Browsing Dissertations & Theses by Title
Now showing items 121-140 of 596
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DAS page replacement algorithm
(2020-06-04)There are different page replacement algorithms and yet there seems to be some drawbacks in them, making no page replacement algorithm ideal. To be one step closer to achieving the ideal algorithm it is vital to have a ... -
Data Analytics Over Hidden Databases
(Computer Science & Engineering, 2010-11-01)Web based access to databases have become a popular method of datadelivery. A multitude of websites provides access to their proprietary datathrough web forms. In order to view this data, customers use the web forminterface ... -
Data Discovery Analysis on Complex Time Series Data
(2022-12-20)Complex time series are a ubiquitous form of data in the modern world. They have wide application across many different fields of scientific inquiry and business endeavor. Time series are used to understand and forecast ... -
Data Dissemination Protocols In Wireless Sensor Networks : Design, Modeling And Security
(Computer Science & Engineering, 2008-08-08)Wireless sensor and actuator networks have been one of the stepping stones towards realizing a pervasive computing infrastructure. However, in a post-deployment scenario, transferring critical updates and reconfigurations ... -
Data-Driven Modeling of Heterogeneous Multilayer Networks For Computing Communities Using Bipartite Graphs
(2019-08-12)Today, more than ever, data modeling and analysis play a vital role for enterprises in terms of finding actionable business intelligence. Data is being collected on a large scale from multiple sources hoping they can be ... -
DECOUPLING-BASED APPROACH TO CENTRALITY DETECTION IN HETEROGENEOUS MULTILAYER NETWORKS
(2021-08-13)Graph analysis is one of the techniques widely used for data analysis. It is used extensively on single graphs. Its ability to capture entities and relationships makes it an attractive data model. Search on graphs, such ... -
DEDUPLICATION-AWARE PAGE CACHE IN LINUX KERNEL FOR IMPROVED READ PERFORMANCE
(2019-12-16)The amount of data being produced and consumed is increasing every day. As a result, there can be a large amount of redundant data in the storage system. Storing and accessing these duplicate data unnecessarily consumes ... -
Deep Learning Based Multi-Label Classification for Surgical Tool Presence Detection in Laparoscopic Videos
(2017-08-07)Laparoscopic surgery, Modern surgery, where the surgery is performed far away from the patient by inserting small incisions on the patient's body and the surgery is performed with a help of a video recorder and through ... -
DEEP LEARNING FOR MOLECULAR PROPERTY PREDICTION
(2023-08-14)Drug discovery has always been a crucial task for society, and molecular property prediction is one of the fundamental problem. It is responsible for identifying the target properties or severe side-effects, so that certain ... -
DEEP LEARNING FOR PROTEIN PROPERTY AND STRUCTURE PREDICTION
(2022-08-15)I present my work towards solving the fundamental, challenging, and valuable problem for protein property and structure prediction. Specifically, I focus on solving the problem from three critical aspects: (1) designing ... -
Deep Learning for Recognition of Objects, Activities, Faces, and Spatio-Temporal Patterns
A popular method in machine learning is Convolutional Neural Network (CNN). CNN had was of high interest to the research community in the 1990s, but after that its popularity receded compared to the Support Vector Machine ... -
DEEP LEARNING METHODS FOR IMAGE RESTORATION AND RECONSTRUCTION
(2021-04-19)The problem of image reconstruction and restoration refers to recovering the clean images from corrupted ones. Corruption or degradation can occur due to atmospheric conditions such as rain, fog, mist, snow, dust, and air ... -
Deep Reinforcement Learning-based Portfolio Management
(2019-05-16)Machine Learning is at the forefront of every field today. The subfields of Machine Learning called Reinforcement Learning and Deep Learning, when combined have given rise to advanced algorithms which have been successful ... -
Deep Representation Learning for Clustering and Domain Adaptation
(2019-12-05)Representation learning is a fundamental task in the area of machine learning which can significantly influence the performance of the algorithms used in various applications. The main goal of this task is to capture the ... -
DEEP REPRESENTATION LEARNING ON GIGA-PIXEL WHOLE SLIDE IMAGES
(2020-05-21)I present my work towards solving the fundamental, challenging and valuable problem for automatically processing the giga-pixel level whole slide pathology images (WSIs): the representation of them. Specifically, I target ... -
DEEPSIGN: A DEEP-LEARNING ARCHITECTURE FOR SIGN LANGUAGE
(2018-11-13)Sign languages are used by deaf people for communication. In sign languages, humans use hand gestures, body, facial expressions and movements to convey meaning. Humans can easily learn and understand sign languages, but ... -
Defending Neural Networks Against Adversarial Examples
(2018-12-12)Deep learning is becoming a technology central to the safety of cars, the security of networks, and the correct functioning of many other types of systems. Unfortunately, attackers can create adversarial examples, small ... -
Delay Tolerant Lazy Release Consistency For Distributed Shared Memory In Opportunistic Networks
(Computer Science & Engineering, 2011-10-11)Opportunistic networking (ON), a concept which allows a mobile wireless device to dynamically interact with other wireless devices in its immediate vicinity, is a field with great potential to improve the utility of itinerant ... -
Design And Analysis Of A Mobile File Sharing System For Opportunistic Networks
(Computer Science & Engineering, 2009-09-16)In the past several years, wireless mobile devices with advanced computing, sensing, and storing capabilities have been increasingly developed by handset manufacturers, deployed by wireless carriers, and accepted by ... -
Design And Analysis Of Application Architecture For Opportunistic Networks Using Ad Hoc Wi-Fi
(Computer Science & Engineering, 2010-03-03)In recent years, the number of smartphone users has increased by many folds. In fact, it is estimated to reach 100 million by 2013. Current generation of smartphones has better storage, battery, computing capabilities and ...