Abstract: This paper proposes a Fuzzy Expert System design to
determine the wearing properties of nitrided and non nitrided steel.
The proposed Fuzzy Expert System approach helps the user and the
manufacturer to forecast the wearing properties of nitrided and non
nitrided steel under specified laboratory conditions. Surfaces of the
engineering components are often nitrided for improving wear,
corosion, fatigue specifications. A major property of nitriding
process is reducing distortion and wearing of the metalic alloys. A
Fuzzy Expert System was developed for determining the wearing and
durability properties of nitrided and non nitrided steels that were
tested under different loads and different sliding speeds in the
laboratory conditions.
Abstract: In this report we present a rule-based approach to
detect anomalous telephone calls. The method described here uses
subscriber usage CDR (call detail record) data sampled over two
observation periods: study period and test period. The study period
contains call records of customers- non-anomalous behaviour.
Customers are first grouped according to their similar usage
behaviour (like, average number of local calls per week, etc). For
customers in each group, we develop a probabilistic model to describe
their usage. Next, we use maximum likelihood estimation (MLE) to
estimate the parameters of the calling behaviour. Then we determine
thresholds by calculating acceptable change within a group. MLE is
used on the data in the test period to estimate the parameters of the
calling behaviour. These parameters are compared against thresholds.
Any deviation beyond the threshold is used to raise an alarm. This
method has the advantage of identifying local anomalies as compared
to techniques which identify global anomalies. The method is tested
for 90 days of study data and 10 days of test data of telecom
customers. For medium to large deviations in the data in test window,
the method is able to identify 90% of anomalous usage with less than
1% false alarm rate.