Department of Computer Science

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https://hdl.handle.net/20.500.14078/7

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PBS software: maps, spatial analysis, and other utilities
(2003) Schnute, Jon; Boers, Nicholas; Haigh, Rowan
This report describes software written to facilitate the compilation and analysis of fishery data, particularly data referenced by spatial coordinates. Our research stems from experiences with information on Canada s Pacific groundfish fisheries compiled at the Pacific Biological Station (PBS). Despite its origins in fishery data analysis, our software has broad applicability. The library PBS Mapping extends the languages R and S-PLUS to include two dimensional plotting features similar to those commonly available in a Geographic Information System (GIS). Embedded C code speeds algorithms from computational geometry, such as finding polygons that contain specified point events or converting between longitude-latitude and Universal Transverse Mercator (UTM) coordinates. We also present a number of convenient utilities for the Microsoft Windows operating systems, including commands that support computational geometry outside the framework of R or S-PLUS. Tools to construct most of our software come freely from the Internet, as documented here in a guide to the packages available. Furthermore, we provide quick tutorials that address key technical issues relevant to our work, such as embedding C code into an R package and writing documentation that meets the R standard. Our results, which depend significantly on the work of students, illustrate the convergence of goals between academic training and applied research.
PBS mapping 2: developer’s guide
(2004) Boers, Nicholas; Haigh, Rowan; Schnute, Jon
This report describes the technical process used to develop and build the software package PBS Mapping 2. A companion User’s Guide (Schnute et al. 2004) documents the purpose and use of this software, which involves over 10,000 lines of code for R, S-PLUS, and C. To build the package from source files, we use a variety of software tools, most of them freely available from the Internet. We outline procedures for downloading and installing these tools, and we describe the directory tree of source files for building PBS Mapping and a related package PBS Data. We then explain how to use automated scripts that build our libraries for three software environments: R, S-PLUS 2000, and S-PLUS 6. Additional scripts create PDF documentation files for appendices in the User’s Guide.
No more isolated files: managing files as social artifacts
(2006) Indratmo, Indratmo; Vassileva, Julita
People manage and use their files/documents in social settings. However, current file systems do not consider social interactions that happen around files. For example, files that have been sent to many people are displayed in the same way as those that have never been sent. We argue that by capturing user activities around files, we can enhance user experience in managing their documents. In particular, presenting activity traces can help users comprehend their document collections better and recall the context of their documents. In this paper, we discuss our approach to providing a context-rich environment for document management.
A usability study of an access control system for group blogs
(2007) Indratmo, Indratmo; Vassileva, Julita
Blogs are a medium to express thoughts, feelings, and opinions. Once published, blog articles potentially become persistent and can be read by non-intended audiences, causing hurt feelings and other troubles. In part these problems are due to the lack of access control in blogs. We propose an access control framework for group blogs. Compared to the typical access control in blogging tools, our system differs in a few aspects. First, the system enables bloggers to grant different access privileges to different audiences over a single blog article. That is, it associates access privileges to people rather than to artifacts (e.g., articles, blogs). Second, the system allows a blogger to create a collaborative space with other bloggers, for example by allowing others to edit his or her articles. Third, the management of access control is integrated with the process of writing and editing blog articles, facilitating the main workflow of the user. We conducted a usability study to evaluate our system and get constructive feedback from users. In this article, we present the proposed access control system, the results of the study, and analysis of the results.
A review of organizational structures of personal information management
(2008) Indratmo, Indratmo; Vassileva, Julita
Personal information management (PIM) covers a large area of research fragmented into separate sub-areas such as file management, web bookmark organization, and email management. Consequently, it is hard to obtain a unified view of the various approaches to PIM developed in these different sub-areas. In this article, we synthesize and classify existing research on PIM based on the approach used to organize information items. We classify the organizational structures into five categories: hierarchical, flat, linear, spatial, and network. We discuss the strengths and weaknesses of each structure along with examples showing how to deal with the weaknesses. Finally, we provide design recommendations and a framework for researchers to experiment with various ideas for developing novel PIM tools.
The role of social interaction filter and visualization in casual browsing
(2012) Indratmo, Indratmo; Vassileva, Julita
Traces of social interaction in information spaces have the potential to improve information exploration. We evaluated interactive interfaces that utilize social interaction history. More specifically, we compared the value of a social filter and social interaction visualization in supporting casual browsing. We hypothesized that information filtering in general plays a more important role than visualization, as it provides additional control for users to browse information collections. Our experimental results showed that, compared to the baseline interface, the social filter increased subjective user satisfaction and was perceived by the study participants to enhance their effectiveness in finding interesting information. However, there were no significant differences between the social filter and social visualization systems. Our analysis suggested that the synergy of information filtering and visualization is more effective than each feature working separately.
Visualizing stock market data with self‐organizing map
(2013) Joseph, Joel; Indratmo, Indratmo
Finding useful patterns in stock market data requires tremendous analytical skills and effort. To help investors manage their portfolios, we developed a tool for clustering and visualizing stock market data using an unsupervised learning algorithm called Self-Organizing Map. Our tool is intended to assist users in identifying groups of stocks that have similar price movement patterns over a period of time. We performed a visual analysis by comparing the resulting visualization with Yahoo Finance charts. Overall, we found that the Self-Organizing Map algorithm can analyze and cluster the stock market data reasonably.
PBSmapping 2.66: user’s guide
(2013) Schnute, Jon; Boers, Nicholas; Haigh, Rowan; Couture-Beil, Alex
This report describes a second version of software designed to facilitate the compilation and analysis of fishery data, particularly data referenced by spatial coordinates. Our research stems from experiences with information on Canada’s Pacific groundfish fisheries compiled at the Pacific Biological Station (PBS). Despite its origins in fishery data analysis, our software has broad applicability. The library PBSmapping extends the R-statistical language to include two dimensional plotting features similar to those commonly available in a Geographic Information System (GIS). Embedded C code speeds algorithms from computational geometry, such as finding polygons that contain specified point events or converting between longitude-latitude and Universal Transverse Mercator (UTM) coordinates. We also present a number of convenient utilities for Microsoft Windows operating systems that support computational geometry outside the framework of R. Our results, which depend significantly on the work of students, illustrate the convergence of goals between academic training and applied research.
A model for web-based course registration systems
(2014) Estevez, Ruben; Rankin, Sean; Silva, Ricardo; Indratmo, Indratmo
University students use web-based course registration systems to search, select, and register to courses. Despite having an important role at universities, course registration systems often pose usability problems to users. In this project, the authors assessed the usability of a web-based course registration system, proposed an improved model for such systems, and evaluated the model. The paper aims to discuss these issues.
Mapping fisheries data and spatial analysis tools
(2015) Schnute, Jon; Boers, Nicholas; Haigh, Rowan; Couture-Beil, Alex; Chabot, Denis; Grandin, Chris; Johnson, Angus; Wessel, Paul; Antonio, Franklin; Lewin-Koh, Nicholas; Bivand, Roger
This software has evolved from fisheries research conducted at the Pacific Biological Station (PBS) in `Nanaimo', British Columbia, Canada. It extends the R language to include two-dimensional plotting features similar to those commonly available in a Geographic Information System (GIS). Embedded C code speeds algorithms from computational geometry, such as finding polygons that contain specified point events or converting between longitude-latitude and Universal Transverse Mercator (UTM) coordinates. Additionally, we include `C++' code developed by Angus Johnson for the `Clipper' library. Also included are data for a global shoreline and other data sets in the public domain. The R directory `.../library/PBSmapping/doc' offers a complete user's guide, which should be consulted to use package functions effectively.
GUI tools made easy: interact with models and explore data
(2015) Schnute, Jon; Couture-Beil, Alex; Haugh, Rowan; Kronlund, Rob; Boers, Nicholas
Provides software to facilitate the design, testing, and operation of computer models. It focuses particularly on tools that make it easy to construct and edit a customized graphical user interface (GUI). Although our simplified GUI language depends heavily on the R interface to the Tcl/Tk package, a user does not need to know Tcl/Tk. Examples illustrate models built with other R packages, including PBSmapping, PBSddesolve, and BRugs. A complete user's guide `PBSmodelling-UG.pdf' shows how to use this package effectively.
Solver for delay differential equations
(2016) Couture-Beil, Alex; Schnute, Jon; Haigh, Rowan; Wood, Simon; Cairns, Benjamin; Boers, Nicholas
Routines for solving systems of delay differential equations by interfacing numerical routines written by Simon N. Wood , with contributions by Benjamin J. Cairns. These numerical routines first appeared in Simon Wood's 'solv95' program. This package includes a vignette and a complete user's guide. 'PBSddesolve' originally appeared on CRAN under the name 'ddesolve'. That version is no longer supported. The current name emphasizes a close association with other PBS packages, particularly 'PBSmodelling'.
Model-based clustering and classification with the multivariate t distribution
(2016) Andrews, Jeffrey; Wickins, Jaymeson; Boers, Nicholas; McNicholas, Paul
Package ‘teigen’: Fits mixtures of multivariate t-distributions (with eigen-decomposed covariance structure) via the expectation conditional-maximization algorithm under a clustering or classification paradigm.
A deep level set method for image segmentation
(2017) Tang, Min; Valipour, Sepehr; Zhang, Zichen; Cobzas, Dana; Jagersand, Martin
This paper proposes a novel image segmentation approach that integrates fully convolutional networks (FCNs) with a level set model. Compared with a FCN, the integrated method can incorporate smoothing and prior information to achieve an accurate segmentation. Furthermore, different than using the level set model as a post-processing tool, we integrate it into the training phase to fine-tune the FCN. This allows the use of unlabeled data during training in a semi-supervised setting. Using two types of medical imaging data (liver CT and left ventricle MRI data), we show that the integrated method achieves good performance even when little training data is available, outperforming the FCN or the level set model alone.
PBSsatellite 1.0: user’s guide
(2017) Lefebvre, Nicholas R.; Boers, Nicholas; Godbout, Lyse; Haigh, Rowan; Boers, Nicholas
This report describes the first version of PBSsatellite, software designed to simplify the extraction and statistical analysis of gridded satellite data. This software extends the R Project for Statistical Computing, and it uses PBSmapping, an existing R package, to aid in spatial analysis and the production of plots. The tools found in this package provide users with the functionality necessary to work with data from a variety of sources. Additionally, users are able to write their own data interpretation algorithms and provide them as arguments to some analysis functions within this package.
Progressive iron accumulation across multiple sclerosis phenotypes revealed by sparse classification of deep gray matter
(2017) Elkady, Ahmed M.; Cobzas, Dana; Sun, Hongfu; Blevins, Gregg; Wilman, Alan H.
To create an automated framework for localized analysis of deep gray matter (DGM) iron accumulation and demyelination using sparse classification by combining quantitative susceptibility (QS) and transverse relaxation rate (R2*) maps, for evaluation of DGM in multiple sclerosis (MS) phenotypes relative to healthy controls.R2*/QS maps were computed using a 4.7T 10‐echo gradient echo acquisition from 16 clinically isolated syndrome (CIS), 41 relapsing‐remitting (RR), 40 secondary‐progressive (SP), 13 primary‐progressive (PP) MS patients, and 75 controls. Sparse classification for R2*/QS maps of segmented caudate nucleus (CN), putamen (PU), thalamus (TH), and globus pallidus (GP) structures produced localized maps of iron/myelin in MS patients relative to controls. Paired t‐tests, with age as a covariate, were used to test for statistical significance (P ≤ 0.05).In addition to DGM structures found significantly different in patients compared to controls using whole region analysis, singular sparse analysis found significant results in RRMS PU R2* (P = 0.03), TH R2* (P = 0.04), CN QS (P = 0.04); in SPMS CN R2* (P = 0.04), GP R2* (P = 0.05); and in PPMS CN R2* (P = 0.04), TH QS (P = 0.04). All sparse regions were found to conform to an iron accumulation pattern of changes in R2*/QS, while none conformed to demyelination. Intersection of sparse R2*/QS regions also resulted in RRMS CN R2* becoming significant, while RRMS R2* TH and PPMS QS TH becoming insignificant. Common iron‐associated volumes in MS patients and their effect size progressively increased with advanced phenotypes.A localized technique for identifying sparse regions indicative of iron or myelin in the DGM was developed. Progressive iron accumulation with advanced MS phenotypes was demonstrated, as indicated by iron‐associated sparsity and effect size.
Progressive iron accumulation across multiple sclerosis phenotypes revealed by sparse classification of deep gray matter
(2017) Elkady, Ahmed M.; Cobzas, Dana; Sun, Hongfu; Blevins, Gregg; Wilman, Alan H.
Purpose: To create an automated framework for localized analysis of deep gray matter (DGM) iron accumulation and demyelination using sparse classification by combining quantitative susceptibility (QS) and transverse relaxation rate (R2*) maps, for evaluation of DGM in multiple sclerosis (MS) phenotypes relative to healthy controls. Materials and Methods: R2*/QS maps were computed using a 4.7T 10-echo gradient echo acquisition from 16 clinically isolated syndrome (CIS), 41 relapsing-remitting (RR), 40 secondary-progressive (SP), 13 primary-progressive (PP) MS patients, and 75 controls. Sparse classification for R2*/QS maps of segmented caudate nucleus (CN), putamen (PU), thalamus (TH), and globus pallidus (GP) structures produced localized maps of iron/myelin in MS patients relative to controls. Paired t-tests, with age as a covariate, were used to test for statistical significance (P ≤ 0.05).Results: In addition to DGM structures found significantly different in patients compared to controls using whole region analysis, singular sparse analysis found significant results in RRMS PU R2* (P = 0.03), TH R2* (P = 0.04), CN QS (P = 0.04); in SPMS CN R2* (P = 0.04), GP R2* (P = 0.05); and in PPMS CN R2* (P = 0.04), TH QS (P = 0.04). All sparse regions were found to conform to an iron accumulation pattern of changes in R2*/QS, while none conformed to demyelination. Intersection of sparse R2*/QS regions also resulted in RRMS CN R2* becoming significant, while RRMS R2* TH and PPMS QS TH becoming insignificant. Common iron-associated volumes in MS patients and their effect size progressively increased with advanced phenotypes. Conclusion: A localized technique for identifying sparse regions indicative of iron or myelin in the DGM was developed. Progressive iron accumulation with advanced MS phenotypes was demonstrated, as indicated by iron-associated sparsity and effect size.
Significant anatomy detection through sparse classification: a comparative study
(2018) Zhang, Li; Cobzas, Dana; Wilman, Alan H.; Kong, Linglong
We present a comparative study for discriminative anatomy detection in high dimensional neuroimaging data. While most studies solve this problem using mass univariate approaches, recent works show better accuracy and variable selection using a sparse classification model. Two types of image-based regularization methods have been proposed in the literature based on either a Graph Net (GN) model or a total variation (TV) model. These studies showed increased classification accuracy and interpretability of results when using image-based regularization, but did not look at the accuracy and quality of the recovered significant regions. In this paper, we theoretically prove bounds on the recovered sparse coefficients and the corresponding selected image regions in four models (two based on GN penalty and two based on TV penalty). Practically, we confirm the theoretical findings by measuring the accuracy of selected regions compared with ground truth on simulated data. We also evaluate the stability of recovered regions over cross-validation folds using real MRI data. Our findings show that the TV penalty is superior to the GN model. In addition, we showed that adding an l2 penalty improves the accuracy of estimated coefficients and selected significant regions for the both types of models.
The efficacy of stacked bar charts in supporting single-attribute and overall-attribute comparisons
(2018) Indratmo, Indratmo; Howorko, Lee; Boedianto, Joyce Maria; Daniel, Ben
Stacked bar charts are a visualization method for presenting multiple attributes of data, and many visualization tools support these charts. To assess the efficacy of stacked bar charts in supporting attribute comparison tasks, we conducted a user study to compare three types of stacked bar charts: classical, inverting, and diverging. Each chart type was used to visualize six attributes of data where half of the attributes have the characteristics of ‘lower better’ whereas the other half ‘higher better.’ Thirty participants were asked to perform two types of comparison tasks: single-attribute and overall-attribute comparisons. We measured the completion time, error rate, and perceived difficulty of the comparison tasks. The results of the study suggest that, for overall-attribute comparisons, the inverting stacked bar chart was the most effective with regards to the completion time. The results also show that performing overall-attribute comparisons using the classical and diverging stacked bar charts required more time than performing single-attribute comparisons using these charts. Participants perceived the inverting and diverging stacked bar charts as easier-to-use than the classical stacked bar chart for overall-attribute comparisons. However, for single-attribute comparisons, all chart types delivered similar performance. We discuss how these findings can inform the better design of interactive stacked bar charts and visualization tools.
The effects of neighbourhood characteristics on crime incidence
(2018) Letourneau, Steven; Ell, Nathan; Cheung, Peter; McCaskill, Jordan; El-Hajj, Mohamad
Using data from the City of Edmonton, Canada Open Data Portal, an exploration process is undergone using data mining techniques to help detect unseen relationships between tangible spatial characteristics and non-tangible crime incidences. These findings will help law enforcement and city planners make empirically based decisions and avoid the misappropriation of public resources. Using frequent pattern analysis to examine neighbourhood attributes that occur alongside crime provides insight into why crime occurs. These techniques include clustering, classification algorithms, and association algorithms. Results of the analysis on neighbourhood spatial characteristics indicate that dwelling structure type and tree density relate to incidence of neighbourhood crime, while other neighbourhood spatial characteristics bear no relationship. Results also show that intangible neighbourhood characteristics indicate that the distribution of yearly household income and employment and school enrollment levels relate to incidence of neighbourhood crime. The distribution of yearly household income bears a relationship to crime type, specifically violent vs non-violent types.

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