The globe valve has a bulbous body, housing a valve seat and screw down plug or disc arranged at right angles to the axis of the pipeAccording to the above sentence, which of the following statements is not true?A.The profile of the valve is like a globeB

题目

The globe valve has a bulbous body, housing a valve seat and screw down plug or disc arranged at right angles to the axis of the pipeAccording to the above sentence, which of the following statements is not true?

A.The profile of the valve is like a globe

B.The valve seat is set into the bulbous body

C.The plug or disc of the valve is made vertical to the axis of the pipe

D.The valve seat is located at right side of the plug or disc


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  • 第1题:

    The Master to prosecute all voyages with the utmost__________ and to render customary assistance with the Vessel's Crew.

    A.fastness

    B.speeding

    C.swiftness

    D.despatch


    正确答案:。

  • 第2题:

    1、哲学家就餐问题的解决方案如下: semephore *chopstick[5]; semaphore *seat; 哲学家 i: …… P(seat); P(chopStick[i]); P(chopStick[(i + 1) % 5]); 吃饭 V(chopStick[i]); V(chopStick[(i + 1) % 5]); V(seat); 其中,信号量seat的初值为()。

    A.0

    B.1

    C.4

    D.5


    C

  • 第3题:

    哲学家就餐问题的解决方案如下: semephore *chopstick[5]; semaphore *seat; 哲学家 i: …… P(seat); P(chopStick[i]); P(chopStick[(i + 1) % 5]); 吃饭 V(chopStick[i]); V(chopStick[(i + 1) % 5]); V(seat); 其中,信号量seat的初值为()。

    A.0

    B.1

    C.4

    D.5


    C

  • 第4题:


    请在第_____处填上正确答案。

    A.exit
    B.window
    C.gate
    D.seat

    答案:A
    解析:
    尽量不要坐在出口处的位置。

  • 第5题:

    下面程序段的执行结果为______。 import tensorflow as tf boston_housing= tf.keras.datasets.boston_housing (train_x,train_y),(test_x,test_y)= boston_housing.load_data(test_split=0.1) print("Training set:", len(train_x)) print("Testing set:", len(test_x))

    A.Training set: 404 Testing set: 102

    B.Training set: 51 Testing set: 455

    C.Training set: 102 Testing set: 404

    D.Training set: 455 Testing set: 51


    程序报错

  • 第6题:

    8、下面程序段的执行结果为______。 import tensorflow as tf boston_housing= tf.keras.datasets.boston_housing (train_x,train_y),(test_x,test_y)= boston_housing.load_data(test_split=0.1) print("Training set:", len(train_x)) print("Testing set:", len(test_x))

    A.Training set: 404 Testing set: 102

    B.Training set: 51 Testing set: 455

    C.Training set: 102 Testing set: 404

    D.Training set: 455 Testing set: 51


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