Volume 6 | Issue 2 |

 Abstract

Vibhajan Ka Haryana Kshetra Par Samajik, Aarthik aur Rajnaitik Parbhav

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Vibhajan Ka Haryana Kshetra Par Samajik, Aarthik aur Rajnaitik Parbhav

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Topic model, Information Filtering, Pattern Mining, Relevance Ranking, Document Clustering

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A present study was conducted to isolate, identify and characterize the E.coli bacteria from turbid water and check its antibiotic activity against Neem, Turmeric, Parijat Plant. From this plant collect plant leaf air dried and crushed it and prepaid fine powder and applies on whatsman filter paper and observes its zone of inhibition against E.Coli. Maximum zone of inhibition was seen under Neem plant contaning disc.

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E.coli, Medicinal plant, zone of inhibition.

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The present paper focuses on the financial growth, of the bank and different types of loans and advances, provided by the SCDCCB. Study is based on the secondary data collected through office records of SCDCCB, annual reports, journals and news paper. Simple statistical tools like, CAGR, Mean, Standard Deviation, and Co-efficient of Variation are used to analyze the data. The study period was from 2001-02 to 2016-17. Through selective indicators it is found that all the financial variables viz., Membership, Share Capital, Reserves, Deposits, Borrowings, Working Capital, Investments, Loans Outstanding, over dues and Profit increased during the study period.

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SCDCCB, Membership, Share Capital, Reserves, Deposits, Borrowings, Working Capital, Investment and Profit

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Twitter has become one of the most important channels of communication with its ability to provide the latest and latest information. Given the extensive use of Twitter as a source of information, touching an interesting tweet for users among a bunch of tweets is a challenge. A huge amount of tweets sent per day per hundred million users, information overload is inevitable. To extract the high-volume information from different tweets, Named Entity Recognition, methods on formal texts. However many applications in information retrieval and NLP ie .natural language processing suffers from the noisy and short nature of tweets. In this paper, we propose a framework which first of all collect the live tweet then Named Entity Recognition get performed on it by using Stanford NER also System Finds its Global and Local Presence and accordingly Segmentation get performed.

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Twitter stream, named entity recognition, Global and Local context, Wikipedia, W3C, Stanford NLP, Tweet Segmentation.

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WhatsApp mobile app messenger is conceivably the most popular app used on all smartphones, tablets by all age of peoples. Billion number of peoples worldwide used Whatsapp for free messaging, calling, and media sharing to another people. Here In this research paper, I analyze the WhatsApp messaging platform and glossographer its security architecture along with a focus on its privacy and preservation.

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Security, Whatsapp.

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Evolution of data communications in the early days was mainly numerical and textual form. Many other forms of data: voice, music, speech, images, computer graphics, etc as specified mostly in the form of electrical or electronic signals. A Signal is a function that conveys information. The concept of digital image processing was introduced relatively late in computer history after the arrival of the first graphical operating systems. More ever, digital image processing requires the most careful optimizations especially for real time applications. Transfer of the messages as signals through electronic media: telegraphs, telephones, television, radar, etc. may be affected by the systems used to acquire, transmit, or process them. Also these systems are imperfect and introduce noise, distortion, or other artifacts leading to necessity of the signal processing. Accordingly, we specifically introduce the information content into the signal to extract it out later by encoding natural phenomena (audio signal, acquired image, etc.), but also generated from scratch (speech generation, computer generated music, computer graphics). Ofllate these technologies are merged together by acquiring a natural signal, processing it, and then transmitting it in some electronic form. This form is called Digital Image Processing. Computer vision aims to duplicate the effect of human vision by electronically perceiving and understanding an image. Incurring an enormous loss of information in due processing. In order to simplify the task of computer vision processing, two levels are usually distinguished viz: Low-level image processing and High-level image processing. Low level images processing methods usually use very little knowledge about the content of image. In the case of the later, it is usually provided by high-level algorithms. Low level methods often include image compression, pre-processing methods for noise filtering, edge extraction, image sharpening and boundary detection for image classification and analysis. High-level image processing is based on knowledge, goals, and plans of how to achieve those goals, and artificial intelligence methods are widely applicable. In this thesis low level image processing methods have been studied for image segmentation and classification of images.

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Helly-Property, Segmentation, Texture model, Neighborhood Spanning Tree, BRF, Markov-Chain-Rule, Edge-Flow, Fuzzy-Logic and Boundary MRF model

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Oozie is widely used in several large production clusters across major enterprises to schedule Hadoop jobs. It simplifies the process of creating workflows and managing coordination among jobs. Oozie offers the ability to combine multiple jobs sequentially into one logical unit of work. An Oozie workflow is a collection of actions arranged in a directed acyclic graph (DAG).Pig is an abstraction over Map Reduce. It is a tool/platform which is used to analyse larger sets of data representing them as data flows. Pig is generally used with Hadoop; we can perform all data manipulation operations in Hadoop using Pig. The purpose of this is to provide automation through Oozie where large sets of data are analysed using Pig queries thereby reducing the time complexity.

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Hadoop, Apache Oozie, Map Reduce, Apache Pig.

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The use of technology in supply chain is considered as a prerequisite for the effective control of today's highly competitive marketplace. Modern technologies help to create better visibility within supply chain, reduce operational costs and also enhance customer satisfaction and retention. Despite the acknowledged importance of technology in supply chain management (SCM), the use is limited. Organizations are skeptical for the investment in technology. Based on empirical data from twenty four industrial and service companies, this paper classifies the areas where companies are using technology or intend to use in future and their short term objectives for this Performance Company is looking for. Data collected from Mumbai with 24 respondents of supply chain professionals has been taken for study. Finding of the research are company is selective in technology but planning to implement advance technology in future. The objective is advancement of technology available with cost reduction, delivery time, integrate functions

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Acceptance and Adoption of the Technology in Supply Chain

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WOSAF is a new system implemented in a smart gadget and as a mobile app for the women in the society. The device mainly consists of two buttons, one is to connect with the nearby police station through the developed app. The another is provided to contact the nearby hospital in case of emergency. The information are send through the app. On both the cases, the alert will be send to the selected contacts which are saved in the app. The WiFi connectivity provided on the device helps the button signal to connect with the app developed in the android phone. The above features are implemented in the hardware device too. The main features provided in the system are one time registration, police service, hospital service, snapshot, accelerometer and panic mode.

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Mobile app, portable device, safety, security,accelerometer

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