Computer Sciences Commons^™

Monte Carlo Model Of Light Propagation In Tissues And The Effects Of Phase Changes On The Light Intensity, Rakesh Choula

Electrical & Computer Engineering Theses & Dissertations

Lasers, due to their unique properties, have a wide range of applications in the medical field. For accurate laser treatments that focus on bio-tissues, prior knowledge of the amount of laser power, spot size and its irradiation time are necessary. In order to predict the effects of lasers on tissues and their bio-effects, a first necessary step is the creation of a model that can predict the temperature distributions within the tissue following laser excitation. This involves modeling light propagation through the tissue with inclusion of internal scattering, and assessment of the energy deposited by the incoming photons. The next …

Parallel Sets In The Real World: Three Case Studies, Robert Kosara, Caroline Ziemkiewicz, F. Joseph Iii Mako, Tin Seong Kam

Research Collection School Of Computing and Information Systems

Parallel Sets are a visualization technique for categorical data. We recently released an implementation to the public in an effort to make our research useful to real users. This paper presents three case studies of Parallel Sets in use with real data.

Continuous Monitoring Of Spatial Queries In Wireless Broadcast Environments, Kyriakos Mouratidis, Spiridon Bakiras, Dimitris Papadias

Research Collection School Of Computing and Information Systems

Wireless data broadcast is a promising technique for information dissemination that leverages the computational capabilities of the mobile devices in order to enhance the scalability of the system. Under this environment, the data are continuously broadcast by the server, interleaved with some indexing information for query processing. Clients may then tune in the broadcast channel and process their queries locally without contacting the server. Previous work on spatial query processing for wireless broadcast systems has only considered snapshot queries over static data. In this paper, we propose an air indexing framework that 1) outperforms the existing (i.e., snapshot) techniques in …

A Surprise Triggered Adaptive And Reactive (Star) Framework For Online Adaptation In Non-Stationary Environments, Truong-Huy Dinh Nguyen, Tze-Yun Leong

Research Collection School Of Computing and Information Systems

We consider the task of developing an adaptive autonomous agent that can interact with non-stationary environments. Traditional learning approaches such as Reinforcement Learning assume stationary characteristics over the course of the problem, and are therefore unable to learn the dynamically changing settings correctly. We introduce a novel adaptive framework that can detect dynamic changes due to non-stationary elements. The Surprise Triggered Adaptive and Reactive (STAR) framework is inspired by human adaptability in dealing with daily life changes. An agent adopting the STAR framework consists primarily of two components, Adapter and Reactor. The Reactor chooses suitable actions based on predictions made …

Visible Reverse K-Nearest Neighbor Query Processing In Spatial Databases, Yunjun Gao, Baihua Zheng, Gencai Chen, Wang-Chien Lee, Ken C. K. Lee, Qing Li

Research Collection School Of Computing and Information Systems

Reverse nearest neighbor (RNN) queries have a broad application base such as decision support, profile-based marketing, resource allocation, etc. Previous work on RNN search does not take obstacles into consideration. In the real world, however, there are many physical obstacles (e.g., buildings) and their presence may affect the visibility between objects. In this paper, we introduce a novel variant of RNN queries, namely, visible reverse nearest neighbor (VRNN) search, which considers the impact of obstacles on the visibility of objects. Given a data set P, an obstacle set O, and a query point q in a 2D space, a VRNN …

Detecting Automotive Exhaust Gas Based On Fuzzy Inference System, Li. Shujin, Ming Bai, Quan Wang, Bo Chen, Xiaobing Zhao, Ting Yang, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

This paper proposes a method of detecting automotive exhaust gas based on fuzzy logic inference after analyzing the principle of the infrared automobile exhaust gas analyzer and the influence of the environmental temperature on analyzer. This paper analyses the measurement error caused by environmental temperature, and then makes a non-linear error correction of temperature for the infrared sensor using fuzzy inference. The results of simulation have clearly demonstrated that the proposed fuzzy compensation scheme is better than the non-fuzzy method.

Inferring Player Rating From Performance Data In Massively Multiplayer Online Role-Playing Games (Mmorpgs), Kyong Jin Shim, Muhammad Aurangzeb Ahmad, Nishith Pathak, Jaideep Srivastava

Research Collection School Of Computing and Information Systems

This paper examines online player performance in EverQuest II, a popular massively multiplayer online role-playing game (MMORPG) developed by Sony Online Entertainment. The study uses the game's player performance data to devise performance metrics for online players. We report three major findings. First, we show that the game's point-scaling system overestimates performances of lower level players and underestimates performances of higher level players. We present a novel point-scaling system based on the game's player performance data that addresses the underestimation and overestimation problems. Second, we present a highly accurate predictive model for player performance as a function of past behavior. …

Essential Spreadsheet Modeling Course For Business Students, Thin Yin Leong, Michelle L. F. Cheong

Research Collection School Of Computing and Information Systems

Ask any student at the Singapore Management University (SMU) to name one of the most practical and useful courses offered by the university. The answer would inevitably include CAT. CAT stands for the "Computer as an Analysis Tool" course. Originally based on a course of the same title offered by the Wharton Business School, the focus of CAT was shifted to provide business students the essential practical skills and necessary "real-world" exposure to better use personal computers for resolving business problems. The course is basically centered on using the Excel spreadsheet to work on ambiguous ill-defined problems.

Multi-Task Transfer Learning For Weakly-Supervised Relation Extraction, Jing Jiang

Research Collection School Of Computing and Information Systems

Creating labeled training data for relation extraction is expensive. In this paper, we study relation extraction in a special weakly-supervised setting when we have only a few seed instances of the target relation type we want to extract but we also have a large amount of labeled instances of other relation types. Observing that different relation types can share certain common structures, we propose to use a multi-task learning method coupled with human guidance to address this weakly-supervised relation extraction problem. The proposed framework models the commonality among different relation types through a shared weight vector, enables knowledge learned from …

Ssnetviz: A Visualization Engine For Heterogeneous Semantic Social Networks, Ee Peng Lim, Maureen Maureen, Nelman Lubis Ibrahim, Aixin Sun, Anwitaman Datta, Kuiyu Chang

Research Collection School Of Computing and Information Systems

SSnetViz is an ongoing research to design and implement a visualization engine for heterogeneous semantic social networks. A semantic social network is a multi-modal network that contains nodes representing di®erent types of people or object entities, and edges representing relationships among them. When multiple heterogeneous semantic social networks are to be visualized together, SSnetViz provides a suite of functions to store heterogeneous semantic social networks, to integrate them for searching and analysis. We will illustrate these functions using social networks related to terrorism research, one crafted by domain experts and another from Wikipedia.

Optimal-Location-Selection Query Processing In Spatial Databases, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li

Research Collection School Of Computing and Information Systems

This paper introduces and solves a novel type of spatial queries, namely, Optimal-Location-Selection (OLS) search, which has many applications in real life. Given a data object set D_A, a target object set D_B, a spatial region R, and a critical distance d_c in a multidimensional space, an OLS query retrieves those target objects in D_B that are outside R but have maximal optimality. Here, the optimality of a target object b \in D_B located outside R is defined as the number of the data objects from D_A that are inside R and meanwhile have their distances to b not exceeding …

Scalable Verification For Outsourced Dynamic Databases, Hwee Hwa Pang, Jilian Zhang, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

Query answers from servers operated by third parties need to be verified, as the third parties may not be trusted or their servers may be compromised. Most of the existing authentication methods construct validity proofs based on the Merkle hash tree (MHT). The MHT, however, imposes severe concurrency constraints that slow down data updates. We introduce a protocol, built upon signature aggregation, for checking the authenticity, completeness and freshness of query answers. The protocol offers the important property of allowing new data to be disseminated immediately, while ensuring that outdated values beyond a pre-set age can be detected. We also …

A Distributed Spatial Index For Error-Prone Wireless Data Broadcast, Baihua Zheng, Wang-Chien Lee, Ken C. K. Lee, Dik Lun Lee, Min Shao

Research Collection School Of Computing and Information Systems

Information is valuable to users when it is available not only at the right time but also at the right place. To support efficient location-based data access in wireless data broadcast systems, a distributed spatial index (called DSI) is presented in this paper. DSI is highly efficient because it has a linear yet fully distributed structure that naturally shares links in different search paths. DSI is very resilient to the error-prone wireless communication environment because interrupted search operations based on DSI can be resumed easily. It supports search algorithms for classical location-based queries such as window queries and kNN queries …

On Efficient Mutual Nearest Neighbor Query Processing In Spatial Databases, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li

Research Collection School Of Computing and Information Systems

This paper studies a new form of nearest neighbor queries in spatial databases, namely, mutual nearest neighbour (MNN) search. Given a set D of objects and a query object q, an MNN query returns from D, the set of objects that are among the k₁ (≥ 1) nearest neighbors (NNs) of q; meanwhile, have q as one of their k₂(≥ 1) NNs. Although MNN queries are useful in many applications involving decision making, data mining, and pattern recognition, it cannot be efficiently handled by existing spatial query processing approaches. In this paper, we present …

Brain Tumor Progression Assessment Using Multiple Mri Volumes, Yufei Shen

Electrical & Computer Engineering Theses & Dissertations

Predicting and assessing tumor progression is important in brain tumor treatment. We attempt to use machine learning techniques to achieve consistency in assessing brain tumor progression. This thesis presents a prediction method of brain tumor progression by exploring a large MR database, which contains two patients ' complete records covering all their visits in the past two years. All ten MRI series, namely, apparent diffusion coefficient (ADC) , diffusion tensor imaging (DTI) , fractional anisotropy (FA), fluid attenuated inversion recovery (FLAIR), max eigenvalue (MAX), mid eigenvalue (MID), min eigenvalue (MIN) , post-contrast T₁-weighted, T₁- weighted, and …

Continuous Obstructed Nearest Neighbor Queries In Spatial Databases, Yunjun Gao, Baihua Zheng

Research Collection School Of Computing and Information Systems

In this paper, we study a novel form of continuous nearest neighbor queries in the presence of obstacles, namely continuous obstructed nearest neighbor (CONN) search. It considers the impact of obstacles on the distance between objects, which is ignored by most of spatial queries. Given a data set P, an obstacle set O, and a query line segment q in a two-dimensional space, a CONN query retrieves the nearest neighbor of each point on q according to the obstructed distance, i.e., the shortest path between them without crossing any obstacle. We formulate CONN search, analyze its unique properties, and develop …

Spatial Cloaking Revisited: Distinguishing Information Leakage From Anonymity, Kar Way Tan, Yimin Lin, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

Location-based services (LBS) are receiving increasing popularity as they provide convenience to mobile users with on-demand information. The use of these services, however, poses privacy issues as the user locations and queries are exposed to untrusted LBSs. Spatial cloaking techniques provide privacy in the form of k-anonymity; i.e., they guarantee that the (location of the) querying user u is indistinguishable from at least k-1 others, where k is a parameter specified by u at query time. To achieve this, they form a group of k users, including u, and forward their minimum bounding rectangle (termed anonymzing spatial region, ASR) to …

Compositemap: A Novel Framework For Music Similarity Measure, Bingjun Zhang, Jialie Shen, Qiaoliang Xiang, Ye Wang

Research Collection School Of Computing and Information Systems

With the continuing advances in data storage and communication technology, there has been an explosive growth of music information from different application domains. As an effective technique for organizing, browsing, and searching large data collections, music information retrieval is attracting more and more attention. How to measure and model the similarity between different music items is one of the most fundamental yet challenging research problems. In this paper, we introduce a novel framework based on a multimodal and adaptive similarity measure for various applications. Distinguished from previous approaches, our system can effectively combine music properties from different aspects into a …

The Wisdom Of The Few: A Collaborative Filtering Approach Based On Expert Opinions From The Web, Xavier Amatriain, Neal Lathia, Josep M. Pujol, Haewoon Kwak, Nuria. Oliver

Research Collection School Of Computing and Information Systems

Nearest-neighbor collaborative filtering provides a successful means of generating recommendations for web users. However, this approach suffers from several shortcomings, including data sparsity and noise, the cold-start problem, and scalability. In this work, we present a novel method for recommending items to users based on expert opinions. Our method is a variation of traditional collaborative filtering: rather than applying a nearest neighbor algorithm to the user-rating data, predictions are computed using a set of expert neighbors from an independent dataset, whose opinions are weighted according to their similarity to the user. This method promises to address some of the weaknesses …

Analysis Of Partial Discharge Pulse Height Distribution Parameters, Vinay N. Nimbole

Electrical & Computer Engineering Theses & Dissertations

Partial Discharges (PD) have been traditionally used to assess the state of any insulation system and its remnant life. In earlier work, Perspex (PMMA) samples with a needle plane gap have been aged with AC voltage. Their tree growth was monitored simultaneously by collecting PD at regular intervals of time and taking microphotographs in real time without interrupting the aging voltage. The obtained partial discharge pulse amplitude records were clustered together into groups of class intervals. The sequence of PD pulse height records was quantified as a time series of shape (η), and scale (σ) parameters of a Weibull distribution. …

Understanding Terrorism Through The Use Of Gis - Crj 346: Terrorism And Society, Joseph F. Ryan, Ph.D., Daniel Farkas, Ph.D.

Cornerstone 3 Reports : Interdisciplinary Informatics

This is a study that concentrates on methodologies on collecting and analysis of intelligence information.

Sample Size Estimation While Controlling False Discovery Rate For Microarray Experiments Using The Ssize.Fdr Package, Megan Orr, Peng Liu

The R Journal

Microarray experiments are becoming more and more popular and critical in many biological disciplines. As in any statistical experiment, appropriate experimental design is essential for reliable statistical inference, and sample size has a crucial role in experimental design. Because microarray experiments are rather costly, it is important to have an adequate sample size that will achieve a desired power with out wasting resources.

For a given microarray data set, thousands of hypotheses, one for each gene, are simultaneously tested. Storey and Tibshirani (2003) argue that con trolling false discovery rate (FDR) is more reasonable and more powerful than controlling family-wise …

Emd: A Package For Empirical Mode Decomposition And Hilbert Spectrum, Donghoh Kim, Hee-Seok Oh

The R Journal

The concept of empirical mode decomposition (EMD)and the Hilber tspectrum (HS) has been developed rapidly in many disciplines of science and engineering since Huang et al. (1998) invented EMD. The key feature of EMD is to decompose a signal into so-called intrinsic mode function (IMF). Further more, the Hilbert spectral analysis of intrinsic mode functions provides frequency information evolving with time and quantifies the amount of variation due to oscillation at different time scales and time locations. In this article,we introduce an R package called EMD (KimandOh, 2008) that performs one and two-dimensional EMD and HS.

Modeling Without Data Using Expert Opinion, Vincent Goulet, Michel Jacques, Mathieu Pigeon

The R Journal

The expert package provides tools to create and manipulate empirical statistical models using expert opinion (or judgment). Here, the latter expression refers to a specific body of techniques to elicit the distribution of a random variable when data is scarce or unavailable. Opinions on the quantiles of the distribution are sought from experts in the field and aggregated into a final estimate. The package supports aggregation by means of the Cooke, Mendel–Sheridan and predefined weights models.

We do not mean to give a complete introduction to the theory and practice of expert opinion elicitation in this paper. However, for the …

Admit, David Ardia, Lennart F. Hoogerheide, Herman K. Van Dijk

The R Journal

This note presents the package AdMit (Ardia et al., 2008, 2009), an R implementation of the adaptive mixture of Student-t distributions (AdMit) procedure developed by Hoogerheide (2006); see also Hoogerheide et al. (2007); Hoogerheide and van Dijk (2008). The AdMit strategy consists of the construction of a mixture of Student-t distributions which approximates a target distribution of interest. The fitting procedure relies only on a kernel of the tar get density, so that the normalizing constant is not required. In a second step, this approximation is used as an importance function in importance sampling or as a candidate density in …

The Hwriter Package: Composing Html Documents With R Objects, Gregoire Pau, Wolfgang Huber

The R Journal

HTML documents are structured documents made of diverse elements such as paragraphs, sections, columns, figures and tables organized in a hierarchical layout. Combination of HTML documents and hyperlinking is useful to report analysis results; for example, in the package array Quality Metrics (Kauffmannetal., 2009), estimating the quality of mi croarray data sets and cellHTS2(Boutrosetal.,2006), performing the analysis of cell-based screens.

There are several tools for exporting data from R into HTML documents. The package R2HTML is able to render a large diversity of R objects in HTML but does not easily support combining them in a structured layout and …

Collaborative Software Development Using R-Forge, Stefan Theußl, Achim Zeileis

The R Journal

Open source software (OSS) is typically created in a decentralized self-organizing process by a community of developers having the same or similar interests (see the famous essay by Raymond, 1999). A key factor for the success of OSS over the last two decades is the Internet: Developers who rarely meet face-to-face can employ new means of communication, both for rapidly writing and deploying software (in the spirit of Linus Torvald’s “release early, release often paradigm”). Therefore, many tools emerged that assist a collaborative software development process, including in particular tools for source code management (SCM) and version control.

In the …

Facets Of R, John M. Chambers

The R Journal

We are seeing today a widespread, and welcome, tendency for non-computer-specialists among statisticians and others to write collections of R functions that organize and communicate their work. Along with the flood of software sometimes comes an attitude that one need-only-learn, or teach, a sort of basic how-to-write-the-function level of R programming, beyond which most of the detail is unimportant or can be absorbed without much discussion. As delusions go, this one is not very objectionable if it encourages participation. Nevertheless, a delusion it is. In fact, functions are only one of a variety of important facets that R has acquired …

Easier Parallel Computing In R With Snowfall And Sfcluster, Jochen Knaus, Christine Porzelius, Harald Binder, Guido Schwarzer

The R Journal

Many statistical analysis tasks in areas such as bioinformatics are computationally very intensive, while lots of them rely on embarrassingly parallel computations (Grama et al., 2003). Multiple computers or even multiple processor cores on standard desktop computers, which are widespread nowadays, can easily contribute to faster analyses.

R itself does not allow parallel execution. There are some existing solutions for R to distribute calculations over many computers — a cluster — for ex ample Rmpi, rpvm, snow, nws or papply. However these solutions require the user to setup and manage the cluster on his own and …

The R Journal (June 2009) 1(1): Complete Issue, The R Foundation

The R Journal

Contributed Research Articles

Facets of R, John M. Chambers

Collaborative Software Development Using R-Forge, Stefan Theußl and Achim Zeileis

Drawing Diagrams with R, Paul Murrell

The hwriter package: Composing HTML Documents with R Objects, Gregoire Pau and Wolfgang Huber

AdMit, David Ardia, Lennart F. Hoogerheide, and Herman K. van Dijk

expert: Modeling Without Data Using Expert Opinion, Vincent Goulet, Michel Jacques, and Mathieu Pigeon

New Numerical Algorithm for Multivariate Normal Probabilities in Package mvtnorm, Xuefei Mi, Tetsuhisa Miwa, and Torsten Hothorn

EMD: A Package for Empirical Mode Decomposition and Hilbert Spectrum, Donghoh Kim, and Hee-Seok Oh

Sample Size Estimation while …