Determining the heat capacity of honey at home
The average heat capacity of a substance can be determined at home by determining the rate of heat
transfer from a hot plate at a fixed setting to a quantity of substance with known heat capacity e.g.
water which has a heat capacity of 4190 J/kg/K, where the same (cooled) container is used to make
the measurements for both substances.
For this, your final home experiment which will contribute to your final report you are to
design and carry out an experiment at home to determine the heat capacity of honey at home.
Your equipment list should include:
300-500 g of honey
500 g of water
Small cooking pot (1 litre)
Stopwatch App
Candy Thermometer (check its temperature range first)
House stove (if you do not have
one, visit a friend)
Digital Scales
Candy thermometers are designed to click onto the side of a saucepan as shown. They should not
touch the bottom of the pan. Your liquid should stay just on the bottom mark (usually 30oC) so you
can see the scale (weigh your liquid). The lowest value on a candy is 30oC so you will not be able to
measure below this temperature. Does this matter? What do you need to measure for this experiment
to work out heat transfer and heat capacity?
Useful formula: Rate of heat transfer, H in J/s, is given by:
dT
H mc
dt
Where m is the mass of substance in kg, c the heat capacity in J/kg/C, T the temperature in degrees
celcius, and t, time in seconds.
Compare your specific heat to the accepted values for honey: 2268 J/kg/K – 2520 J/kg/K. How is
specific heat normally measured?
Sample Solution
i. How do these technologies work?
As listed above, there exists a long list of methods and algorithms that can be used for facial recognition. Four of them are used frequently and are most known in the literature, i.e. Eigenface Method, Correlation Method, Fisherface Method and the Linear Subspaces Method. But how do these facial recognition work? Because of word limitations, only one of those four facial recognition techniques, i.e The Eigenface Method, will be discussed. Hopefully this will give an general idea of how facial recognition works and can be used.
One of the major difficulties of facial recognition, is that you have to cope with the fact that a person’s appearance may change, such that the two images that are being compared differentiate too much from each other. Also environmental changes in pictures, like lightning, have to be taken into account, in order to have successful facial recognition. Thus from a picture of a face, as well as from a live face, some yet more abstract visual representation must be established which can mediate recognition despite the fact that in real life the same face will hardly ever form an identical image on successive occasions. Our ability to do this shows that we can derive structural codes for faces, which capture those aspects of the structure of a face essential to distinguish it from other faces[6].
One of the four most famous facial recognition methods is the Eigenface Method. This method focuses on the aspects of the face stimulus that are important for identification. This is done by decoding face images into significant local and global ‘features’[24]. Such features may or may not be directly related to our intuitive notion of face features such as the eyes, nose, lips and hair. Scientists Matthew Turk and Alex Pentland [24] developed a computer system for the eigenface approach w