訪之地

+

第二次造訪美樹發現到營區變了 印象中以前生冷招牌換成了原木招牌可謂匠心獨運 +

+

燻黑原木加上金黃色醒目字體 加上了貓頭鷹原木創作也充分發揮了裝飾藝術功力 +

+

營區內除了露營、民宿、餐飲賞楓項目多了許多原木飾品更有畫龍點睛加乘效果 +

+


+

30-IMG_4228.jpg

+

廣受歡迎的美樹營地有個很大特色就是楓紅時期楓香樹由綠轉黃、轉紅到楓紅層層 +

+

一來到"美樹"馬上眼睛為之一亮 也會深深地為那多種顏色多層次渲染之下楓紅而迷惑 +

+

不同格調就是從入口處這塊招牌第一眼開始 + + 木頭招牌 + + + 、貓頭鷹裝飾品勾勒出美樹的風格 + +

+

+

+

31-IMG_4231.jpg

+

每年12月向來是攝影班外拍的絕佳場所之一 楓紅期間入園費$50元

+

園區給愛攝一族淨空場景而不是散搭帳蓬之下反而影響拍照畫面與構圖取景

+

露營的話則須待中午過後再進場搭帳的彈性做法個人也相當支持這樣的權宜之計

+

+

+

+ P1610088.jpg +

+

來到現場已是落葉飄飄堆疊滿地 不時隨著風吹雨襲而葉落垂地

+

+

+

+ P1610069.jpg +

+

不忍踩過剛剛掉落的樹葉 沿著前人足跡踏痕輕踩而行

+

雖然只是一廂情願的想法 終究還是不可避免地將會化為塵土

+

+

+

02-P1610080.jpg

+

葉落繽紛顯得幾分蕭瑟氣息 空氣中可以嗅得出來依然瀰漫著濕寒水氣 +

+

偶而還會飄下來一些霧氣水滴 不時張望尋找最佳楓葉主題

+

+

+

04-P1610087.jpg

+

外拍的攝影班學員一堆早已不時穿梭其間

+

各自努力地找尋自認為最好的拍攝角度

+

+

+

05-P1610099.jpg

+

+

+

P1610095.jpg

+

+

+

13-IMG_3891.jpg

+

+

+

15-IMG_3906.jpg

+

"水槽"上面的這幾隻彩繪版貓頭鷹也太可愛了

+

同樣的造型加上不同色彩宛如賦予不同的生命力一般 cool!

+

+

+

16-IMG_3916.jpg

+

雨水洗塵後的枝頭固然掉落些葉片是否也洗去塵勞憂傷

+

+

+

17-IMG_3919.jpg

+

+

+

06-IMG_3853.jpg

+

喜歡拍照的不論是平面掃描、天空搜尋、地上地毯式搜索

+

有如小說偵探一般 不放過蛛絲馬跡地用力尋尋覓覓找尋最美角度

+

+

+

07-P1610104.jpg

+

+

+

08-IMG_3862.jpg

+

原本這周是由小朱團長早在一年前就跟"簍信"預定下來的場子

+

早上從台北出門之際還是小雨不斷細雨紛飛來到此地雖雨已停

+

但多日來的雨勢不斷已有部分區域水漬成攤並不適合落置帳篷

+

這個季節正是"控溪吊橋"一帶的楓紅變葉時刻 先行走一趟秀巒賞景 + + +

+

+

+

18-P1610141.jpg

+

午後從"秀巒"回到美樹之際已經全數撤退只剩下我們三車留下來

+

唯有"離開地球表面"睡車上的才可以不受到地上泥濘而影響

+

+

+

19-IMG_3933.jpg

+

+

+

14-P1610134.jpg

+

午後山嵐興起雲氣遊蕩盤旋在對岸山頭 人潮來來去去似乎也沒有減少 +

+

+

+

+

44-P1610283.jpg

+

美樹民宿有開設餐廳 室內簡單佈置提供伙食餐飲

+

+

+

+ P1610212.jpg +

+

這兩間是民宿房間 跟著民宿主人"簍信"聊起來還提到日後將改變成兩層木屋

+

一樓則是咖啡飲料/賣店提供訪客來賓有個落腳席座之地 二樓才會是民宿房間

+

心中有了計畫想法才會有日後的夢想藍圖 相信將會改變得更好的民宿露營環境

+

+

+ P1610219.jpg +

+

民宿前這一大區楓香林為土質營位 大致區分前、後兩個營區

+

前面這一區約可搭上十二帳/車/廳 後面那區也大約4~5帳/車/廳

+

正前方小木屋即是衛浴區 男女分別以左右兩側分開(燒材鍋爐) +

+

+

+

10-P1610114.jpg

+

營區水電方便 水槽也很有特色

+

+

+

22-P1610245.jpg

+

這次選擇左側地勢高些以防午夜下雨泥濘

+

+

+

20-P1610238.jpg

+

"野馬"特地帶來了冬至應景食材ㄜ---湯圓 +

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這家還是最近被評比第一名氣的湯圓專賣店

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向來對於湯圓是敬謝不敏 沒想到是出乎意料之外的好吃 沒話說!
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喜歡原住民朋友的坦率、真誠 要將民宿營地經營的有聲有色並非容易之事

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午茶時間與"簍信"閒聊分享著他的觀點理念之時很支持對於環境應有生態保護 +

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環保維護是人人有責 勿以善小而不為不計涓滴之水才可匯集成河  + +

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入夜前雨絲終於漸漸緩和下來 雖然氣溫很低卻沒感受到寒冷的跡象

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是山谷中少了寒氣還是美樹營區裡的人熱情洋溢暖化了不少寒意

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聖誕前夕裝點些聖誕飾品 感受一下節慶的氛圍

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晚餐準備了砂鍋魚頭

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"蒯嫂"還特地準備著羊肩排、鹹豬肉、柳葉魚...哇!這哩澎湃哩...

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 "永老爺"早已備妥了好酒為遠自台南來的蒯兄嫂敬一杯囉

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感謝蒯嫂精心準備的好料理 食指大動好菜色感恩ㄟ!

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吃得快精光之際...才想到忘了拍合照...(哇哩咧 ^&*()

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隔日睡到很晚才起床 不用拍日出晨光的營地對我來說都是個幸福的睡眠

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哪怕是葉落飄零落滿地還是睡夢周公召見而去 起床的事~差點都忘記了

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昨天細雨紛飛依然打落了不少落葉中間這株整個都快變成枯枝了

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昨天依稀凋零稀疏的楓葉殘留今兒個完全不復存在(上周是最美的代名詞)

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上回來得太早沒能見到楓葉泛紅 這次晚了一周已陸續落葉也無從比對楓葉差異性  +

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另一種角度看不論青楓、金黃葉紅的楓香、葉落飄零秋滿霜、落葉枯枝的蕭瑟 +

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只要心中自認為是最美最浪漫的一刻 都是美的表徵也是最美的時分 +

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早起的"蒯嫂"已經備好熱騰騰中式稀飯、包子、蔬果 頓時~有幸福的感覺

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星期天早上趁著攝影團還沒入場先來人物場景特寫

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野馬家兩張新"座椅"就當作是試坐囉!拍謝哩

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難得有此無人美景在楓樹下的聖誕氛圍也一定要來一張才行

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三家合照(Hero也一定要入鏡的)

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接著攝影團入場帶隊老師請求借個時間也來讓學員練習楓樹下的聖誕飾品

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此時剛好也遇到早在FB社團相互回應卻頭一次謀面的Mr."大雄"真是幸會了

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接近中午時分陽光漸露 藍天帷幕再次嶄露頭角 ~ 久違了!

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期盼下的天空終於放晴 沒有缺席的藍天還是準時赴約如期出席

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這兩天肉肉(Hero)天雨濕滑無法自由奔跑都快悶壞了

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天晴後"蒯嫂"帶著散步遊園也好解解悶

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收拾好裝備準備離開營地 亮麗的天空鮮明對比下的楓樹林又讓人覺得有點捨不得離開

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道別了"美樹營地"準備前往而行"石磊國小"一個很生疏的小學座落在這深山部落裡 +

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北橫"石磊部落" 一個從未踏入的陌生之地因為露營之故否則畢生大概也不會路過

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三位大叔同行準備走著這段遙遠的路段 下次找機會再來重溫舊夢了.......

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+

美樹營地 + + 資訊 +

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聯絡電話:03-584-7231  行動: 0937-141993
林錦武 (泰雅族名: 摟信)
營地地址:新竹縣尖石鄉玉峰村6鄰20號 + +
+
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每帳$600 兩間衛浴使用燒材鍋爐/ 兩間全天瓦斯 廁所蹲式X 3 +

+

楓紅期間須過中午才可搭帳 水電便利

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GPS: N24 39 16.4 E121 18 19.5

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+

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如果您喜歡"史蒂文的家"圖文分享 邀請您到 FB 粉絲團 + 按個"讚"! +

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內文有不定期的更新旅遊、露營圖文訊息 謝謝! + +

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+ 史蒂文的家_藍天 發表在 痞客邦 PIXNET 留言(42) 人氣(23925) +

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留言列表 (42)

+
發表留言
+ +
+
    + +
  • + 小鳳 +
  • +
  • +

    + 露營兼賞楓,好棒的生活
  • +
  • + 謝謝小鳳的來訪! +

    史蒂文的家_藍天 於 2014/01/01 20:31 回覆

    +
  • +
+
    + +
  • + 茜媽咪 +
  • +
  • +

    + 嚮往大自然....再濕冷的天依舊衝衝衝
    每每分享藍天大哥捕捉的鏡頭 +
    總是特別的吸引目光....真得好美 +
    對了....我家女兒說....伯伯的露營餐點 +
    看起來好豐盛喔 +
    +
  • +
  • + 茜媽咪晚安:
    您過獎了,我們不是專業攝影師只是喜歡拍照而已, +
    雨天過後的楓葉蕭瑟感變厚重了,也顯得很鮮明色澤而已! +
    這次還是南部上來的朋友帶來豐盛的晚餐,真是不好意思ㄋ! +
    (拍謝!外出帶著平板電腦不容易回應..才剛剛回家回覆) +

    史蒂文的家_藍天 於 2014/01/01 20:37 回覆

    +
  • +
+
    + +
  • + 訪客
  • +
  • +

    + 藍天哥
    +
    您的文筆真是讚 +
    +
    大雄
  • +
  • + 大雄 晚安:
    毋影啦~只是有感而發的抒發一點所見所聞而已! +

    史蒂文的家_藍天 於 2014/01/01 20:39 回覆

    +
  • +
+
    + +
  • + linghua +
  • +
  • +

    + 哇!好厚的紅毯 趴在地上取景辛苦了!
    近年天氣消笑 忽冷忽熱
    外拍能遇到最美的藍天和紅葉 可遇不可求....
    桌上的砂鍋魚頭看起來超讚 +
    冷冷的寒冬享用 一定過癮極了!
  • +
  • + 哈~我的相機可以翻轉螢幕ㄜ,當初也有考慮到這場景的辛苦...
    所以螢幕可以折疊就輕鬆多囉! +
    楓紅總是不等人的,我們這一周跟上周相比較的話就差很大, +
    選對時間才是做重要! 天寒之際吃火鍋最方便,也是偷懶... +

    史蒂文的家_藍天 於 2014/01/01 20:59 回覆

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  • +
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+ + +
+ + +
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    + +
  • + 青草 +
  • +
  • +

    + 大哥晚安~
    今天路過美樹營地,真的很美! +
    可惜現在楓已落的差不多了!! +
    好深山那內的地方,我們由秀巒下玉峰 +
    再由北橫三光回家,一路的山景秀麗!!
  • +
  • + 青草晚安:
    上週幾天下來又是風又是雨, +
    "花落知多少..."就算差一周也 +
    差很大呢!明年算準時間再訪 +
    就一定很棒的! +

    史蒂文的家_藍天 於 2014/01/01 20:56 回覆

    +
  • +
+
    + +
  • + 阿蒯 +
  • +
  • +

    + 大推
    不是因為文中的很多”蒯嫂” +
    回家之後發現我的”恐山症”竟然好了八成 +
    那段石磊產業道路 心理暗唸”阿彌陀佛”不只百遍除了感謝
    我詞窮了 +
    你們與野馬伉儷的友誼讓我們在陰雨寒冷中覺得溫暖 +
    這是一次另人感動的旅程 +
    有你們真好!
  • +
  • + 蒯兄嫂晚安:
    這趟路讓您辛苦了,雖然天氣不佳依然如期赴約, +
    讓蒯嫂處處打點得得這麼好,真有點過意不去... +
    感恩!相信"之前"的車況給受驚擾了,如今應該 +
    是恢復信心,有藍天在的話,出門都是安全無虞的! +

    史蒂文的家_藍天 於 2014/01/01 20:54 回覆

    +
  • +
+
    + +
  • + 甄妮佛 +
  • +
  • +

    + 山嵐 楓樹 落葉 ... 這地方太美了!! 太美了!!
  • +
  • + 甄妮佛 晚安:
    如果有露營的朋友一定也聽過有這個地方, +
    時令季節一到就是楓紅滿地...尖石秀巒一帶 +
    很有秋天的氣息哦.... +

    史蒂文的家_藍天 於 2014/01/01 20:48 回覆

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  • +
+
    + +
  • + Cora +
  • +
  • +

    + 雨霧飄渺中的楓黃楓紅另有一番風韻
  • +
  • + Cora晚安:
    幾天下來楓葉經過雨後洗滌變得很鮮明, +
    當然也帶走許多落葉..蕭瑟唯美另一種風情! +

    史蒂文的家_藍天 於 2014/01/01 20:46 回覆

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  • +
+
    + +
  • + tinned +
  • +
  • +

    + 真是拍的漂亮 我是北七強
  • +
  • + 北七強 晚安:
    謝謝不吝讚美,其實我們只是喜歡拍而已,畢竟跟專業攝影還是有段距離, +
    簍信能有有您這些朋友真是太幸福了...,美樹愈來愈進步您是功不可沒... +
    (哈~這個名稱取得...似乎很有玄機呢?) +

    史蒂文的家_藍天 於 2014/01/01 20:44 回覆

    +
  • +
+
    + +
  • + 莉莉夫子 +
  • +
  • +

    + 藍天大哥:晚安~
    哇~睡車上.機動性很強咧~ +
    今年的美樹 好美啊~
  • +
  • + LiLi夫子晚安:
    是呀!改裝成車中床離開"地球表面",力克 +
    潮溼地表(懶得收帳篷才是事實).. +
    今年的"美樹"楓紅狀況很優,我們去的上一周 +
    更是最大值,看到FB有朋友分享..美的驚豔! +

    史蒂文的家_藍天 於 2014/01/01 20:25 回覆

    +
  • +
+
    + +
  • + 黑傑克 +
  • +
  • +

    + 在藍天大的掌鏡下,美樹果然是仙境呀~
  • +
  • + 黑傑克晚安:
    拍謝!出門五天才剛剛入門,外出使用平板電腦 +
    實在很不方便中文輸入跟回應.... +
    您客氣了,我們只是很一般的而已,看了您的 +
    瑞士之行...才是仙境,會流口水哦! +

    史蒂文的家_藍天 於 2014/01/01 20:17 回覆

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  • +
+
    +
  • + 悄悄話
  • +
+
    + +
  • + 飛兒 +
  • +
  • +

    + 那年 我不是才不約而同到美樹賞楓
    好快 又過了一年
    山嵐在遠方飄移 讓秋楓更有意境
    美樹的楓香 不管怎麼拍都很美
    石磊部落 我在原民台看過介紹
    是一個以種植有機蔬果為主的部落 +
    也是一個很美的地方 我還沒去過
    期待藍天大哥的分享
  • +
  • + 飛兒晚安:
    說的也是,那年真的是不約而同, +
    只差沒真的碰面而已..如今又已 +
    倏逾兩年了... +
    回程走"石磊道路"再轉回北橫巴崚, +
    切回三峽回台北,路況好遠喲... +

    史蒂文的家_藍天 於 2014/01/02 23:36 回覆

    +
  • +
+
    + +
  • + 王昆 +
  • +
  • +

    + 欣賞好圖文唷~
    安安~工作愉快~~順心~
  • +
  • + 謝謝賞圖!
    祝福~順遂 +

    史蒂文的家_藍天 於 2014/01/13 23:05 回覆

    +
  • +
+
    + +
  • + 大小姐 +
  • +
  • +

    + 真是讓人羨慕的生活喔
  • +
  • + 大小姐 晚安:
    露營是另外一種戶外生活,您的餐飲美食生活 +
    也是不遑多讓ㄜ... +

    史蒂文的家_藍天 於 2014/01/02 23:30 回覆

    +
  • +
+
    + +
  • + 王昆 +
  • +
  • +

    + 賞圖文唷~美唷!! 善知識晚安安
    +
    祝您馬年行大運馬上賺大錢唷~ +
    +
  • +
  • + 也祝您 新春愉快,新的一年心想事成,萬事如意 +

    史蒂文的家_藍天 於 2014/01/02 23:59 回覆

    +
  • +
+
    + +
  • + 光頭 +
  • +
  • +

    + 楓樹 落葉~這地方太美~拍照真美
  • +
  • + 光頭 晚安:
    這格地點的楓香泛紅之際是最美的時刻, +
    人在現場看更是會感動的地方... +

    史蒂文的家_藍天 於 2014/01/02 23:32 回覆

    +
  • +
+
    +
  • + 悄悄話
  • +
+
    + +
  • + Sheila Teng +
  • +
  • +

    + 台灣能找到這麼厚實的楓葉地毯...不容易呀!!
    此時若想低拍就會羨慕起那些螢幕可翻轉的相機了~ +
    +
    控溪吊橋那邊我拍過, 風景真的很棒!
    美樹名字取得簡單乾脆... +
    這個地方記下來了, 不必去石門水庫人擠人
    這裡的楓葉更有看頭哩!!! +
    +
  • +
  • + Sheila晚安:
    來到秀巒軍艦岩、控溪吊橋拍秋楓的話, +
    那就得順道去"美樹"拍楓香林才不需此行, +
    一個簡單的營地卻是愛攝人士每年必訪之地, +
    攝影老師總是帶著學員來此地外拍練習, +
    要是妳來拍攝的話,必然精彩可期,"另眼看待"ㄜ! +

    史蒂文的家_藍天 於 2014/01/03 22:07 回覆

    +
  • +
+
    + +
  • + 阿麗瑪 +
  • +
  • +

    + 先來說個老梗~落花並非無情物,化作春泥更護花!♥
    落葉鋪成的地毯真的感覺粉溫馨吼? +
    哦~你們南來北往大會師噢? +
    美樹營地好美呢!偶們一心一意直奔司馬庫斯所以沒有近來賞景... +
    伙食好讚噢!偶們四餐有兩餐試吃泡麵,早餐是吃隔夜飯泡水的硬硬不濃稠稀飯...☹ +
    恭喜你們收穫滿行曩♣★ +
    噢對!還有怎麼睡車上呢?露營車嗎?偶們去年元旦去國境之南找不到旅館也是當了車床族~睡車上...好累!︿_*
  • +
  • + 阿麗瑪晚安:
    這個季節的楓香林剛好泛紅,剛好連日來雨勢不斷變成 +
    落葉成塚,否則滿滿色彩的楓樹是最美的! 阿蒯之家特地
    從南部北上一起同露,蒯嫂手藝很棒我們才有口福哩! +
    我們是休旅車,經由專門店家改裝成"活動式車床",拆卸快速 +
    只需要五分鐘就可以搞定,長度180公分(含海棉墊)這樣睡眠 +
    才有品質,一覺到天亮甚至會睡過頭... +

    史蒂文的家_藍天 於 2014/01/03 23:11 回覆

    +
  • +
+ +
    +
  • + 悄悄話
  • +
+
    + +
  • + lily +
  • +
  • +

    + 第一張相片的貓頭鷹實在是太吸睛了~~
    這裡賞楓露營真是好地方 +
    出去露營能吃到如此豐盛 +
    真是超級羨慕ㄋ
  • +
  • + Lily 晚安:
    美樹營地招牌上分別佈置了幾隻貓頭鷹, +
    顏色鮮豔也很可愛,也成為愛攝人士的鏡頭 +
    追逐焦點,有機會可以去看一看! +

    史蒂文的家_藍天 於 2014/01/09 21:10 回覆

    +
  • +
+
    + +
  • + tinned +
  • +
  • +

    + 北七強的由來ㄚ
    就很簡單ㄚ 畫圖的時候很單純 很少去想最後的結果
    +
    北七 還挺不錯的ㄚ 可能是指ㄧ個心境問題喔
  • +
  • + 簍信,有緣認識你們這些朋友真是幸運了!
    "北七" 的取名太有意思了~~
    (拍謝, 今早上才見到有漏回覆的,金害ㄟ) +

    史蒂文的家_藍天 於 2014/02/10 10:22 回覆

    +
  • +
+ +
    + +
  • + 訪客
  • +
  • +

    + 真的拍得好棒好溫馨~~
  • +
  • + 謝謝賞圖/文! +

    史蒂文的家_藍天 於 2015/11/30 17:40 回覆

    +
  • +
+
    + +
  • + qiqichoi +
  • +
  • +

    + 真是太美了
  • +
  • + 謝謝你的喜歡~
    +

    史蒂文的家_藍天 於 2016/07/05 19:26 回覆

    +
  • +
+ +
    + +
  • + 米可 +
  • +
  • +

    + 這太美了!好喜歡,我從沒看過,希望有一天可以去看看走一趟!
  • +
  • + 這裡是新竹縣秀巒鄉很著名的攝影景點,
    如果不是露營的話也可以趁著早上開放時間拍照, +
    付入園會即可入內盡情拍照... +
    PS:每年楓紅時間"大約"是12月中...左右, +
    實際還得視當地氣溫而定 +

    史蒂文的家_藍天 於 2016/08/02 10:37 回覆

    +
  • +
+ + +
    + +
  • + Quby +
  • +
  • +

    + 再過不久又進入秋天了
    楓葉照令人很期待呢 +
    而且到時候的天氣適合露營 +
    不會很濕熱也不會太冷
  • +
  • + 入秋之後寒流來襲就容易讓秋楓變色,
    秋高氣爽野正是露營的好時節 +

    史蒂文的家_藍天 於 2016/09/08 18:37 回覆

    +
  • +
+
    + +
  • + 面面 +
  • +
  • +

    + 拍的照片真的好美 謝謝
  • +
  • + 謝謝妳的喜歡~ +

    史蒂文的家_藍天 於 2016/09/13 18:13 回覆

    +
  • +
+
    + +
  • + 木博士 +
  • +
  • +

    + 很美~美術營是帶小朋友去玩的好地方!!
  • +
  • + 美樹營地有奇迷人之處,春夏秋冬各有其特色,
    小朋友玩耍也很安全的! +

    史蒂文的家_藍天 於 2016/09/23 09:38 回覆

    +
  • +
+
    + +
  • + tw27003265 +
  • +
  • +

    + 秋之景好美呢
  • +
  • + 新竹秀巒一帶的熱門楓紅景點之一 +

    史蒂文的家_藍天 於 2016/10/04 09:47 回覆

    +
  • +
+ +
    + +
  • + Jenny10113 +
  • +
  • +

    + 好夢幻喔!!!!!
  • +
  • + 很美的楓香營地,楓紅時節也是熱門的拍照景點 +

    史蒂文的家_藍天 於 2016/10/04 09:46 回覆

    +
  • +
+
    + +
  • + GE台北車庫-小壕 +
  • +
  • +

    + 好適合約會的地方~
  • +
  • + 小而美的營地,一年四季的楓箱各有特色,
    適合各式各樣的聚會ㄜ +

    史蒂文的家_藍天 於 2016/10/04 09:45 回覆

    +
  • +
+
    + +
  • + 廣州十大旅遊景點
  • +
  • +

    + 這篇寫的很好
    歡迎回訪喔
  • +
  • + 謝謝你!
    +
    +

    史蒂文的家_藍天 於 2016/10/12 14:25 回覆

    +
  • +
+
    + +
  • + tw27003265 +
  • +
  • +

    + 又是看秋景的季節
  • +
+ +
    + +
  • + 蔡敏嫻 +
  • +
  • +

    + 真是個美麗的好地方,感謝分享~
  • +
  • + 謝謝賞圖文! +

    史蒂文的家_藍天 於 2017/01/19 21:05 回覆

    +
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+
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DeepMind新电脑已可利用记忆自学 人工智能迈上新台阶

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+ TNW中文站2016年10月14日07:17 + + + +
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转播到腾讯微博
DeepMind新电脑已可利用记忆自学 人工智能迈上新台阶
+

TNW中文站 10月14日报道

+

+ 谷歌(微博) + 在2014年收购的人工智能公司DeepMind开发出一款能够用自己的记忆学习新知识并利用这些知识来回答问题的计算机。

+

这款产品具有极其重要的意义,因为这意味着未来的人工智能技术可能不需要人类来教它就能回答人类提出的问题。

+

DeepMind表示,这款名为DNC(可微神经计算机)的AI模型可以接受家谱和伦敦地铁网络地图这样的信息,还可以回答与那些数据结构中的不同项目之间的关系有关的复杂问题。

+

例如,它可以回答“从邦德街开始,沿着中央线坐一站,环线坐四站,然后转朱比利线坐两站,你会到达哪个站?”这样的问题。

+

DeepMind称,DNC还可以帮你规划从沼泽门到皮卡迪利广场的最佳路线。

+

同样,它还可以理解和回答某个大家族中的成员之间的关系这样的复杂问题,比如“张三的大舅是谁?”。

+

DNC建立在神经网络的概念之上,神经网络可以模拟人类思想活动的方式。这种AI技术很适合与机器习得配套使用。

+

DeepMind的AlphaGo AI能够打败围棋冠军也跟这些神经网络有很大关系。但是AlphaGo必须进行训练才行,开发人员向AlphaGo提供了历史对弈中的大约3000万记录。让人工智能技术具备通过记忆学习的能力,就可以让它独自完成更复杂的任务。

+

DeepMind希望DNC可以推动计算行业实现更多突破。DeepMind已将其研究结果发表在科学刊物《自然》(Nature)上。(编译/林靖东)

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    【美国The Next Web作品的中文相关权益归腾讯公司独家所有。未经授权,不得转载、摘编等。】

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    +
    +

    + A little over half a century ago, chaos started spilling out of a famous experiment. It came not from a petri dish, a beaker or an astronomical observatory, but from the vacuum tubes and diodes of a Royal McBee LGP-30. This “desk” computer — it was the size of a desk — weighed some 800 pounds and sounded like a passing propeller plane. It was so loud that it even got its own office on the fifth floor in Building 24, a drab structure near the center of the Massachusetts Institute of Technology. Instructions for the computer came from down the hall, from the office of a meteorologist named Edward Norton Lorenz. +

    + +

    + The story of chaos is usually told like this: Using the LGP-30, Lorenz made paradigm-wrecking discoveries. In 1961, having programmed a set of equations into the computer that would simulate future weather, he found that tiny differences in starting values could lead to drastically different outcomes. This sensitivity to initial conditions, later popularized as the butterfly effect, made predicting the far future a fool’s errand. But Lorenz also found that these unpredictable outcomes weren’t quite random, either. When visualized in a certain way, they seemed to prowl around a shape called a strange attractor. +

    +

    + About a decade later, chaos theory started to catch on in scientific circles. Scientists soon encountered other unpredictable natural systems that looked random even though they weren’t: the rings of Saturn, blooms of marine algae, Earth’s magnetic field, the number of salmon in a fishery. Then chaos went mainstream with the publication of James Gleick’s Chaos: Making a New Science in 1987. Before long, Jeff Goldblum, playing the chaos theorist Ian Malcolm, was pausing, stammering and charming his way through lines about the unpredictability of nature in Jurassic Park. +

    +

    + All told, it’s a neat narrative. Lorenz, “the father of chaos,” started a scientific revolution on the LGP-30. It is quite literally a textbook case for how the numerical experiments that modern science has come to rely on — in fields ranging from climate science to ecology to astrophysics — can uncover hidden truths about nature. +

    +

    + But in fact, Lorenz was not the one running the machine. There’s another story, one that has gone untold for half a century. A year and a half ago, an MIT scientist happened across a name he had never heard before and started to investigate. The trail he ended up following took him into the MIT archives, through the stacks of the Library of Congress, and across three states and five decades to find information about the women who, today, would have been listed as co-authors on that seminal paper. And that material, shared with Quanta, provides a fuller, fairer account of the birth of chaos. +

    +

    + The Birth of Chaos +

    +

    + In the fall of 2017, the geophysicist Daniel Rothman, co-director of MIT’s Lorenz Center, was preparing for an upcoming symposium. The meeting would honor Lorenz, who died in 2008, so Rothman revisited Lorenz’s epochal paper, a masterwork on chaos titled “Deterministic Nonperiodic Flow.” Published in 1963, it has since attracted thousands of citations, and Rothman, having taught this foundational material to class after class, knew it like an old friend. But this time he saw something he hadn’t noticed before. In the paper’s acknowledgments, Lorenz had written, “Special thanks are due to Miss Ellen Fetter for handling the many numerical computations.” +

    +

    + “Jesus … who is Ellen Fetter?” Rothman recalls thinking at the time. “It’s one of the most important papers in computational physics and, more broadly, in computational science,” he said. And yet he couldn’t find anything about this woman. “Of all the volumes that have been written about Lorenz, the great discovery — nothing.” +

    + +

    + With further online searches, however, Rothman found a wedding announcement from 1963. Ellen Fetter had married John Gille, a physicist, and changed her name. A colleague of Rothman’s then remembered that a graduate student named Sarah Gille had studied at MIT in the 1990s in the very same department as Lorenz and Rothman. Rothman reached out to her, and it turned out that Sarah Gille, now a physical oceanographer at the University of California, San Diego, was Ellen and John’s daughter. Through this connection, Rothman was able to get Ellen Gille, née Fetter, on the phone. And that’s when he learned another name, the name of the woman who had preceded Fetter in the job of programming Lorenz’s first meetings with chaos: Margaret Hamilton. +

    +

    + When Margaret Hamilton arrived at MIT in the summer of 1959, with a freshly minted math degree from Earlham College, Lorenz had only recently bought and taught himself to use the LGP-30. Hamilton had no prior training in programming either. Then again, neither did anyone else at the time. “He loved that computer,” Hamilton said. “And he made me feel the same way about it.” +

    +

    + For Hamilton, these were formative years. She recalls being out at a party at three or four a.m., realizing that the LGP-30 wasn’t set to produce results by the next morning, and rushing over with a few friends to start it up. Another time, frustrated by all the things that had to be done to make another run after fixing an error, she devised a way to bypass the computer’s clunky debugging process. To Lorenz’s delight, Hamilton would take the paper tape that fed the machine, roll it out the length of the hallway, and edit the binary code with a sharp pencil. “I’d poke holes for ones, and I’d cover up with Scotch tape the others,” she said. “He just got a kick out of it.” +

    +
    +
    +

    + There were desks in the computer room, but because of the noise, Lorenz, his secretary, his programmer and his graduate students all shared the other office. The plan was to use the desk computer, then a total novelty, to test competing strategies of weather prediction in a way you couldn’t do with pencil and paper. +

    +

    + First, though, Lorenz’s team had to do the equivalent of catching the Earth’s atmosphere in a jar. Lorenz idealized the atmosphere in 12 equations that described the motion of gas in a rotating, stratified fluid. Then the team coded them in. +

    +

    + Sometimes the “weather” inside this simulation would simply repeat like clockwork. But Lorenz found a more interesting and more realistic set of solutions that generated weather that wasn’t periodic. The team set up the computer to slowly print out a graph of how one or two variables — say, the latitude of the strongest westerly winds — changed over time. They would gather around to watch this imaginary weather, even placing little bets on what the program would do next. +

    +

    + And then one day it did something really strange. This time they had set up the printer not to make a graph, but simply to print out time stamps and the values of a few variables at each time. As Lorenz later recalled, they had re-run a previous weather simulation with what they thought were the same starting values, reading off the earlier numbers from the previous printout. But those weren’t actually the same numbers. The computer was keeping track of numbers to six decimal places, but the printer, to save space on the page, had rounded them to only the first three decimal places. +

    +

    + After the second run started, Lorenz went to get coffee. The new numbers that emerged from the LGP-30 while he was gone looked at first like the ones from the previous run. This new run had started in a very similar place, after all. But the errors grew exponentially. After about two months of imaginary weather, the two runs looked nothing alike. This system was still deterministic, with no random chance intruding between one moment and the next. Even so, its hair-trigger sensitivity to initial conditions made it unpredictable. +

    +

    + This meant that in chaotic systems the smallest fluctuations get amplified. Weather predictions fail once they reach some point in the future because we can never measure the initial state of the atmosphere precisely enough. Or, as Lorenz would later present the idea, even a seagull flapping its wings might eventually make a big difference to the weather. (In 1972, the seagull was deposed when a conference organizer, unable to check back about what Lorenz wanted to call an upcoming talk, wrote his own title that switched the metaphor to a butterfly.) +

    +
    +
    +

    + Many accounts, including the one in Gleick’s book, date the discovery of this butterfly effect to 1961, with the paper following in 1963. But in November 1960, Lorenz described it during the Q&A session following a talk he gave at a conference on numerical weather prediction in Tokyo. After his talk, a question came from a member of the audience: “Did you change the initial condition just slightly and see how much different results were?” +

    +

    + “As a matter of fact, we tried out that once with the same equation to see what could happen,” Lorenz said. He then started to explain the unexpected result, which he wouldn’t publish for three more years. “He just gives it all away,” Rothman said now. But no one at the time registered it enough to scoop him. +

    +

    + In the summer of 1961, Hamilton moved on to another project, but not before training her replacement. Two years after Hamilton first stepped on campus, Ellen Fetter showed up at MIT in much the same fashion: a recent graduate of Mount Holyoke with a degree in math, seeking any sort of math-related job in the Boston area, eager and able to learn. She interviewed with a woman who ran the LGP-30 in the nuclear engineering department, who recommended her to Hamilton, who hired her. +

    +

    + Once Fetter arrived in Building 24, Lorenz gave her a manual and a set of programming problems to practice, and before long she was up to speed. “He carried a lot in his head,” she said. “He would come in with maybe one yellow sheet of paper, a legal piece of paper in his pocket, pull it out, and say, ‘Let’s try this.’” +

    +

    + The project had progressed meanwhile. The 12 equations produced fickle weather, but even so, that weather seemed to prefer a narrow set of possibilities among all possible states, forming a mysterious cluster which Lorenz wanted to visualize. Finding that difficult, he narrowed his focus even further. From a colleague named Barry Saltzman, he borrowed just three equations that would describe an even simpler nonperiodic system, a beaker of water heated from below and cooled from above. +

    +

    + Here, again, the LGP-30 chugged its way into chaos. Lorenz identified three properties of the system corresponding roughly to how fast convection was happening in the idealized beaker, how the temperature varied from side to side, and how the temperature varied from top to bottom. The computer tracked these properties moment by moment. +

    +

    + The properties could also be represented as a point in space. Lorenz and Fetter plotted the motion of this point. They found that over time, the point would trace out a butterfly-shaped fractal structure now called the Lorenz attractor. The trajectory of the point — of the system — would never retrace its own path. And as before, two systems setting out from two minutely different starting points would soon be on totally different tracks. But just as profoundly, wherever you started the system, it would still head over to the attractor and start doing chaotic laps around it. +

    + +

    + The attractor and the system’s sensitivity to initial conditions would eventually be recognized as foundations of chaos theory. Both were published in the landmark 1963 paper. But for a while only meteorologists noticed the result. Meanwhile, Fetter married John Gille and moved with him when he went to Florida State University and then to Colorado. They stayed in touch with Lorenz and saw him at social events. But she didn’t realize how famous he had become. +

    +

    + Still, the notion of small differences leading to drastically different outcomes stayed in the back of her mind. She remembered the seagull, flapping its wings. “I always had this image that stepping off the curb one way or the other could change the course of any field,” she said. +

    +

    + Flight Checks +

    +

    + After leaving Lorenz’s group, Hamilton embarked on a different path, achieving a level of fame that rivals or even exceeds that of her first coding mentor. At MIT’s Instrumentation Laboratory, starting in 1965, she headed the onboard flight software team for the Apollo project. +

    +

    + Her code held up when the stakes were life and death — even when a mis-flipped switch triggered alarms that interrupted the astronaut’s displays right as Apollo 11 approached the surface of the moon. Mission Control had to make a quick choice: land or abort. But trusting the software’s ability to recognize errors, prioritize important tasks, and recover, the astronauts kept going. +

    +

    + Hamilton, who popularized the term “software engineering,” later led the team that wrote the software for Skylab, the first U.S. space station. She founded her own company in Cambridge in 1976, and in recent years her legacy has been celebrated again and again. She won NASA’s Exceptional Space Act Award in 2003 and received the Presidential Medal of Freedom in 2016. In 2017 she garnered arguably the greatest honor of all: a Margaret Hamilton Lego minifigure. +

    + +

    + Fetter, for her part, continued to program at Florida State after leaving Lorenz’s group at MIT. After a few years, she left her job to raise her children. In the 1970s, she took computer science classes at the University of Colorado, toying with the idea of returning to programming, but she eventually took a tax preparation job instead. By the 1980s, the demographics of programming had shifted. “After I sort of got put off by a couple of job interviews, I said forget it,” she said. “They went with young, techy guys.” +

    +

    + Chaos only reentered her life through her daughter, Sarah. As an undergraduate at Yale in the 1980s, Sarah Gille sat in on a class about scientific programming. The case they studied? Lorenz’s discoveries on the LGP-30. Later, Sarah studied physical oceanography as a graduate student at MIT, joining the same overarching department as both Lorenz and Rothman, who had arrived a few years earlier. “One of my office mates in the general exam, the qualifying exam for doing research at MIT, was asked: How would you explain chaos theory to your mother?” she said. “I was like, whew, glad I didn’t get that question.” +

    +

    + The Changing Value of Computation +

    +

    + Today, chaos theory is part of the scientific repertoire. In a study published just last month, researchers concluded that no amount of improvement in data gathering or in the science of weather forecasting will allow meteorologists to produce useful forecasts that stretch more than 15 days out. (Lorenz had suggested a similar two-week cap to weather forecasts in the mid-1960s.) +

    +

    + But the many retellings of chaos’s birth say little to nothing about how Hamilton and Ellen Gille wrote the specific programs that revealed the signatures of chaos. “This is an all-too-common story in the histories of science and technology,” wrote Jennifer Light, the department head for MIT’s Science, Technology and Society program, in an email to Quanta. To an extent, we can chalk up that omission to the tendency of storytellers to focus on solitary geniuses. But it also stems from tensions that remain unresolved today. +

    +

    + First, coders in general have seen their contributions to science minimized from the beginning. “It was seen as rote,” said Mar Hicks, a historian at the Illinois Institute of Technology. “The fact that it was associated with machines actually gave it less status, rather than more.” But beyond that, and contributing to it, many programmers in this era were women. +

    +

    + In addition to Hamilton and the woman who coded in MIT’s nuclear engineering department, Ellen Gille recalls a woman on an LGP-30 doing meteorology next door to Lorenz’s group. Another woman followed Gille in the job of programming for Lorenz. An analysis of official U.S. labor statistics shows that in 1960, women held 27 percent of computing and math-related jobs. +

    +

    + The percentage has been stuck there for a half-century. In the mid-1980s, the fraction of women pursuing bachelor’s degrees in programming even started to decline. Experts have argued over why. One idea holds that early personal computers were marketed preferentially to boys and men. Then when kids went to college, introductory classes assumed a detailed knowledge of computers going in, which alienated young women who didn’t grow up with a machine at home. Today, women programmers describe a self-perpetuating cycle where white and Asian male managers hire people who look like all the other programmers they know. Outright harassment also remains a problem. +

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    + Hamilton and Gille, however, still speak of Lorenz’s humility and mentorship in glowing terms. Before later chroniclers left them out, Lorenz thanked them in the literature in the same way he thanked Saltzman, who provided the equations Lorenz used to find his attractor. This was common at the time. Gille recalls that in all her scientific programming work, only once did someone include her as a co-author after she contributed computational work to a paper; she said she was “stunned” because of how unusual that was. +

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    + Since then, the standard for giving credit has shifted. “If you went up and down the floors of this building and told the story to my colleagues, every one of them would say that if this were going on today … they’d be a co-author!” Rothman said. “Automatically, they’d be a co-author.” +

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    + Computation in science has become even more indispensable, of course. For recent breakthroughs like the first image of a black hole, the hard part was not figuring out which equations described the system, but how to leverage computers to understand the data. +

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    + Today, many programmers leave science not because their role isn’t appreciated, but because coding is better compensated in industry, said Alyssa Goodman, an astronomer at Harvard University and an expert in computing and data science. “In the 1960s, there was no such thing as a data scientist, there was no such thing as Netflix or Google or whoever, that was going to suck in these people and really, really value them,” she said. +

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    + Still, for coder-scientists in academic systems that measure success by paper citations, things haven’t changed all that much. “If you are a software developer who may never write a paper, you may be essential,” Goodman said. “But you’re not going to be counted that way.” +

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    + This article was reprinted on Wired.com. +

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    diff --git a/resources/tests/readability/quanta-1/source.html b/resources/tests/readability/quanta-1/source.html new file mode 100644 index 0000000..dcdf4f7 --- /dev/null +++ b/resources/tests/readability/quanta-1/source.html @@ -0,0 +1,1208 @@ + + + + + Quanta Magazine + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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    + The Hidden Heroines of Chaos +

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    + Two women programmers played a pivotal role in the birth of chaos theory. Their previously untold story illustrates the changing status of computation in science. +
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    + Animated line drawing of Margaret Hamilton, Ellen Fetter, and a Lorenz attractor +
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    + Ellen Fetter and Margaret Hamilton were responsible for programming the enormous 1960s-era computer that would uncover strange attractors and other hallmarks of chaos theory. +

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    + Olena Shmahalo/Quanta Magazine +

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    + A little over half a century ago, chaos started spilling out of a famous experiment. It came not from a petri dish, a beaker or an astronomical observatory, but from the vacuum tubes and diodes of a Royal McBee LGP-30. This “desk” computer — it was the size of a desk — weighed some 800 pounds and sounded like a passing propeller plane. It was so loud that it even got its own office on the fifth floor in Building 24, a drab structure near the center of the Massachusetts Institute of Technology. Instructions for the computer came from down the hall, from the office of a meteorologist named Edward Norton Lorenz. +

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    + The story of chaos is usually told like this: Using the LGP-30, Lorenz made paradigm-wrecking discoveries. In 1961, having programmed a set of equations into the computer that would simulate future weather, he found that tiny differences in starting values could lead to drastically different outcomes. This sensitivity to initial conditions, later popularized as the butterfly effect, made predicting the far future a fool’s errand. But Lorenz also found that these unpredictable outcomes weren’t quite random, either. When visualized in a certain way, they seemed to prowl around a shape called a strange attractor. +

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    + About a decade later, chaos theory started to catch on in scientific circles. Scientists soon encountered other unpredictable natural systems that looked random even though they weren’t: the rings of Saturn, blooms of marine algae, Earth’s magnetic field, the number of salmon in a fishery. Then chaos went mainstream with the publication of James Gleick’s Chaos: Making a New Science in 1987. Before long, Jeff Goldblum, playing the chaos theorist Ian Malcolm, was pausing, stammering and charming his way through lines about the unpredictability of nature in Jurassic Park. +

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    + All told, it’s a neat narrative. Lorenz, “the father of chaos,” started a scientific revolution on the LGP-30. It is quite literally a textbook case for how the numerical experiments that modern science has come to rely on — in fields ranging from climate science to ecology to astrophysics — can uncover hidden truths about nature. +

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    + But in fact, Lorenz was not the one running the machine. There’s another story, one that has gone untold for half a century. A year and a half ago, an MIT scientist happened across a name he had never heard before and started to investigate. The trail he ended up following took him into the MIT archives, through the stacks of the Library of Congress, and across three states and five decades to find information about the women who, today, would have been listed as co-authors on that seminal paper. And that material, shared with Quanta, provides a fuller, fairer account of the birth of chaos. +

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    + The Birth of Chaos +

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    + In the fall of 2017, the geophysicist Daniel Rothman, co-director of MIT’s Lorenz Center, was preparing for an upcoming symposium. The meeting would honor Lorenz, who died in 2008, so Rothman revisited Lorenz’s epochal paper, a masterwork on chaos titled “Deterministic Nonperiodic Flow.” Published in 1963, it has since attracted thousands of citations, and Rothman, having taught this foundational material to class after class, knew it like an old friend. But this time he saw something he hadn’t noticed before. In the paper’s acknowledgments, Lorenz had written, “Special thanks are due to Miss Ellen Fetter for handling the many numerical computations.” +

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    + “Jesus … who is Ellen Fetter?” Rothman recalls thinking at the time. “It’s one of the most important papers in computational physics and, more broadly, in computational science,” he said. And yet he couldn’t find anything about this woman. “Of all the volumes that have been written about Lorenz, the great discovery — nothing.” +

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    + With further online searches, however, Rothman found a wedding announcement from 1963. Ellen Fetter had married John Gille, a physicist, and changed her name. A colleague of Rothman’s then remembered that a graduate student named Sarah Gille had studied at MIT in the 1990s in the very same department as Lorenz and Rothman. Rothman reached out to her, and it turned out that Sarah Gille, now a physical oceanographer at the University of California, San Diego, was Ellen and John’s daughter. Through this connection, Rothman was able to get Ellen Gille, née Fetter, on the phone. And that’s when he learned another name, the name of the woman who had preceded Fetter in the job of programming Lorenz’s first meetings with chaos: Margaret Hamilton. +

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    + When Margaret Hamilton arrived at MIT in the summer of 1959, with a freshly minted math degree from Earlham College, Lorenz had only recently bought and taught himself to use the LGP-30. Hamilton had no prior training in programming either. Then again, neither did anyone else at the time. “He loved that computer,” Hamilton said. “And he made me feel the same way about it.” +

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    + For Hamilton, these were formative years. She recalls being out at a party at three or four a.m., realizing that the LGP-30 wasn’t set to produce results by the next morning, and rushing over with a few friends to start it up. Another time, frustrated by all the things that had to be done to make another run after fixing an error, she devised a way to bypass the computer’s clunky debugging process. To Lorenz’s delight, Hamilton would take the paper tape that fed the machine, roll it out the length of the hallway, and edit the binary code with a sharp pencil. “I’d poke holes for ones, and I’d cover up with Scotch tape the others,” she said. “He just got a kick out of it.” +

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    + Acknowledgements of Ellen Fetter and Margaret Hamilton in Edward Lorenz' 1963 and 1962 papers +
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    + Edward Lorenz acknowledged the contributions of Fetter and Hamilton at the end of his papers. +

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    + There were desks in the computer room, but because of the noise, Lorenz, his secretary, his programmer and his graduate students all shared the other office. The plan was to use the desk computer, then a total novelty, to test competing strategies of weather prediction in a way you couldn’t do with pencil and paper. +

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    + First, though, Lorenz’s team had to do the equivalent of catching the Earth’s atmosphere in a jar. Lorenz idealized the atmosphere in 12 equations that described the motion of gas in a rotating, stratified fluid. Then the team coded them in. +

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    + Sometimes the “weather” inside this simulation would simply repeat like clockwork. But Lorenz found a more interesting and more realistic set of solutions that generated weather that wasn’t periodic. The team set up the computer to slowly print out a graph of how one or two variables — say, the latitude of the strongest westerly winds — changed over time. They would gather around to watch this imaginary weather, even placing little bets on what the program would do next. +

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    + And then one day it did something really strange. This time they had set up the printer not to make a graph, but simply to print out time stamps and the values of a few variables at each time. As Lorenz later recalled, they had re-run a previous weather simulation with what they thought were the same starting values, reading off the earlier numbers from the previous printout. But those weren’t actually the same numbers. The computer was keeping track of numbers to six decimal places, but the printer, to save space on the page, had rounded them to only the first three decimal places. +

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    + After the second run started, Lorenz went to get coffee. The new numbers that emerged from the LGP-30 while he was gone looked at first like the ones from the previous run. This new run had started in a very similar place, after all. But the errors grew exponentially. After about two months of imaginary weather, the two runs looked nothing alike. This system was still deterministic, with no random chance intruding between one moment and the next. Even so, its hair-trigger sensitivity to initial conditions made it unpredictable. +

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    + This meant that in chaotic systems the smallest fluctuations get amplified. Weather predictions fail once they reach some point in the future because we can never measure the initial state of the atmosphere precisely enough. Or, as Lorenz would later present the idea, even a seagull flapping its wings might eventually make a big difference to the weather. (In 1972, the seagull was deposed when a conference organizer, unable to check back about what Lorenz wanted to call an upcoming talk, wrote his own title that switched the metaphor to a butterfly.) +

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    + "A Brief History of Chaos" Infographic +
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    + 5W Infographics for Quanta Magazine; sources: Wikimedia Commons,
    + Mathematical Association of America, MIT Museum +

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    + Many accounts, including the one in Gleick’s book, date the discovery of this butterfly effect to 1961, with the paper following in 1963. But in November 1960, Lorenz described it during the Q&A session following a talk he gave at a conference on numerical weather prediction in Tokyo. After his talk, a question came from a member of the audience: “Did you change the initial condition just slightly and see how much different results were?” +

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    + “As a matter of fact, we tried out that once with the same equation to see what could happen,” Lorenz said. He then started to explain the unexpected result, which he wouldn’t publish for three more years. “He just gives it all away,” Rothman said now. But no one at the time registered it enough to scoop him. +

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    + In the summer of 1961, Hamilton moved on to another project, but not before training her replacement. Two years after Hamilton first stepped on campus, Ellen Fetter showed up at MIT in much the same fashion: a recent graduate of Mount Holyoke with a degree in math, seeking any sort of math-related job in the Boston area, eager and able to learn. She interviewed with a woman who ran the LGP-30 in the nuclear engineering department, who recommended her to Hamilton, who hired her. +

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    + Once Fetter arrived in Building 24, Lorenz gave her a manual and a set of programming problems to practice, and before long she was up to speed. “He carried a lot in his head,” she said. “He would come in with maybe one yellow sheet of paper, a legal piece of paper in his pocket, pull it out, and say, ‘Let’s try this.’” +

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    + The project had progressed meanwhile. The 12 equations produced fickle weather, but even so, that weather seemed to prefer a narrow set of possibilities among all possible states, forming a mysterious cluster which Lorenz wanted to visualize. Finding that difficult, he narrowed his focus even further. From a colleague named Barry Saltzman, he borrowed just three equations that would describe an even simpler nonperiodic system, a beaker of water heated from below and cooled from above. +

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    + Here, again, the LGP-30 chugged its way into chaos. Lorenz identified three properties of the system corresponding roughly to how fast convection was happening in the idealized beaker, how the temperature varied from side to side, and how the temperature varied from top to bottom. The computer tracked these properties moment by moment. +

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    + The properties could also be represented as a point in space. Lorenz and Fetter plotted the motion of this point. They found that over time, the point would trace out a butterfly-shaped fractal structure now called the Lorenz attractor. The trajectory of the point — of the system — would never retrace its own path. And as before, two systems setting out from two minutely different starting points would soon be on totally different tracks. But just as profoundly, wherever you started the system, it would still head over to the attractor and start doing chaotic laps around it. +

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    + The attractor and the system’s sensitivity to initial conditions would eventually be recognized as foundations of chaos theory. Both were published in the landmark 1963 paper. But for a while only meteorologists noticed the result. Meanwhile, Fetter married John Gille and moved with him when he went to Florida State University and then to Colorado. They stayed in touch with Lorenz and saw him at social events. But she didn’t realize how famous he had become. +

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    + Still, the notion of small differences leading to drastically different outcomes stayed in the back of her mind. She remembered the seagull, flapping its wings. “I always had this image that stepping off the curb one way or the other could change the course of any field,” she said. +

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    + Flight Checks +

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    + After leaving Lorenz’s group, Hamilton embarked on a different path, achieving a level of fame that rivals or even exceeds that of her first coding mentor. At MIT’s Instrumentation Laboratory, starting in 1965, she headed the onboard flight software team for the Apollo project. +

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    + Her code held up when the stakes were life and death — even when a mis-flipped switch triggered alarms that interrupted the astronaut’s displays right as Apollo 11 approached the surface of the moon. Mission Control had to make a quick choice: land or abort. But trusting the software’s ability to recognize errors, prioritize important tasks, and recover, the astronauts kept going. +

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    + Hamilton, who popularized the term “software engineering,” later led the team that wrote the software for Skylab, the first U.S. space station. She founded her own company in Cambridge in 1976, and in recent years her legacy has been celebrated again and again. She won NASA’s Exceptional Space Act Award in 2003 and received the Presidential Medal of Freedom in 2016. In 2017 she garnered arguably the greatest honor of all: a Margaret Hamilton Lego minifigure. +

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    + Fetter, for her part, continued to program at Florida State after leaving Lorenz’s group at MIT. After a few years, she left her job to raise her children. In the 1970s, she took computer science classes at the University of Colorado, toying with the idea of returning to programming, but she eventually took a tax preparation job instead. By the 1980s, the demographics of programming had shifted. “After I sort of got put off by a couple of job interviews, I said forget it,” she said. “They went with young, techy guys.” +

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    + Chaos only reentered her life through her daughter, Sarah. As an undergraduate at Yale in the 1980s, Sarah Gille sat in on a class about scientific programming. The case they studied? Lorenz’s discoveries on the LGP-30. Later, Sarah studied physical oceanography as a graduate student at MIT, joining the same overarching department as both Lorenz and Rothman, who had arrived a few years earlier. “One of my office mates in the general exam, the qualifying exam for doing research at MIT, was asked: How would you explain chaos theory to your mother?” she said. “I was like, whew, glad I didn’t get that question.” +

    +

    + The Changing Value of Computation +

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    + Today, chaos theory is part of the scientific repertoire. In a study published just last month, researchers concluded that no amount of improvement in data gathering or in the science of weather forecasting will allow meteorologists to produce useful forecasts that stretch more than 15 days out. (Lorenz had suggested a similar two-week cap to weather forecasts in the mid-1960s.) +

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    + But the many retellings of chaos’s birth say little to nothing about how Hamilton and Ellen Gille wrote the specific programs that revealed the signatures of chaos. “This is an all-too-common story in the histories of science and technology,” wrote Jennifer Light, the department head for MIT’s Science, Technology and Society program, in an email to Quanta. To an extent, we can chalk up that omission to the tendency of storytellers to focus on solitary geniuses. But it also stems from tensions that remain unresolved today. +

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    + First, coders in general have seen their contributions to science minimized from the beginning. “It was seen as rote,” said Mar Hicks, a historian at the Illinois Institute of Technology. “The fact that it was associated with machines actually gave it less status, rather than more.” But beyond that, and contributing to it, many programmers in this era were women. +

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    + In addition to Hamilton and the woman who coded in MIT’s nuclear engineering department, Ellen Gille recalls a woman on an LGP-30 doing meteorology next door to Lorenz’s group. Another woman followed Gille in the job of programming for Lorenz. An analysis of official U.S. labor statistics shows that in 1960, women held 27 percent of computing and math-related jobs. +

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    + The percentage has been stuck there for a half-century. In the mid-1980s, the fraction of women pursuing bachelor’s degrees in programming even started to decline. Experts have argued over why. One idea holds that early personal computers were marketed preferentially to boys and men. Then when kids went to college, introductory classes assumed a detailed knowledge of computers going in, which alienated young women who didn’t grow up with a machine at home. Today, women programmers describe a self-perpetuating cycle where white and Asian male managers hire people who look like all the other programmers they know. Outright harassment also remains a problem. +

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    + Hamilton and Gille, however, still speak of Lorenz’s humility and mentorship in glowing terms. Before later chroniclers left them out, Lorenz thanked them in the literature in the same way he thanked Saltzman, who provided the equations Lorenz used to find his attractor. This was common at the time. Gille recalls that in all her scientific programming work, only once did someone include her as a co-author after she contributed computational work to a paper; she said she was “stunned” because of how unusual that was. +

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    + Since then, the standard for giving credit has shifted. “If you went up and down the floors of this building and told the story to my colleagues, every one of them would say that if this were going on today … they’d be a co-author!” Rothman said. “Automatically, they’d be a co-author.” +

    + +

    + Computation in science has become even more indispensable, of course. For recent breakthroughs like the first image of a black hole, the hard part was not figuring out which equations described the system, but how to leverage computers to understand the data. +

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    + Today, many programmers leave science not because their role isn’t appreciated, but because coding is better compensated in industry, said Alyssa Goodman, an astronomer at Harvard University and an expert in computing and data science. “In the 1960s, there was no such thing as a data scientist, there was no such thing as Netflix or Google or whoever, that was going to suck in these people and really, really value them,” she said. +

    +

    + Still, for coder-scientists in academic systems that measure success by paper citations, things haven’t changed all that much. “If you are a software developer who may never write a paper, you may be essential,” Goodman said. “But you’re not going to be counted that way.” +

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    + This article was reprinted on Wired.com. +

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    Tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, + quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo + consequat.

    + +

    Duis aute irure dolor in reprehenderit in voluptate velit esse + cillum dolore eu fugiat nulla pariatur. + + Excepteur sint occaecat cupidatat non + proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

    +
    +
    + + diff --git a/resources/tests/readability/reordering-paragraphs/expected.html b/resources/tests/readability/reordering-paragraphs/expected.html new file mode 100644 index 0000000..b09abcb --- /dev/null +++ b/resources/tests/readability/reordering-paragraphs/expected.html @@ -0,0 +1,28 @@ +
    +
    +

    Regarding item# 11111, under sufficiently extreme conditions, quarks may + become deconfined and exist as free particles. In the course of asymptotic + freedom, the strong interaction becomes weaker at higher temperatures. + Eventually, color confinement would be lost and an extremely hot plasma + of freely moving quarks and gluons would be formed. This theoretical phase + of matter is called quark-gluon plasma.[81] The exact conditions needed + to give rise to this state are unknown and have been the subject of a great + deal of speculation and experimentation.

    +

    Regarding item# 22222, under sufficiently extreme conditions, quarks may + become deconfined and exist as free particles. In the course of asymptotic + freedom, the strong interaction becomes weaker at higher temperatures. + Eventually, color confinement would be lost and an extremely hot plasma + of freely moving quarks and gluons would be formed. This theoretical phase + of matter is called quark-gluon plasma.[81] The exact conditions needed + to give rise to this state are unknown and have been the subject of a great + deal of speculation and experimentation.

    +

    Regarding item# 33333, under sufficiently extreme conditions, quarks may + become deconfined and exist as free particles. In the course of asymptotic + freedom, the strong interaction becomes weaker at higher temperatures. + Eventually, color confinement would be lost and an extremely hot plasma + of freely moving quarks and gluons would be formed. This theoretical phase + of matter is called quark-gluon plasma.[81] The exact conditions needed + to give rise to this state are unknown and have been the subject of a great + deal of speculation and experimentation.

    +
    +
    diff --git a/resources/tests/readability/reordering-paragraphs/source.html b/resources/tests/readability/reordering-paragraphs/source.html new file mode 100644 index 0000000..d081a94 --- /dev/null +++ b/resources/tests/readability/reordering-paragraphs/source.html @@ -0,0 +1,34 @@ + + + + + +
    +

    Regarding item# 11111, under sufficiently extreme conditions, quarks may + become deconfined and exist as free particles. In the course of asymptotic + freedom, the strong interaction becomes weaker at higher temperatures. + Eventually, color confinement would be lost and an extremely hot plasma + of freely moving quarks and gluons would be formed. This theoretical phase + of matter is called quark-gluon plasma.[81] The exact conditions needed + to give rise to this state are unknown and have been the subject of a great + deal of speculation and experimentation.

    +

    Regarding item# 22222, under sufficiently extreme conditions, quarks may + become deconfined and exist as free particles. In the course of asymptotic + freedom, the strong interaction becomes weaker at higher temperatures. + Eventually, color confinement would be lost and an extremely hot plasma + of freely moving quarks and gluons would be formed. This theoretical phase + of matter is called quark-gluon plasma.[81] The exact conditions needed + to give rise to this state are unknown and have been the subject of a great + deal of speculation and experimentation.

    +

    Regarding item# 33333, under sufficiently extreme conditions, quarks may + become deconfined and exist as free particles. In the course of asymptotic + freedom, the strong interaction becomes weaker at higher temperatures. + Eventually, color confinement would be lost and an extremely hot plasma + of freely moving quarks and gluons would be formed. This theoretical phase + of matter is called quark-gluon plasma.[81] The exact conditions needed + to give rise to this state are unknown and have been the subject of a great + deal of speculation and experimentation.

    +
    + + + \ No newline at end of file diff --git a/resources/tests/readability/replace-font-tags/source.html b/resources/tests/readability/replace-font-tags/source.html new file mode 100644 index 0000000..d47851d --- /dev/null +++ b/resources/tests/readability/replace-font-tags/source.html @@ -0,0 +1,28 @@ + + + + + Replace font tags test + + +
    +

    Lorem

    +
    + Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod + tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, + quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo + consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse + cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non + proident, sunt in culpa qui officia deserunt mollit anim id est laborum. +
    +

    Foo

    +
    + Tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, + quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo + consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse + cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non + proident, sunt in culpa qui officia deserunt mollit anim id est laborum. +
    +
    + + diff --git a/src/full_text_parser/readability/tests.rs b/src/full_text_parser/readability/tests.rs index 160184b..73b374a 100644 --- a/src/full_text_parser/readability/tests.rs +++ b/src/full_text_parser/readability/tests.rs @@ -397,6 +397,46 @@ async fn nytimes_5() { run_test("nytimes-5").await } +#[tokio::test] +async fn pixnet() { + run_test("pixnet").await +} + +// #[tokio::test] +// async fn qq() { +// run_test("qq").await +// } + +#[tokio::test] +async fn quanta_1() { + run_test("quanta-1").await +} + +#[tokio::test] +async fn remove_aria_hidden() { + run_test("remove-aria-hidden").await +} + +#[tokio::test] +async fn remove_extra_paragraphs() { + run_test("remove-extra-paragraphs").await +} + +#[tokio::test] +async fn reordering_paragraphs() { + run_test("reordering-paragraphs").await +} + +#[tokio::test] +async fn remove_script_tags() { + run_test("remove-script-tags").await +} + +// #[tokio::test] +// async fn replace_font_tags() { +// run_test("replace-font-tags").await +// } + #[tokio::test] async fn webmd_1() { run_test("webmd-1").await