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    毫無疑問,人工智能技術給人們的生活帶來了便利與進步,但由其引發的諸多倫理問題也給人類社會帶來了不同程度的影響。以對勞動力市場的影響為例,機器人取代流水線工人、聊天機器取代人工客服、虛擬主播取代主持人、快譯機取代翻譯人,人工智能技術的發展對傳統就業崗位的影響日益明顯。根據《中國青年報》的一則報道[2],中國廣州東莞的松山湖長盈精密技術有限公司正常運轉需要650名員工的辛勤勞作,如今工廠轉型為“無人工廠”,有60條機器人手臂晝夜不停地工作在10條生產線上,員工只剩下60人,其中3人負責檢查和監控生產線,其他人負責監控電腦控制系統,實現了用機器取代90%的人力資源,從而提高了250%的生產效率、降低了80%的缺陷率。類似這樣的“無人工廠”,在各個行業都開始發力。根據《半月談》2019年9月10日的一則報道[3],記者在義烏申通分撥中心看到,平臺上設有240個方形分揀口,每個分揀口都代表一個城市或轉運中心,700個“小黃人”分揀機器人開始工作后滿場奔忙,但精準率能達到99.9%以上。據申通統計,700個“小黃人”一天工作10小時,能夠分揀20萬件快遞,大大減少了人工作業。2017年,麥肯錫全球研究所(The McKinsey Global Institute)的一份報告《Jobs lost, jobs gained: Workforce transitions in a time of automation》[4]預測,到2030年全球60%的工作崗位中,至少有30%工作可以實現自動化,這意味著可能影響到8億個工作職位。
    There is no doubt that the AI technology has made our life more convenient and progressive, but it has incurred many ethical problems that have impact on human society to various degrees. Take its impact on the labor market as an example, with robots replacing workers on the assembly line, chatbots replacing customer support staff, virtual anchors replacing human hosts, and quick machine translation replacing human translation, the advancing AI technology is exerting an increasingly significant influence on conventional jobs. A report from China Youth Daily[2] said that Everwin Precision Technology Co, Ltd., located around the Songshan Lake in Dongguan, Guangdong, used to provide jobs for 650 industrious workers to maintain its smooth operation, but now the plant is almost an “unmanned factory”, with 60 robot arms working around the clock on 10 production lines and only 60 staff left out there — three in charge of inspecting and monitoring the production lines, and the rest responsible for monitoring the computer panel systems. With robots in place of 90% workers, the AI technology has improved its productivity by 250%, and reduced its defect rate by 80%. These “unmanned factories” have started to play a strong role in various industries. On September 10, 2019, a news story from China Biweekly Comment[3] said that at a distribution center of STO Express in Yiwu, Zhejiang, the distribution platform is equipped with 240 square sorting slots, each of which represents a city or a transfer center, where 700 “Minions” sorting robots are busy running and working out there, achieving an accuracy of over 99.9%. Statistics of STO Express show that the 700 “Minions” can sort out 200,000 packages in 10 hours every day, greatly reducing manual work. In 2017, the McKinsey Global Institute predicted in a report titled Jobs lost, jobs gained: Workforce transitions in a time of automation [4] that by 2030, among 60% jobs around the globe, at least 30% can be robotized, threatening 800 million jobs.
    砂卵石地層透水性強,顆粒間級配較差,粘聚力弱,在降水作用下顆粒易流失,地表產生固結沉降。采用DEM-CFD耦合計算方法,分析降水過程中顆粒流失情況。FHY基坑基巖為中風化泥巖,滲透性低,降水對基巖影響極小,對此僅取砂卵石地層及黏土地層建模。砂卵石地層幾乎沒有粘聚力和抗拉破壞強度采用線彈性模型,黏土采用平行粘結模型。 數值模型長30m,高15m,粉質粘土厚度5m,砂卵石層厚度10m,地下水埋深為5m。模型中下部設置降水井,降水井內放置濾料,近似模擬濾料的過濾作用。砂卵石地層細顆粒的流失與降水速度和濾料有關,該計算模擬了管井內填充濾料為4mm、8mm、12mm和無濾料,每種濾料粒徑下又設置了4m3/h、6m3/h、8 m3/h、10m3/h這四種不同的降水量,共20種工況。
    The sandy cobble stratum has strong water permeability, poor particle size distribution and weak particle cohesion. As a result, the particles are easily washed away under the action of dewatering, causing consolidation settlement. The DEM-CFD coupling method was used to analyze the loss of particles during dewatering. The bedrock of the FHY foundation pit was moderately weathered mudstone with low permeability, and dewatering had little impact on the bedrock, so the numerical model was built based on only the sandy cobble stratum and the clay stratum. The particle sizes of sand pebble and clay were 0.001-0.6m and 0.02-0.13m. The linear elastic model was used for particle-particle contact model in the sandy cobble stratum that had practically zero cohesion and zero tensile strength, while the parallel-bond model was adopted for the clay stratum. The numerical model was 30?m long and 15?m high, where the silty clay was 5?m thick, the sandy cobble stratum 10?m thick and the groundwater 5?m deep (Figure 9). A water outlet was reserved at the centre of the bottom of the fluid model to simulate the dewatering well, and filter media were generated near the dewatering well. The loss of fine particles in the sandy cobble stratum was related to the dewatering rate and filter media. The calculation model simulated the tube well filled with filter media with grain sizes of 0?mm, 4?mm, 8?mm, 12?mm. The dewatering rates for each filter media were 4?m3/h, 6?m3/h, 8?m3/h and 10?m3/h. In total, 20 working conditions were simulated.
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