大学MOOC 学术英语表达与沟通(武汉理工大学)1461065162 最新慕课完整章节测试答案
Chapter1Pronunciation1AcademicWriting1
test1
1、单选题：
An abstract includes the statements of _____.
选项：
A: problems, approach, conclusion and significance
B: problems, topic, conclusion and discussion
C: problems, topic, approach, conclusion and significance
D: problems, topic, arrangement, discussion and significance
答案: 【 problems, topic, approach, conclusion and significance】
2、单选题：
The act of joining the neighboring sounds together is _____.
选项：
A: liaison
B: assimilation
C: incomplete plosive
D: open syllable
答案: 【 liaison】
3、单选题：
IMRaD means______.
选项：
A: introduction, method& materials, results, discussion
B: introduction, method, results, abstract, discussion
C: introduction, materials, results, abstract, discussion
D: index, materials, results, abstract, discussion
答案: 【 introduction, method& materials, results, discussion】
4、单选题：
In formal writings, there are more______.
选项：
A: contracted structures
B: conversational structures
C: nominal structures
D: first person pronouns
答案: 【 nominal structures】
5、单选题：
Which of the following title is good?
选项：
A: Radioactive Material Transport is Effective and Safe with FIQ System
B: The Study of Risk Assessment of External Corrosion of Pipelines
C: Bats blamed by scientist for virus transmission
D: Can AI be used in Cranial Nerve Damage Repair?
答案: 【 Bats blamed by scientist for virus transmission】
6、单选题：
Which name is not right in spelling?
选项：
A: Zhuge Liang
B: Nan Ren Dong
C: Dongguo Xiansheng
D: ZHONG Nanshan
答案: 【 Nan Ren Dong】
7、单选题：
Read the following sentence carefully and tell the sentence is an effective sentence or not. As we know, it is long history of the examination system in our country.
选项：
A: Yes
B: No
C: Unknown
D: Acceptable
答案: 【 No】
8、单选题：
Read the following ABSTRACT and identify the sentences in the abstract that correspond with the elements outlined below. Use the number before each sentence to stand for the sentence instead of copying the whole abstract while analyzing it. ①Transforming the manufacturing environment from manually operated production units to unsupervised robotic machining centers requires a presence of reliable in-process monitoring system. ②In this paper, we demonstrate a technique for automatic endpoint detection of weld seam removal in a robotic abrasive belt grinding process with the help of a vision system using deep learning. ③The paper presents the results of the first investigative stage of semantic segmentation of weld seam removal states using encoder-decoder conventional neural networks (EDCNN). ④An experimental investigation using four different weld seam states on mild steel work coupon are trained using the VGG-l6 network based on encoder-decoder architecture. ⑤The results demonstrate the potential of the developed vision based methodology as a tool for endpoint prediction of the weld seam removal in real time during a compliant abrasive belt grinding process. ⑥The prediction system based on semantic segmentation is able to monitor