Abstract-A large number of gray shades can be displayed in rms responding displays by using integer wavelets. The technique is demonstrated by displaying 64 gray shades in a twisted nematic liquid crystal display. We have reduced the hardware complexity of the display drivers by adding a few analog multiplexers that are common to a large number of stages (one for each output) in the drivers. A simple controller was implemented in a low cost complex programmable logic device.Index Terms-Gray shades, liquid crystal displays (LCDs), matrix addressing, multi-line addressing (MLA), wavelets.

In recent years, the Indian economy has shown rapid growth among all other major economies. India has been tragically reviled with issues like corruption and black currency, fake money notes is additionally major issues to it, in spite of a strong security feature are endorsed by RBI to print original currency. The advancement of color printing technology helped local racketeers and foreign racketeers to print a large amount of counterfeit Indian currency notes in the market. Albeit counterfeit money is being printed with accuracy, it likely is distinguished with some effort. In this paper, the proposed model efficiently detect the counterfeit Indian currency notes by adapting three-layered Deep Convolutional Neural Network (Deep ConvNet), and achieved an accuracy of 96.6%.

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SPR is a software engineering process that improves organizational efficiency in responding to quality outcome challenges, change management and productivity improvement, product quality and competitive advantage. To include improvements to the required considerations and agreements of SEM, SPR, implements, inherits and explores the architecture of procedure change. Machine learning is a key part of SPR in software development organizations. The objective of this paper is to integrate automation technology such as ML into the SDLC of software product development and to increase the conceptual focus on its life cycle development and highlight ML methods in SPM, and how to execute ML in SEM methods. ML algorithms for empirical analysis and discussion of the specific performance and reuse of tasks that we have attempted to achieve in SEM. An observed study of software methods involves the control system of self determining software implementation. In the current period, ML gives better validity in few SEM areas. The main aim of this research is the practical as well as systematic study and also literature survey to advance the wanted standard software, between their qualified evaluation of existing procedures and their carry for SQE.

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