R. Vasantha Kumari

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Multi-item inventory model for deteriorating items with stock dependent demand under two-warehouse system is developed in fuzzy environment (purchase cost, investment amount and storehouse capacity are imprecise ) under inflation and time value of money. For display and storage, the retailers hire one warehouse of finite capacity at market place, treated as(More)
It is proposed to have a study on the diagnosis of cancer using neural network approach engaging cloud computing. Cloud computing facilitates data protection, privacy and medical record access. The present paper focuses on cloud computing services extended to medical diagnosis of cancer as well as selection of therapeutic strategies. A neural network judged(More)
In this research work we developed a novel algorithm that can generate a narrative report of cricketing domain based on statistical data information extracted from raw values of match data.The algorithm is successful able to match quality standards of creating reporting with fair amount of increase in information gain. Key Words-Natural language processing(More)
Telugu is the third largest language spoken by nearly 80 million native speakers. Telugu is one of four classical languages in India. Telugu is the official language for the state of Andhra Pradesh. Each telugu word ends with vowels. So there is a scope for research about Telugu vowels recognition rate. The application of machine learning techniques to(More)
In this paper an efficient implementation of speech to text converter for mobile application is presented. The prime motive of this work is to formulate a system which would give optimum performance in terms of complexity, accuracy, delay and memory requirements for mobile environment. The speech to text converter consists of two stages namely front-end(More)
In this paper a novel approach for implementing isolated speech recognition is studied. While most of the literature on speech recognition (SR) is based on hidden Markov model (HMM), the present system is implemented by Radial Basis Function type neural network. The two phases of training and testing in a Radial Basis Function type neural network has been(More)
The method of self-organizing maps (SOM) is a method of exploratory data analysis used for clustering and projecting multi-dimensional data into a lower-dimensional space to reveal hidden structure of the data. The Self-Organizing Feature Maps (SOFMs) [11] is a class of neural networks capable of recognizing the main features of the data they are trained(More)
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