In this problem set, you will implement multidimensional scaling (MDS) from scratch. You may use standard matrix/vector libraries (e. g. numpy) but you must implement two dimensional MDS itself on your own and not use an existing software package. MDS attempts to find an arrangement of points such that the distances between points match human-judged similarities. To do this, we will minimize the stress, which is the squared difference between psychological and MDS distances:

Refrigerant-134a enters the compressor of a refrigerator as superheated vapor at 0.14 mpa and -10°c at a rate of 0.05 ka/s and leaves at 0.8 mpa and 50°c. the refrigerant is cooied in the condenser to 0.72 mpa and 26'c. it is then throttled to 0.15 mpa. sketch the t-s diagram for the system and evaluate: 6) the rate of heat removai from the refrigerated space (kw), it) the power input to the compressor (kw), ii) the isentropic efficiency of the compressor (%), and iv) the cop of the refrigerator.