  A method for selecting events with densely populated narrow regions or spikes
in a given data sample is discussed. Applying this method to 200 A GeV/c
32S-AgBr and 32S-Gold collision data, a few events having "hot regions" are
chosen for further analysis. The finding reveals that a systematic study of
particle density fluctuations, if carried out in terms of scaled factorial
moments, and the results are compared with those for the analysis of
correlation free Monte Carlo events, would be useful in identifying events with
large dynamical fluctuations. Formation of clusters or jet-like structure in
multihadronic final states in the selected spiky events is also looked into and
compared with the predictions of AMPT and independent emission hypothesis
models by carrying out Monte Carlo simulation. The findings suggest that
clustering or jet-like algorithm adopted in the present study may also serve as
an important tool for triggering different classes of events.
