An Android App to remind the Medication
Authors: P Sreedhar, M Sri Manvitha, M Venkata Surekha, T JayaVani, T Sujatha, R Vamsi Krishna
Abstract
In modern society, busy life has made people forget many things in day to day life. The elderly people and the people victims of chronicle diseases who need to take the medicines timely without missing are suffering from dementia, which is forgetting things in their daily routine. Considering this situation study has been done in this. Paper reviewing the technologies of home health care which are currently used for improving this situation by reminding the scheduled of medicine, remote monitoring and update new medicine data of patients, which can be done by prescriber through web.
A MACHINE LEARNING FRAMEWORKS TO PREDICT AND ANALYZE THE CRIMES AGAINST WOMEN HARASSMENT
Authors: M.Praveena, D.Sivaparvathi, K.Srivyshnavi, P.Lakshmiprasanna, T.Surekha, A.Bhagylakshmi
Abstract
A country’s economic growth is unfavorably influenced with the steadily expanding crimes consistently. It is quite possibly the most serious issues in our general public and decreasing the crime rates have become a critical undertaking. Consequently, recognize various elements, event relations of crimes and subsequently deciding upgraded approach to lessen crimes rates. For this a data set should be kept up with which keeps record of various crimes with subtleties identified with spot, time and nature so on for future reference. This exploration work centers around how AI calculations can be planned and dissected to diminish crime rates in India. By the methods for AI procedures, deciding the example relations among immense arrangement of information has gotten simpler. This exploration primarily relies upon giving a forecast on crime type that may happen dependent on the area where it has effectively occurred. AI has been utilized to foster a model by the utilization of preparing informational index that have gone through the interaction of information cleaning and change. Investigation of informational index alongside its qualities can be carried out with the guide of information perception. The different elements are being recognized and caught. Hazard factors are being distinguished and prescient measures are planned which help in protecting society. Different grouping calculations, improvement calculations and factual investigation has been accomplished in this work.
From Stochastic To Bit Stream Computing: Accurate Implementation of Arithmetic Circuits and Applications In Neural Networks
Authors: Dr P G KUPPUSAMY, K.LAHARI , A.MUNIESWAR, GUNDRAJU PRAFUL KUMAR RAJU, CHEMURU JYOTHIPRAKASH
Abstract
In this project, we propose a novel computing paradigm “Bit Stream Computing” that is constructed on the logic used in stochastic computing, but does not necessarily employ randomly or Binomially distributed bit streams as stochastic computing does. Any type of streams can be used either stochastic or deterministic. The proposed paradigm benefits from the area advantage of stochastic logic and the accuracy advantage of conventional binary logic. We implement accurate arithmetic multiplier and adder circuits, classified as asynchronous or synchronous; we also consider their suitability of processing successive streams. The proposed circuits are simulated using the Cadence Genus tool with TSMC 0.18µm CMOS technology. We thoroughly compare the proposed adders and multipliers with their predecessors in the literature, individually and in a neural network application. Comparisons are made in terms of area, speed, power, and accuracy. We believe that this study opens up new horizons for computing that enables us to implement much smaller yet accurate arithmetic circuits compared to the conventional binary and stochastic ones. Index Terms—Stochastic computing, bit stream computing, arithmetic circuits, neural network.