Computer Sciences Commons^™

The Rwiener Package: An R Package Providing Distribution Functions For The Wiener Diffusion Model, Dominik Wabersich, Joachim Vandekerckhove

The R Journal

We present the RWiener package that provides R functions for the Wiener diffusion model. The core of the package are the four distribution functions dwiener, pwiener, qwiener and rwiener, which use up-to-date methods, implemented in C, and provide fast and accurate computation of the density, distribution, and quantile function, as well as a random number generator for the Wiener diffusion model. We used the typical Wiener diffusion model with four parameters: boundary separation, non-decision time, initial bias and drift rate parameter. Beyond the distribution functions, weprovide extended likelihood-based functions that can be used for parameter estimation and model selection. The …

Fully Differential Cross Sections For Electron-Impact Excitation-Ionization Of Aligned D₂, Esam Ali, A. L. Harris, J. Lower, E. Weigold, Chuang-Gang Ning, Don H. Madison

Physics Faculty Research & Creative Works

We examine fully differential cross sections for 176 eV electron-impact dissociative excitation-ionization of orientated D2 for transitions to final ion states 2sσ_g, 2pσ_u, and 2pπ_u. In previous work [Phys. Rev. A 88, 062705 (2013)PLRAAN1050-294710.1103/PhysRevA.88.062705], we calculated these cross sections using the molecular four-body distorted wave (M4DW) method with the ground-state D2 wave function being approximated by a product of two Dyson 1s-type orbitals. The theoretical results were compared with experimental measurements for five different orientations of the target molecule (four in the scattering plane and one perpendicular to the scattering plane). For the unresolved …

Computational Analysis Of Gene Expression And Connectivity Patterns In The Convoluted Structures Of Mouse Cerebellum, Tao Zeng

Computer Science Theses & Dissertations

One significant difference between evolved mammalian brains and other species is that mammalian brains exhibit increasingly convoluted structures in the cerebral cortex. Groove and ridge shaped structures named gyri and sulci expand surface area of cerebral cortex, making more functions possible. Prior studies using neuroimaging techniques such as dMRI and DTI have revealed that neural fibers are heavily connected to gyri comparing to those connected to sulci, such macro-scale experiments indicates that gyri are involved in large scale information processing while sulci process information locally. However, molecular and cellar level evidences, namely, gene expression pattern and its resulting neuronal connectivity …

Theoretical Triple-Differential Cross Sections Of A Methane Molecule By A Proper-Average Method, Hari Chaluvadi, C. G. Ning, Don H. Madison

Physics Faculty Research & Creative Works

For the last few years, our group has calculated cross sections for electron-impact ionization of molecules using the molecular three-body distorted-wave approximation coupled with the orientation-averaged molecular orbital (OAMO) approximation. This approximation was very successful for calculating ionization cross sections for hydrogen molecules and to a lesser extent nitrogen molecules. Recently we used the approximation to calculate single ionization cross sections for the 1t₂ state of methane (CH₄) and we found major discrepancies with the experimental data. Here we investigate the validity of the OAMO approximation by calculating cross sections that have been properly averaged over all …

Ar-Miner: Mining Informative Reviews For Developers From Mobile App Marketplace, Ning Chen, Jialiu Lin, Steven C. H. Hoi, Xiaokui Xiao, Boshen Zhang

Research Collection School Of Computing and Information Systems

With the popularity of smartphones and mobile devices, mobile application (a.k.a. “app”) markets have been growing exponentially in terms of number of users and downloads. App developers spend considerable effort on collecting and exploiting user feedback to improve user satisfaction, but suffer from the absence of effective user review analytics tools. To facilitate mobile app developers discover the most “informative” user reviews from a large and rapidly increasing pool of user reviews, we present “AR-Miner” — a novel computational framework for App Review Mining, which performs comprehensive analytics from raw user reviews by (i) first extracting informative user reviews by …

Air Indexing For On-Demand Xml Data Broadcast, Weiwei Sun, Rongrui Qin, Jinjin Wu, Baihua Zheng

Research Collection School Of Computing and Information Systems

XML data broadcast is an efficient way to disseminate semi-structured information in wireless mobile environments. In this paper, we propose a novel two-tier index structure to facilitate the access of XML document in an on-demand broadcast system. It provides the clients with an overall image of all the XML documents available at the server side and hence enables the clients to locate complete result sets accordingly. A pruning strategy is developed to cut down the index size and a two-tier structure is proposed to further remove any redundant information. In addition, two index distribution strategies, namely naive distribution and partial …

On Efficient Reverse Skyline Query Processing, Yunjun Gao, Qing Liu, Baihua Zheng, Gang Chen

Research Collection School Of Computing and Information Systems

Given a D-dimensional data set P and a query point q, a reverse skyline query (RSQ) returns all the data objects in P whose dynamic skyline contains q. It is important for many real life applications such as business planning and environmental monitoring. Currently, the state-of-the-art algorithm for answering the RSQ is the reverse skyline using skyline approximations (RSSA) algorithm, which is based on the precomputed approximations of the skylines. Although RSSA has some desirable features, e.g., applicability to arbitrary data distributions and dimensions, it needs for multiple accesses of the same nodes, incurring redundant I/O and CPU costs. In …

Graph-Based Semi-Supervised Learning: Realizing Pointwise Smoothness Probabilistically, Yuan Fang, Kevin Chen-Chuan Chang, Hady W. Lauw

Research Collection School Of Computing and Information Systems

As the central notion in semi-supervised learning, smoothness is often realized on a graph representation of the data. In this paper, we study two complementary dimensions of smoothness: its pointwise nature and probabilistic modeling. While no existing graph-based work exploits them in conjunction, we encompass both in a novel framework of Probabilistic Graph-based Pointwise Smoothness (PGP), building upon two foundational models of data closeness and label coupling. This new form of smoothness axiomatizes a set of probability constraints, which ultimately enables class prediction. Theoretically, we provide an error and robustness analysis of PGP. Empirically, we conduct extensive experiments to show …

Hydrographic Surface Modeling Through A Raster Based Spline Creation Method, Julie G. Alexander

LSU New Orleans Theses and Dissertations

The United States Army Corp of Engineers relies on accurate and detailed surface models for various construction projects and preventative measures. To aid in these efforts, it is necessary to work for advancements in surface model creation. Current methods for model creation include Delaunay triangulation, raster grid interpolation, and Hydraulic Spline grid generation. While these methods produce adequate surface models, attempts for improved methods can still be made.

A method for raster based spline creation is presented as a variation of the Hydraulic Spline algorithm. By implementing Hydraulic Splines in raster data instead of vector data, the model creation process …

A Uniform Database Of Teleseismic Shear Wave Splitting Measurements For The Western And Central United States, Kelly H. Liu, Ahmed Elsheikh, Awas Lemnifi, Uranbaigal Purevsuren, Melissa Ray, Hesham Refayee, Bin B. Yang, Youqiang Yu, Stephen S. Gao

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

We present a shear wave splitting (SWS) database for the western and central United States as part of a lasting effort to build a uniform SWS database for the entire North America. The SWS measurements were obtained by minimizing the energy on the transverse component of the PKS, SKKS, and SKS phases. Each of the individual measurements was visually checked to ensure quality. This version of the database contains 16,105 pairs of splitting parameters. The data used to generate the parameters were recorded by 1774 digital broadband seismic stations over the period of 1989-2012, and represented all the available data …

Generating Combinatorial Objects- A New Perspective, Alexander Chizoma Nwala

Computer Science Theses & Dissertations

Combinatorics is the science of "possibilities." This definition, while not formal is a fair statement because all too often, in order to gain insight into the solution of many counting problems, we explore the possibilities. In some cases we seek to know how many options, while in other cases we seek to enumerate or list the options. Irrespective of the scenario, combinatorics plays a vital role today. In many instances such as exploring the options for choosing a new password for a combination lock, we employ combinatorics. In considering the possible license plate permutations for a state, or to see …

Canaries In The Urban Data Mine: Analytics For Smarter City Life, Robert J. Kauffman

Research Collection School Of Computing and Information Systems

Technology-based sensors and data analytics have created unprecendented levels of informedness for consumers, corporations, the public and government agencies. The information they generated provides a basis for smarter cities and more sustainable urban living.

How Many Eyeballs Does A Bug Need? An Empirical Validation Of Linus' Law, Subhajit Datta, Proshanta Sarkar, Sutirtha Das, Sonu Sreshtha, Prasanth Lade, Subhashis Majumder

Research Collection School Of Computing and Information Systems

Linus’ Law reflects on a key characteristic of open source software development: developers’ tendency to closely work together in the bug resolution process. In this paper we empirically examine Linus’ Law using a data-set of 1,000+ Android bugs, owned by 70+ developers. Our results indicate that encouraging developers to work closely with one another has nuanced implications; while one form of contact may help reduce bug resolution time, another form can have quite the opposite effect. We present statistically significant evidence in support of our results and discuss their relevance at the individual and organizational levels.

New Pod Error Expressions, Error Bounds, And Asymptotic Results For Reduced Order Model Of Parabolic Pdes, John R. Singler

Mathematics and Statistics Faculty Research & Creative Works

The derivations of existing error bounds for reduced order models of time varying partialdi erential equations (PDEs) constructed using proper orthogonal decomposition (POD) haverelied on bounding the error between the POD data and various POD projections of that data.Furthermore, the asymptotic behavior of the model reduction error bounds depends on theasymptotic behavior of the POD data approximation error bounds. We consider time varyingdata taking values in two di erent Hilbert spacesHandV, withVH, and prove exactexpressions for the POD data approximation errors considering four di erent POD projectionsand the two di erent Hilbert space error norms. Furthermore, the exact error expressions …

Seismic Anisotropy And Subduction-Induced Mantle Fabrics Beneath The Arabian And Nubian Plates Adjacent To The Red Sea, Ahmed A. Elsheikh, Stephen S. Gao, Kelly H. Liu, Abdelnasser A. Mohamed, Youqiang Yu, Raafat E. Fat-Helbary

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

For most continental areas, the mechanisms leading to mantle fabrics responsible for the observed anisotropy remain ambiguous, partially due to the lack of sufficient spatial coverage of reliable seismological observations. Here we report the first joint analysis of shear-wave splitting measurements obtained at stations on the Arabian and Nubian Plates adjacent to the Red Sea. More than 1100 pairs of high-quality splitting parameters show dominantly N-S fast orientations at all 47 stations and larger-than-normal splitting times beneath the Afro-Arabian Dome (AAD). The uniformly N-S fast orientations and large splitting times up to 1.5 s are inconsistent with significant contributions from …

Automatic Objects Removal For Scene Completion, Jianjun Yang, Yin Wang, Honggang Wang, Kun Hua, Wei Wang, Ju Shen

Computer Science Faculty Publications

With the explosive growth of Web-based cameras and mobile devices, billions of photographs are uploaded to the Internet. We can trivially collect a huge number of photo streams for various goals, such as 3D scene reconstruction and other big data applications. However, this is not an easy task due to the fact the retrieved photos are neither aligned nor calibrated. Furthermore, with the occlusion of unexpected foreground objects like people, vehicles, it is even more challenging to find feature correspondences and reconstruct realistic scenes. In this paper, we propose a structure-based image completion algorithm for object removal that produces visually …

Multi-Threaded Automatic Integration Using Openmp And Cuda, Rida Assaf

Masters Theses

Problems in many areas give rise to computationally expensive integrals that beg the need of efficient techniques to solve them, e.g., in computational finance for the modeling of cash flows; for the computation of Feynman loop integrals in high energy physics; and in stochastic geometry with applications to computer graphics.

We demonstrate feasible numerical approaches in the framework of the PARINT multivariate integration package. The parallel environment is provided by the cluster of the High Performance Computational Science (HPCS) laboratory, with 22 (16- or 32-core) nodes, NVIDIA GPUs, and Intel Xeon Phi coprocessors.

Monte Carlo integration is implemented in CUDA …

Computational Pain Quantification And The Effects Of Age, Gender, Culture And Cause, Colin R. Ostberg

Master's Theses (2009 -)

Chronic pain affects more than 100 million Americans and more than 1.5 billion people worldwide. Pain is a multidimensional construct, expressed through a variety of means. Facial expressions are one such type of pain expression. Automatic facial expression recognition, and in particular pain expression recognition, are fields that have been studied extensively. However, nothing has explored the possibility of an automatic pain quantification algorithm, able to output pain levels based upon a facial image. Developed for a remote monitoring context, a computational pain quantification algorithm has been developed and validated by two distinct sets of data. The second set of …

Ubiquitous Data-Centric Sensor Networks, Ting Yang, Peng Yung Woo, Zhaoxia Wang, Javid Taheri, Hoong Chor Chin, Guaqiang Hu

Research Collection School Of Computing and Information Systems

Ubiquitous data-centric sensor networks (U-DCSN) are a new integrated science and technology, which focus on data instead of individual sensor nodes. The network, as a dynamic database system, can accurately acquire data, perform high-performance processing of big data, and effectively access data from different users/actuators. Due this characteristic, U-DCSN hold huge potentials on service improvement in a wide range of applications and have attracted significant attention in recent years, for example, mobile cloud and consumer electronics. The modern mobile cloud, comprised of mobile devices (smart phones, tablets, and embedded sensor nodes), provides unlimited information resources, putting “cloud into a pocket.” …

On Modeling Community Behaviors And Sentiments In Microblogging, Tuan Anh Hoang, William Cohen, Ee Peng Lim

Research Collection School Of Computing and Information Systems

In this paper, we propose the CBS topic model, a probabilistic graphical model, to derive the user communities in microblogging networks based on the sentiments they express on their generated content and behaviors they adopt. As a topic model, CBS can uncover hidden topics and derive user topic distribution. In addition, our model associates topic-specific sentiments and behaviors with each user community. Notably, CBS has a general framework that accommodates multiple types of behaviors simultaneously. Our experiments on two Twitter datasets show that the CBS model can effectively mine the representative behaviors and emotional topics for each community. We also …

On Finding The Point Where There Is No Return: Turning Point Mining On Game Data, Wei Gong, Ee Peng Lim, Feida Zhu, Achananuparp Palakorn, David Lo

Research Collection School Of Computing and Information Systems

Gaming expertise is usually accumulated through playing or watching many game instances, and identifying critical moments in these game instances called turning points. Turning point rules (shorten as TPRs) are game patterns that almost always lead to some irreversible outcomes. In this paper, we formulate the notion of irreversible outcome property which can be combined with pattern mining so as to automatically extract TPRs from any given game datasets. We specifically extend the well-known PrefixSpan sequence mining algorithm by incorporating the irreversible outcome property. To show the usefulness of TPRs, we apply them to Tetris, a popular game. We mine …

Modeling Contextual Agreement In Preferences, Ha Loc Do, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Personalization, or customizing the experience of each individual user, is seen as a useful way to navigate the huge variety of choices on the Web today. A key tenet of personalization is the capacity to model user preferences. The paradigm has shifted from that of individual preferences, whereby we look at a user's past activities alone, to that of shared preferences, whereby we model the similarities in preferences between pairs of users (e.g., friends, people with similar interests). However, shared preferences are still too granular, because it assumes that a pair of users would share preferences across all items. We …

Recommending Investors For Crowdfunding Projects, Jisun An, Daniele Quercia, Jon Crowcroft

Research Collection School Of Computing and Information Systems

To bring their innovative ideas to market, those embarking in new ventures have to raise money, and, to do so, they have often resorted to banks and venture capitalists. Nowadays, they have an additional option: that of crowdfunding. The name refers to the idea that funds come from a network of people on the Internet who are passionate about supporting others' projects. One of the most popular crowdfunding sites is Kickstarter. In it, creators post descriptions of their projects and advertise them on social media sites (mainly Twitter), while investors look for projects to support. The most common reason for …

Computational Study Of The Rovibrational Spectrum Of Co₂-Cs₂, James Corgan Brown, Xiao-Gang Wang, Tucker Carrington Jr., Garry S. Grubbs, Richard Dawes

Chemistry Faculty Research & Creative Works

A new intermolecular potential energy surface, rovibrational transition frequencies, and line strengths are computed for CO₂-CS₂. the potential is made by fitting energies obtained from explicitly correlated coupled-cluster calculations using an interpolating moving least squares method. the rovibrational Schrödinger equation is solved with a symmetry-adapted Lanczos algorithm and an uncoupled product basis set. All four intermolecular coordinates are included in the calculation. in agreement with previous experiments, the global minimum of the potential energy surface (PES) is cross shaped. the PES also has slipped-parallel minima. Rovibrational wavefunctions are localized in the cross minima and the slipped-parallel …

Phonon Density Of States And Anharmonicity Of Uo₂, Judy W. Pang, Aleksandr V. Chernatynskiy, Bennett C. Larson, William J. Buyers, Douglas L. Abernathy, Kenneth J. Mcclellan, Simon R. Phillpot

Physics Faculty Research & Creative Works

Phonon density of states (PDOS) measurements have been performed on polycrystalline UO₂ at 295 and 1200 K using time-of-flight inelastic neutron scattering to investigate the impact of anharmonicity on the vibrational spectra and to benchmark ab initio PDOS simulations performed on this strongly correlated Mott insulator. Time-of-flight PDOS measurements include anharmonic linewidth broadening, inherently, and the factor of ~7 enhancement of the oxygen spectrum relative to the uranium component by the increased neutron sensitivity to the oxygen-dominated optical phonon modes. The first-principles simulations of quasiharmonic PDOS spectra were neutron weighted and anharmonicity was introduced in an approximate way by …

Seismic Anisotropy And Mantle Flow Beneath The Northern Great Plains Of North America, Bin B. Yang, Stephen S. Gao, Kelly H. Liu, Ahmed A. Elsheikh, Awad A. Lemnifi, Hesham A. Refayee, Youqiang Yu

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

A diverse set of tectonic features and the recent availability of high-quality broadband seismic data from the USArray and other stations on the northern Great Plains of North America provide a distinct opportunity to test different anisotropy-forming mechanisms. A total of 4138 pairs of well-defined splitting parameters observed at 445 stations show systematic spatial variations of anisotropic characteristics. Azimuthally invariant fast orientations subparallel to the absolute plate motion (APM) direction are observed at most of the stations on the Superior Craton and the southern Yavapai province, indicating that a single layer of anisotropy with a horizontal axis of symmetry is …

Receiver Function Constraints On Crustal Seismic Velocities And Partial Melting Beneath The Red Sea Rift And Adjacent Regions, Afar Depression, Cory A. Reed, Sattam Almadani, Stephen S. Gao, Ahmed A. Elsheikh, Solomon Cherie, Mohamed G. Abdel Salam, Allison K. Thurmond, Kelly H. Liu

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

The Afar Depression is an ideal locale for the investigation of crustal processes involved in the transition from continental rifting to oceanic spreading. To provide relatively high resolution images of the crust beneath the Red Sea rift (RSR) represented by the Tendaho graben in the Afar Depression, we deployed an array of 18 broadband seismic stations in 2010 and 2011. Stacking of about 2300 receiver functions from the 18 and several nearby stations along the ~200 km long array reveals an average crustal thickness of 22 ± 4 km, ranging from ~17 km near the RSR axis to 30 km …

Retrieval-Based Face Annotation By Weak Label Regularized Local Coordinate Coding, Dayong Wang, Steven C. H. Hoi, Ying He, Jianke Zhu, Mei Tao, Jiebo Luo

Research Collection School Of Computing and Information Systems

Auto face annotation, which aims to detect human faces from a facial image and assign them proper human names, is a fundamental research problem and beneficial to many real-world applications. In this work, we address this problem by investigating a retrieval-based annotation scheme of mining massive web facial images that are freely available over the Internet. In particular, given a facial image, we first retrieve the top n similar instances from a large-scale web facial image database using content-based image retrieval techniques, and then use their labels for auto annotation. Such a scheme has two major challenges: 1) how to …

On Predicting User Affiliations Using Social Features In Online Social Networks, Minh Thap Nguyen

Dissertations and Theses Collection (Open Access)

User profiling such as user affiliation prediction in online social network is a challenging task, with many important applications in targeted marketing and personalized recommendation. The research task here is to predict some user affiliation attributes that suggest user participation in different social groups.

Online Feature Selection And Its Applications, Jialei Wang, Peilin Zhao, Steven C. H. Hoi, Rong Jin

Research Collection School Of Computing and Information Systems

Feature selection is an important technique for data mining. Despite its importance, most studies of feature selection are restricted to batch learning. Unlike traditional batch learning methods, online learning represents a promising family of efficient and scalable machine learning algorithms for large-scale applications. Most existing studies of online learning require accessing all the attributes/features of training instances. Such a classical setting is not always appropriate for real-world applications when data instances are of high dimensionality or it is expensive to acquire the full set of attributes/features. To address this limitation, we investigate the problem of online feature selection (OFS) in …