The Division of Engineering and Applied Sciences (the buildings in this photograph) has significantly expanded its Computer Systems work in recent years. However, there has been a noticeable lack of quality work on Rodent Performance Evaluation. This study is a first attempt to remedy this deficiency.

We chose gray squirrels as our subject of study because of their abundance in the immediate surroundings of the Aiken Computation Lab, with many large oak trees nearby.

The primary investigators in this study are Yasuhiro Endo (left) and Nikolas Gloy (right), shown here in front of the former high-performance vehicle of Professor J. Bradley Chen.

Early attempts to measure squirrel performance involved chasing them around and trying to guard all nearby trees by a sufficient number of researchers, but these efforts were mostly fruitless.

Another method involved building primitive traps from cardboard boxes and 10baseT Ethernet cables, but these cables either attracted unwanted attention or got lost high up in trees.

Some insight was gained, however, into ways of focusing squirrels attention on small objects which are dropping on the ground, such as acorns. This led to the formulation of Gloy's First Conjecture that a squirrel will always give up one acorn if another one is thrown nearby.

This led to our current approach to measure the reaction of squirrels to a peanut tied to a long piece of string. The low end of the performance scale includes not running away from a peanut thrown at the subject, and following it as it is dragged through the grass. The aiming accuracy of the trowing process can be greatly increased by attaching a key to the string about 3 inches from the end.

The next point on the performance scale is the willingness to grab the peanut and hold on to it under moderate tension.

A smarter squirrel will discover after a while that it is better to bite through the string than simply pull on the peanut. This distinguishing tactic leads us to believe that the average squirrel performance in Texas is much higher than in Massachusetts.

Prolonged lack of success in consuming the peanut can lead to frustration, as shown on the face of the squirrel in this picture. Note that in this experiment, a magnet found on a mouse cable was used as a weight to improve throwing precision, rather than a key as mentioned earlier.

Because of the complexity of the resulting photographs, with uneven focus across the field of depth, these images are now widely used in computer graphics teaching and research. Professor Steven J. Gortler is considered the leading authority in this subfield.

Another attempt a biting through the string. The low-quality string used in this phase of our experiments made this a little too easy.

Another question that has been puzzling researchers for years is whether it is possible to make a squirrel fall on its back by skillful manipulation of a bait suspended above its head. The theory was that this could be achieved if this bait was moved in a straight line over the center of gravity of the squirrel towards its back.

After many hours of experimentation, we were able to disprove this theory. More research is needed to determine if squirrels get dizzy from prolonged spinning around.

The highest mark on the squirrel performance scale is achieved when a subject is willing to hold on to the peanut or string while it is being lifted off the ground. This state only lasts for a very short time and is very difficult to photograph.

Liftoff !!!