During the previous years, the demand for producing the quality of software has been quickly increased. In this paper, Bayesian Regularization (BR) technique has been used for finding the software faults before the testing process. This technique helps us to reduce the cost of software testing which reduces the cost of the software project. The basic purpose of BR technique is to minimizes a combination of squared errors and weights, and then determine the correct combination so as to produce an efficient network.BR Technique algorithm based neural network tool is used for finding the results on the given public dataset. The accuracy of BR algorithm based neural network has been compared with Levenberg-Marquardt(LM) algorithm and Back Propagation (BPA) algorithm for finding the software defects. Our results signify that the software fault prediction model using BR technique provide better accuracy than Levenberg-Marquardt (LM) algorithm and Back Propagation (BPA) algorithm.
Speech recognition is a vast research field for researchers in modern era. Earlier, the human language was processed by the computer system for speech recognition. Thus, the main objective is to develop recognition system which improves human to human communication by enabling human-machine communication by processing of text or speech. Various applications of speech recognition systems are present and these all includes various research challenges. A critical machine learning based review is defined which addresses the various challenging tasks of speech recognition system in NLP. In the existing systems, the recognition rate is very less and the noise ration during the recognition process creates a problem. Thus in this literature review we try to address such kind of challenges and provides a solution to work further in future.
Privacy Security of data in Cloud Storage is one of the main issues. Many Frameworks and Technologies are used to preserve data security in cloud storage.[1] Proposes a framework which includes the design of data organization structure, the generation and management of keys, the treatment of change of user's access right and dynamic operations of data, and the interaction between participants. It also design an interactive protocol and an extirpation-based key derivation algorithm, which are combined with lazy revocation, it uses multi-tree structure and symmetric encryption to form a privacy-preserving, efficient framework for cloud storage. [2] Proposes a framework which design a privacy-preserving cloud storage framework in which he designed an interaction protocol among participants, use key derivation algorithm to generate and manage keys, use both symmetric and asymmetric encryption to hide the sensitive data of users, and apply Bloom filter for cipher text retrieval. A system based on this framework is realized. This paper analyzes both the frameworks in terms of the feasibility of the frameworks, running overhead of the system and the privacy security of the frameworks.
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