Browsing Computer Science and Automation (CSA) by Title
Now showing items 281-300 of 552
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IO Pattern Aware Methods to Improve the Performance and Lifetime of NAND SSD
Modern SSDs can store multiple bits per transistor which enables it to have higher storage capacities. Low cost per bit of such SSDs has made it a commercial success. As of 2018, cells with an ability to store three bits ... -
iSAN : An intelligent storage area network
A storage area network (SAN) is a high-speed special-purpose network that interconnects data storage devices and storage-consumers. Present day SANs, based on Fibre Channel or iSCSI, share a common deficiency: Neither of ... -
The Isoperimetric Problem On Trees And Bounded Tree Width Graphs
(2010-08-26)In this thesis we study the isoperimetric problem on trees and graphs with bounded treewidth. Let G = (V,E) be a finite, simple and undirected graph. For let δ(S,G)= {(u,v) ε E : u ε S and v ε V – S }be the edge boundary ... -
Kernel Methods Fast Algorithms and real life applications
(Indian Institute of Science, 2005-02-08)Support Vector Machines (SVM) have recently gained prominence in the field of machine learning and pattern classification (Vapnik, 1995, Herbrich, 2002, Scholkopf and Smola, 2002). Classification is achieved by finding a ... -
knowledge teaching : an alternative strategy for knowkedge-base development
The development of knowledge-based systems relies heavily on the transfer of human expertise into a structured knowledge base - a process known as knowledge acquisition or knowledge elicitation. This process is widely ... -
A Knowledge-Based Approach To Pattern Clustering
(Indian Institute of Science, 2005-03-11)The primary objective of this thesis is to develop a methodology for clustering of objects based on their functionality typified by the notion of concept. We begin by giving a formal definition of concept. By assigning a ... -
Knowledge-based approach to pattern clustering.
The primary objective of this thesis is to develop a methodology for clustering of objects based on their functionality, typified by the notion of concept. We begin by giving a formal definition of concept. By assigning a ... -
Knowledge-based mining of multi-database for associations
Knowledge Discovery in Databases (KDD) uses knowledge engineering tools and database technology to extract hidden patterns from databases. Data mining is a step in the KDD process that finds useful patterns in the data. ... -
Knowledge-based preanalysis for multilevel clustering
Multilevel clustering offers the cluster analyst flexibility of choosing different algorithms at different levels with the possibility of reducing overall computational effort in comparison with the single-level application ... -
Labelled clustering and its applications
Clustering is a process of grouping a collection of objects. Clustering approaches can be broadly categorized into conventional and knowledge-based approaches. In a conventional approach, objects are typically represented ... -
Language Support for Exploiting Software Structure Specifications
(Indian Institute of Science, 2005-02-16)Precise specification of the architecture and design of software is a good practice. Such specifications contain a lot of information about the software that can potentially be exploited by tools, to reduce redundancy ... -
Language Support for Exploiting Software Structure Specifications
Precise specification of the architecture and design of software is a good practice. Such specifications contain a lot of information about the software that can potentially be exploited by tools to reduce redundancy in ... -
Language Support For Testing CORBA Based Applications
(Indian Institute of Science, 2005-12-07)Component Based Development has emerged as economical, reusable, scalable way of developing enterprise as well as embedded software applications. Testing distributed component based systems is difficult when third party ... -
Large Data Clustering And Classification Schemes For Data Mining
(2009-03-20)Data Mining deals with extracting valid, novel, easily understood by humans, potentially useful and general abstractions from large data. A data is large when number of patterns, number of features per pattern or both are ... -
Large Scale Graph Processing in a Distributed Environment
(2018-05-25)Graph algorithms are ubiquitously used across domains. They exhibit parallelism, which can be exploited on parallel architectures, such as multi-core processors and accelerators. However, real world graphs are massive in ... -
Large Scale Implementation Of The Block Lanczos Algorithm
(2010-08-16)Large sparse matrices arise in many applications, especially in the major problems of Cryptography of factoring integers and computing discrete logarithms. We focus attention on such matrices called sieve matrices generated ... -
Learning Algorithms Using Chance-Constrained Programs
(2010-07-08)This thesis explores Chance-Constrained Programming (CCP) in the context of learning. It is shown that chance-constraint approaches lead to improved algorithms for three important learning problems — classification with ... -
Learning Decentralized Goal-Based Vector Quantization
(2012-05-04) -
Learning Dynamic Prices In Electronic Markets
(2011-04-19)