WorldCat Identities

University of Alberta Department of Computing Science

Overview
Works: 633 works in 670 publications in 1 language and 1,621 library holdings
Genres: Conference papers and proceedings 
Classifications: Z699, 000
Publication Timeline
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Most widely held works about University of Alberta
 
Most widely held works by University of Alberta
Fifth IEEE International Workshop on Web Site Evolution : proceedings : theme: architecture : Amsterdam, the Netherlands, 22 September, 2003 by International Workshop on Web Site Evolution( Book )

6 editions published in 2003 in English and held by 28 WorldCat member libraries worldwide

Report on information retrieval and library automation studies by University of Alberta( Book )

2 editions published in 1972 in English and held by 10 WorldCat member libraries worldwide

Queries and query processing in object-oriented database systems by Dave D Straube( Book )

2 editions published between 1990 and 1991 in English and held by 8 WorldCat member libraries worldwide

Using semantic knowledge of transactions to increase concurrency by Abdel A Farrag( Book )

2 editions published between 1985 and 1989 in English and held by 8 WorldCat member libraries worldwide

Data structures for spatial data processing by Wayne A Davis( Book )

1 edition published in 1985 in English and held by 5 WorldCat member libraries worldwide

Selecting test data for the domain testing strategy by I. A Perera( Book )

1 edition published in 1985 in English and held by 5 WorldCat member libraries worldwide

On determining tree-query membership of a distributed query by C. T Yu( Book )

1 edition published in 1980 in English and held by 5 WorldCat member libraries worldwide

Experiments determining best paths for testing computer program predicates by L. J White( Book )

1 edition published in 1985 in English and held by 5 WorldCat member libraries worldwide

A survey of current LAN technology and performance by W. J Neilson( Book )

1 edition published in 1985 in English and held by 5 WorldCat member libraries worldwide

Discovering spatial co-clustering patterns in collision data by Dapeng Li( )

1 edition published in 2013 in English and held by 3 WorldCat member libraries worldwide

Identifying spatial patterns of collisions is critical for improving the efficiency and effectiveness of traffic enforcement deployment and road safety. Recently, many studies have centred on finding locations with high collision concentration, so-called hotspots. However, most of them only focus on the location information of the collision data, without integrating the non-spatial attributes into analysis. Taking non-spatial attributes into account opens opportunities to reveal attribute-related hotspots that otherwise goes undetected, and can add valuable indicators for explaining those hotspots. In this thesis, we address this problem. We propose a method for identifying the sets of non-spatial attribute-value pairs (AVPs) that together contribute significantly to the spatial clustering of the corresponding collisions. We call such AVP sets Spatial Co-Clustering Patterns (SCCPs). By applying our method on Edmonton's collision data, we discovered larger numbers of meaningful hotspot patterns than traditional methods did, and revealed the relevant non-spatial indicators for explaining those hotspots
Gabor-gist visual homing by Michael J Mills( )

1 edition published in 2013 in English and held by 3 WorldCat member libraries worldwide

Many robotic systems are required to navigate or home to learned location using minimal resources. Autonomous robots are generally limited in computation and storage resources, imposing significant challenges on algorithm design. Particularly when only visual data is used, these algorithms need to be robust and efficient. In addition, independence from a scene model is preferred. Extraction of models and calibration procedures are time consuming and sensitive to changes in the environment. Visual homing without a geometric model is studied in mapless or qualitative visual homing. In this thesis, we adopt a framework based on View-Sequenced Route Representation (VSRR) and contribute in two areas: Compact representation of the path and visual homing along a desired route using the representation, and secondly develop an algorithm which localizes the robot using a novel concept we call eigensegments. The effectiveness of the system is demonstrated with both indoor and outdoor environments
A measure of perceptual aliasing in image descriptors by Jiemin Wang( )

1 edition published in 2013 in English and held by 3 WorldCat member libraries worldwide

This thesis is concerned with a measure of perceptual aliasing in image descriptors. Perceptual aliasing occurs when the one-to-one mapping relations between world states (objects) and their representation (descriptors) are not maintained. Our method measures the discriminating power of an image descriptor in terms of its ability to distinguish between images of different objects and to match images of the same object. Specifically, our method runs spectral clustering on the similarity matrix computed with descriptors of known image clusters and measures the performance of an image descriptor by its ability to maintain the original clusters, using two indices, MRI-1 and MRI-2, that are based on the Rand index. Experiments on MRI versus precision and recall show that our proposed metrics are more appropriate for applications such as content-based image retrieval in which image clustering is a critical step
A contextual approach towards more accurate duplicate bug report detection by Anahita Alipour( )

1 edition published in 2013 in English and held by 3 WorldCat member libraries worldwide

The issue-tracking systems used by software projects contain issues or bugs written by a wide variety of bug reporters, with different levels of knowledge about the system under development. Typically, reporters lack the skills and/or time to search the issue-tracking system for similar issues already reported. Hence, many reports end up referring to the same issue, which effectively makes the bug-report triaging process time consuming and error prone. Many researchers have approached the bug-deduplication problem using off-the-shelf information-retrieval tools. In this thesis, we extend the state of the art by investigating how contextual information about software-quality attributes, software-architecture terms, and system-development topics can be exploited to improve bug-deduplication. We demonstrate the effectiveness of our contextual bug-deduplication method on the bug repository of Android, Eclipse, Mozilla, and OpenOffice Software Systems. Based on this experience, we conclude that researchers should not ignore the context of the software engineering domain for deduplication
Cluster-and-conquer : a paradigm for solving state-space problems by Levi H Santana de Lelis( )

1 edition published in 2013 in English and held by 3 WorldCat member libraries worldwide

Many important problems can be cast as state-space problems. In this dissertation we study a general paradigm for solving state-space problems which we name Cluster-and-Conquer (C & C). Algorithms that follow the C & C paradigm use the concept of equivalent states to reduce the number of states explored to solve the problem. The concept of equivalent states is captured by a type system, which is a partition of the states in the state space. C & C algorithms assume that states of the same type are equivalent to one another, thus only one state of each type must be explored. Although our type systems only approximate the ideal partition of states into equivalent states, the solutions found by most of our C & C algorithms are guaranteed to converge to optimal solutions. The C & C paradigm is general and can be used to solve different problems. In this dissertation we advance and develop C & C algorithms for solving different state-space problems. Namely, we advance Conditional Distribution Prediction (CDP) and Stratified Sampling (SS), two existing algorithms for predicting the search tree size of Iterative-Deepening A* (IDA*). Among other contributions, (1) we introduce different heuristic-based type systems, and (2) we apply the concept of active sampling to increase the accuracy of the predictions. Our versions of CDP and SS represent the current state of the art for predicting the IDA* search tree size; we present Two-Step Stratified Sampling (TSS), an algorithm for predicting the search tree size of Depth-First Branch and Bound (DFBnB). TSS is the only known algorithm able to produce accurate predictions of the DFBnB search tree size in a reasonable amount of time; we present Solution Cost Predictor (SCP) and Bidirectional Stratified Sampling (BiSS), the first algorithms designed for predicting the optimal solution cost of state-space problems. We show that one can reduce from days to minutes the time required for learning heuristic functions by using BiSS to label the training set; we present Stratified Tree Search (STS), a search algorithm for finding suboptimal solutions of state-space problems when the only heuristics available are too weak to usefully guide existing methods
Robust learning under uncertain test distributions by Junfeng Wen( )

1 edition published in 2013 in English and held by 3 WorldCat member libraries worldwide

Many learning situations involve learning the conditional distribution p(y
A solution to the eye contact correction in tele-presence systems by Xiaozhou Zhou( )

1 edition published in 2013 in English and held by 3 WorldCat member libraries worldwide

With the development of globalization, numerous tele-conferencing systems have been developed to shorten the distance between people. Tele-presence is one of these systems which can broadcast high-quality audio and video to remote sites trying to give the illusion to the participants that they are co-located in a common virtual meeting room. In order to provide this illusion, one main criterion is to maintain eye contact. This is important because eye contact can convey more information than languages sometimes and correct eye contact is one of the essential factors which make the participants feel like they are talking face-to-face. However, some of the successful methods to eye contact correction problem in tele-presence systems need special equipment which is either large or expensive. In this thesis, we propose a software-based solution to the eye contact correction problem. This solution uses depth-based view interpolation to create virtual views from a network of cameras located around the display screen. Using this method, users have the freedom to adjust their viewpoints to allow eye contact or to focus their attention on important regions. To improve the illusion of being in a common meeting room, we propose a new image matting algorithm to extract a participant from the background that can deal with hair and small details. This is essential as any small imperfections in the matte will destroy the illusion of being in a same virtual meeting room. In the thesis, we also explore how to overcome the uneven illumination found in tele-presence rooms. We present solutions to the illumination invariant stereo matching problem to create better disparity maps. Taking the advantage of the parallel structure of local stereo matching, the GPU implementation of the proposed solution can run in real time. Intensive experiments demonstrate the effectiveness and efficiency. In general, our main goal in this thesis is to develop core technologies that will eventually be used in future tele-presence systems
The impact of user choice and software change on energy consumption by Chenlei Zhang( )

1 edition published in 2013 in English and held by 3 WorldCat member libraries worldwide

Hardware and software engineers are instrumental in developing energy efficient mobile systems. Unfortunately the last mile of energy efficiency comes from the choices and requirements of the end-user. Imagine an end-user who has no power-outlet access and must remain productive on her laptop battery life. How does this user maximize the laptop's battery life, yet remain productive? What does the user have to give up to keep on working? In the first half of this thesis, we highlight the peril that users face and the ultimate responsibility users have for the battery life and energy consumption of their mobile devices; using multiple scenarios we show that executing a task can consume more or less energy depending on the requirements and software choices of users. We investigate multiple scenarios demonstrating that applications can consume energy differently for the same task thus illustrating the tradeoffs that end-users can make for the sake of energy consumption. Furthermore, as the builders and more frequently the maintainers of applications, software developers are responsible for updating and shipping energy efficient applications for end-users. Yet, the impact of software changes on energy consumption is still a mystery. Thus in the second half of this thesis we relate software changes to energy consumption by tracing the system calls that act as the interface between user applications and the OS kernel. We show the energy consumption evolution of multiple gedit versions under two test scenarios. We also present the potential of modeling software energy consumption via system call invocations
Human metabolite identification through web-based applications by Ronghong Li( )

1 edition published in 2013 in English and held by 3 WorldCat member libraries worldwide

High throughput bio-technologies in chemistry experiments generate a huge amount of data. These data are awaiting to be analyzed for knowledge discovery. In this work, we have developed a web-based resource MyCompoundID for compound identification. Our base database contains 8,021 metabolite substrates imported from Human Metabolome Database, and we adopt 76 the most commonly encountered biotransformations collected from the literature. We first expand the database to include all the pseudo metabolic products for up to two reactions, which are filtered by multiple levels of restrictions we specified. Using MyCompoundID for compound identification, either through mass queries or MS/MS spectrum queries, can identify many more unknown metabolites than using the existing works
A unified FEM-based framework for medical image registration and segmentation by Karteek Popuri( )

1 edition published in 2013 in English and held by 3 WorldCat member libraries worldwide

Medical image registration and segmentation are challenging because, medical images are generally corrupted by noise, image artifacts and the various anatomical regions of interest in medical images often do not have distinct sharp boundaries. However, these anatomical regions frequently exhibit consistent shape and topological characteristics which is an advantage when compared to natural images. In our proposed work, we take into account the above mentioned aspects and devise automatic registration and segmentation methods using the popular energy minimization framework, with an application to medical images. In contrast to the widely used level set based segmentation approach, we follow the template-based segmentation approach, which is more suitable for medical images as it can easily handle multi-region segmentation and also has the desirable property of preserving the known topology of the anatomical structures. However, unlike the traditional template-based segmentation and registration methods that use uniform meshes along with the finite difference method (FDM) to solve the partial differential equations (PDEs) that arise in these methods, we use the finite element method (FEM) and solve the PDEs on a non-uniform mesh to obtain solutions whose accuracy is well adapted to the salient features in the image domain. In this work, we present a unified FEM-based registration and segmentation framework where the goal is to estimate a deformation field following the minimization of an energy that consists of a common diffusion-based regularization term and data term that depends on the appropriate segmentation or registration objective. Further, we extend this framework through the incorporation of an additional shape prior based regularization term that is learned from training data. Lastly, we propose a novel variational formulation for discrete deformable registration and show that interestingly it can be cast into our unified FEM-based registration and segmentation framework. We validated our proposed unified FEM-based segmentation and registration framework on real medical images including some of the popular benchmark datasets. We present a thorough evaluation of the various registration and segmentation algorithms developed in our work by comparing their performance with the other established methods in image registration and segmentation
SafeType : detecting type violations for type-based alias analysis of C by Iain Ireland( )

1 edition published in 2013 in English and held by 3 WorldCat member libraries worldwide

A type-based alias analysis uses the types of variables in a program to assist in determining the alias relations of those variables. The C standard imposes restrictions on the types of expressions that may access objects in memory, with the explicit intent of specifying when two objects may be aliased. In practice, however, many C programs do not conform to these restrictions, making type-based alias analysis unsound for those programs. As a result, type-based alias analysis is frequently disabled. This thesis presents SafeType, a sound approach for compile-time detection of violations of the C standard's type-based restrictions on memory access; describes an implementation of SafeType in the IBM XL C compiler, extended with flow- and context-sensitive queries to handle variables with type void *; evaluates that implementation, showing that it scales to programs with hundreds of thousands of lines of code; and identifies a previously unreported violation of the C standard's type-based restrictions on memory access in the 470.lbm benchmark in SPEC CPU2006
 
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Alternative Names

controlled identityUniversity of Alberta

University of Alberta. Dept. of Computing Science

Languages
English (30)