1,727,414 research outputs found
Design of Michelin calender 800 quick pace change assembly
Full text linkThesis (M.S.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1996.Includes bibliographical references (leaf 95).by Jayakumar Gurusamy.M.S
Inventory system for FCSIT / Jayakumar Kunju
Full text linkThis e-inventory system is an Internet based system developed. As a web based application, e-inventory system's client works in tandem with the server, operating over the internet. The server side contains all the related operating applications, and data storage. Web browser is involved to retrieve information from the web server. It is a centralized kiosk for the retrieval and collection of information.There are many example or current inventory system either is online or stand-alone system that have been referred during the system design. Furthermore, system functional requirements of this project include login function, output displaying function, search fun functions ads, edit or delete function, output displaying function and user manual. Next, the data flow diagrams is used to illustrate data sources,
destinations, flows, store, and transformation of the system. The Online system consist of a few separate module, this include system user architecture design module, authentications module, user management module and product transaction module. For the system development, Windows 2000 will be used as application platform, Microsoft Access server as the database server ASP and ASP. Net as the web page technology, JavaScript and VB Scripts as the scripting language and the IIS as the web server. Moreover, the waterfall model with prototype is the selected methodology to develop the e-inventory system
Three Essays on Indian Economy
Full text linkThe research work focuses on the applicability of parametric approaches such as Time-Varying and Sign Restricted Vector Auto Regression (VAR), Structural Vector Autoregression (SVAR) models for some problems faced by the Indian Economy. The study is based on three issues, which are categorised as the following three chapters 1. Analysing Inflation in India using Time-Varying SVAR Model 2. Twin Deficit Hypothesis and its Relevance in India: Time-Varying VAR Approach 3. Oil Shocks and Its Impact On Indian Economy: Sign Restricted SVAR Model. In the first chapter using Time-Varying SVAR Impulse Response Functions (IRFs), it is checked whether crude oil price shock has brought about changes in the inflation (p), output growth (x) and interest rate (i) of Indian economy. It is based on the procedure followed by Nakajima (2011). The results indicate that sudden oil price shock is followed by an increase in inflation. The increase in inflation is later accompanied by a declinein output growth, to which Reserve Bank of India (RBI) responds by raising the interest rate, thereby making the inflation move towards the stability level as specified by the RBI i.e. (5-5.5%). In the second chapter, Time-Varying Vector Autoregression (VAR) has been employed to prove the existence of twin deficit hypothesis in India following the methodology by Nakajima (2011). The budget deficit and trade deficit are interrelated through the phenomena termed as twin deficit hypothesis. To understand the phenomena, the study has tried to understand the impact of the fiscal shock on macro variables in India namely current account deficit as a percentage of GDP, Real effective exchange rate of India and real GDP of India. The impact of the fiscal shock on macro variables is studied, as maintaining a sustainable level of budget deficit is considered to be a necessary condition for the maintenance of a comfortable level of current account balance. The results indicate that fiscal deficit and current account deficit are related in the Indian context, and twin deficit hypothesis holds. In the third chapter, a Sign Restricted SVARModel has been employed to understand the macroeconomic impact of oil shocks on the Indian economy. Three types of shocks have been identified using sign restrictions, namely an Oil Supply Shock, Oil Demand Shock created by Global economic activity and an Oil-specific Demand Shock following the identification procedure of Baumister, Peersman and Van Robays (2012). The results indicate that output growth and inflation react very differently to the fluctuations in oil prices as the type of the shock is concerned
Adaptive batching of streams to enhance throughput and to support dynamic load balancing
Full text linkAs data permeates all disciplines, the role of big data becomes increasingly important. Sensors, IoT devices, social networks, and online transactions are all generating data that can be monitored constantly to enable a business to identify opportunity to enhance customer service and increase revenue. This need for real-time processing of big data has led to the development of frameworks for distributed stream processing in clusters. It is important for such frameworks to be resilient against variable operating conditions such as server load variation, changes in data ingestion rates, and workload characteristics. In this thesis, we explore the effects of the batch size on the performance of streaming workloads by developing an adaptive batching framework and building load-balancing algorithms on top of this framework. We explore the idea of using a combination of adaptive batching of tuples and dynamic tuple dispatching to improve the throughput and load-distribution of the workload. We show through experiments that the system is able to be resilient and robust under varying operating conditions.Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2017-02-28 without embargo termsThe student, Anirudh Jayakumar, accepted the attached license on 2016-12-06 at 10:59.The student, Anirudh Jayakumar, submitted this Thesis for approval on 2016-12-06 at 11:02.This Thesis was approved for publication on 2016-12-06 at 14:08.DSpace SAF Submission Ingestion Package generated from Vireo submission #10446 on 2017-02-28 at 14:55:31Made available in DSpace on 2017-03-01T15:49:29Z (GMT). No. of bitstreams: 2
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Previous issue date: 2016-12-0
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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