Receivable Management in Non Banking Finance Companies with Special Reference to Vehicle Financing

In the absence of entry barrier or regulatory restrictions, Non Banking Financial Companies frantically grew and accessed the public deposit without any regulatory control. The deposit of NBFCs grew from Rs. 41.9 crore in 1971 to 53116.0 crore in 1997. This growth was the result of a combined effect of increase in the number of NBFCs and increase in the amount of deposits. The deposits amazed as above was invested in various assets especially that in motor vehicles by these asset financing NBFCs. Various tactics were adopted by these NBFCs and their agents for recovering the receivable outstanding from such assets. Both central government and RBI were concerned about the protection of depositors‘ interest and various committees were set up to frame a comprehensive regulation for the functioning of these NBFCs.

Integrated Environment for Launch Vehicle Telemetry Data Management

The telemetry data processing operation intended for a given mission are pre-defined by an onboard telemetry configuration, mission trajectory and overall telemetry methodology have stabilized lately for ISRO vehicles. The given problem on telemetry data processing is reduced through hierarchical problem reduction whereby the sequencing of operations evolves as the control task and operations on data as the function task. The function task Input, Output and execution criteria are captured into tables which are examined by the control task and then schedules when the function task when the criteria is being met.

Connected digit speech recognition system for Malayalam language

A connected digit speech recognition is important in many applications such as automated banking system, catalogue-dialing, automatic data entry, automated banking system, etc. This paper presents an optimum speaker-independent connected digit recognizer forMalayalam language. The system employs Perceptual Linear Predictive (PLP) cepstral coefficient for speech parameterization and continuous density Hidden Markov Model (HMM) in the recognition process. Viterbi algorithm is used for decoding. The training data base has the utterance of 21 speakers from the age group of 20 to 40 years and the sound is recorded in the normal office environment where each speaker is asked to read 20 set of continuous digits. The system obtained an accuracy of 99.5 % with the unseen data.