Numerical Analysis and Scientific Computing Commons^™

Manipulation Of Discrete Random Variables With Discreterv, Eric Hare, Andreas Buja, Heike Hofmann

The R Journal

A prominent issue in statistics education is the sometimes large disparity between the theoretical and the computational coursework. discreteRV is an R package for manipulation of discrete random variables which uses clean and familiar syntax similar to the mathematical notation in introductory probability courses. The package offers functions that are simple enough for users with little experience with statistical programming, but has more advanced features which are suitable for a large number of more complex applications. In this paper, we introduce and motivate discreteRV, describe its functionality, and provide reproducible examples illustrating its use.

The Complex Multivariate Gaussian Distribution, Robin K.S. Hankin

The R Journal

Here I introduce package cmvnorm, a complex generalization of the mvtnorm package. A complex generalization of the Gaussian process is suggested and numerical results presented using the package. An application in the context of approximating the Weierstrass-function using a complex Gaussian process is given.

Emerging Criticality In The Disordered Three-Color Ashkin-Teller Model, Qiong Zhu, Xin Wan, Rajesh Narayanan, José A. Hoyos, Thomas Vojta

Physics Faculty Research & Creative Works

We study the effects of quenched disorder on the first-order phase transition in the two-dimensional three-color Ashkin-Teller model by means of large-scale Monte Carlo simulations. We demonstrate that the first-order phase transition is rounded by the disorder and turns into a continuous one. Using a careful finite-size-scaling analysis, we provide strong evidence for the emerging critical behavior of the disordered Ashkin-Teller model to be in the clean two-dimensional Ising universality class, accompanied by universal logarithmic corrections. This agrees with perturbative renormalization-group predictions by Cardy. As a byproduct, we also provide support for the strong-universality scenario for the critical behavior of …

Erratum: Theoretical And Experimental (E,2e) Study Of Electron-Impact Ionization Of Laser-Aligned Mg Atoms [Physical Review A 90, 062707 (2014)], Sadek Amami, Andrew J. Murray, Al Stauffer, Kate Nixon, Gregory Armstrong, James Colgan, Don H. Madison

Physics Faculty Research & Creative Works

We have recently reported a theoretical and experimental study of electron-impact ionization of laser-aligned magnesium. Results were presented for both ionization of the ground state, as well as for laser-aligned atoms in the 3p state. For ionization from the 3p state, theoretical results were presented using the distorted wave Born (DWBA) and three-body distorted wave (3DW) approximations. Unfortunately, after publication we learned that the theoretical results were incorrect due to one of the arrays in the computer code dimensioned too small. The figures affected by this error are Figs. 3–5 in the original paper. The present Figs. 3–5 …

Towards A Global Model Of Spin-Orbit Coupling In The Halocarbenes, Silver Nyambo, Cyrus Karshenas, Scott A. Reid, Phalgun Lolur, Richard Dawes

Chemistry Faculty Research & Creative Works

We report a global analysis of spin-orbit coupling in the mono-halocarbenes, CH(D)X, where X = Cl, Br, and I. These are model systems for examining carbene singlet-triplet energy gaps and spin-orbit coupling. Over the past decade, rich data sets collected using single vibronic level emission spectroscopy and stimulated emission pumping spectroscopy have yielded much information on the ground vibrational level structure and clearly demonstrated the presence of perturbations involving the low-lying triplet state. To model these interactions globally, we compare two approaches. First, we employ a diabatic treatment of the spin-orbit coupling, where the coupling matrix elements are written in …

Should We Use The Sample? Analyzing Datasets Sampled From Twitter's Stream Api, Yazhe Wang, Jamie Callan, Baihua Zheng

Research Collection School Of Computing and Information Systems

Researchers have begun studying content obtained from microblogging services such as Twitter to address a variety of technological, social, and commercial research questions. The large number of Twitter users and even larger volume of tweets often make it impractical to collect and maintain a complete record of activity; therefore, most research and some commercial software applications rely on samples, often relatively small samples, of Twitter data. For the most part, sample sizes have been based on availability and practical considerations. Relatively little attention has been paid to how well these samples represent the underlying stream of Twitter data. To fill …

Methods And Systems For Biclustering Algorithm, Donald C. Wunsch, Rui Xu, Sejun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

Methods and systems for improved unsupervised learning are described. The unsupervised learning can consist of biclustering a data set, e.g., by biclustering subsets of the entire data set. In an example, the biclustering does not include feeding know and proven results into the biclustering methodology or system. A hierarchical approach can be used that feeds proven clusters back into the biclustering methodology or system as the input. Data that does not cluster may be discarded. Thus, a very large unknown data set can be acted on to learn about the data. The system is also amenable to parallelization.

Determining Crustal Structure Beneath Seismic Stations Overlying A Low-Velocity Sedimentary Layer Using Receiver Functions, Youqiang Yu, Jianguo Song, Kelly H. Liu, Stephen S. Gao

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

The receiver function (RF) technique has been widely applied to investigate crustal and mantle layered structures using P-to-S converted (Ps) phases from velocity discontinuities. However, the presence of low-velocity (relative to that of the bedrock) sediments can give rise to strong reverberations in the resulting RFs, frequently masking the Ps phases from crustal and mantle boundaries. Such reverberations are caused by P-to-S conversions and their multiples associated with the strong impedance contrast across the bottom of the low-velocity sedimentary layer. Here we propose and test an approach to effectively remove the near-surface reverberations and decipher the Ps phases associated with …

Kinetic Isotope Effect Of The ¹⁶O+³⁶O₂ And ¹⁸O+³²O₂ Isotope Exchange Reactions: Dominant Role Of Reactive Resonances Revealed By An Accurate Time-Dependent Quantum Wavepacket Study, Zhigang Sun, Dequan Yu, Wenbo Xie, Jiayi Hou, Richard Dawes, Hua Guo

Chemistry Faculty Research & Creative Works

The O + O₂ isotope exchange reactions play an important role in determining the oxygen isotopic composition of a number of trace gases in the atmosphere, and their temperature dependence and kinetic isotope effects (KIEs) provide important constraints on our understanding of the origin and mechanism of these and other unusual oxygen KIEs important in the atmosphere. This work reports a quantum dynamics study of the title reactions on the newly constructed Dawes-Lolur-Li-Jiang-Guo (DLLJG) potential energy surface (PES). The thermal reaction rate coefficients of both the 18O + 32O₂ and 16O + 36O₂ reactions obtained using the …

Compression Of Video Tracking And Bandwidth Balancing Routing In Wireless Multimedia Sensor Networks, Yin Wang, Jianjun Yang, Ju Shen, Bryson Payne, Juan Guo, Kun Hua

Computer Science Faculty Publications

There has been a tremendous growth in multimedia applications over wireless networks. Wireless Multimedia Sensor Networks(WMSNs) have become the premier choice in many research communities and industry. Many state-of-art applications, such as surveillance, traffic monitoring, and remote heath care are essentially video tracking and transmission in WMSNs. The transmission speed is constrained by the big file size of video data and fixed bandwidth allocation in constant routing paths. In this paper, we present a CamShift based algorithm to compress the tracking of videos. Then we propose a bandwidth balancing strategy in which each sensor node is able to dynamically select …

Pore Pressure Evolution And Fluid Flow During Visco-Elastic Single-Layer Buckle Folding, Andreas Eckert, X. Liu, P. Connolly

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Pore pressure and fluid flow during the deformational history of geologic structures are directly influenced by tectonic deformation events. In this contribution, 2D plane strain finite element analysis is used to study the influence of different permeability distributions on the pore pressure field and associated flow regimes during the evolution of visco-elastic single-layer buckle folds. The buckling-induced fluid flow regimes indicate that flow directions and, to a lesser degree, their magnitudes vary significantly throughout the deformation and as a function of the stratigraphic permeability distribution. The modelling results suggest that the volumetric strain and the permeability distribution significantly affect the …

Selective Detection Of Volatile Organic Compounds Using Metal Oxide Sensor Arrays, Anton Dmitrievich Netchaev

Dissertations

Selective detection of organic contaminant using widely available and inexpensive metal oxide sensors has the potential to be used in various robotic platforms for navigation, harmful chemical leak detection, mobile environmental monitoring, etc. Selective gas detection in real world environments using easily available sensors has not been reported and can be used in many industries. A sensor system using only four commercially available sensors with accompanying signal conditioning and clustering algorithm capable of discriminatory detection of chemical marker is possible. Tests have shown that temperature, humidity and concentration fluctuations can be accounted for to produce systems for real world environments. …

Secure And Reliable Routing Protocol For Transmission Data In Wireless Sensor Mesh Networks, Nooh Adel Bany Muhammad

Dissertations

Abstract

Sensor nodes collect data from the physical world then exchange it until it reaches the intended destination. This information can be sensitive, such as battlefield surveillance. Therefore, providing secure and continuous data transmissions among sensor nodes in wireless network environments is crucial. Wireless sensor networks (WSN) have limited resources, limited computation capabilities, and the exchange of data through the air and deployment in accessible areas makes the energy, security, and routing major concerns in WSN. In this research we are looking at security issues for the above reasons. WSN is susceptible to malicious activities such as hacking and physical …

Moving Average Reversion Strategy For On-Line Portfolio Selection, Bin Li, Steven C. H. Hoi, Doyen Sahoo, Zhi-Yong Liu

Research Collection School Of Computing and Information Systems

On-line portfolio selection, a fundamental problem in computational finance, has attracted increasing interest from artificial intelligence and machine learning communities in recent years. Empirical evidence shows that stock's high and low prices are temporary and stock prices are likely to follow the mean reversion phenomenon. While existing mean reversion strategies are shown to achieve good empirical performance on many real datasets, they often make the single-period mean reversion assumption, which is not always satisfied, leading to poor performance in certain real datasets. To overcome this limitation, this article proposes a multiple-period mean reversion, or so-called "Moving Average Reversion" (MAR), and …

Efficient Reverse Top-K Boolean Spatial Keyword Queries On Road Networks, Yunjun Gao, Xu Qin, Baihua Zheng, Gang Chen

Research Collection School Of Computing and Information Systems

Reverse k nearest neighbor (RkNN) queries have a broad application base such as decision support, profile-based marketing, and resource allocation. Previous work on RkNN search does not take textual information into consideration or limits to the Euclidean space. In the real world, however, most spatial objects are associated with textual information and lie on road networks. In this paper, we introduce a new type of queries, namely, reverse top-k Boolean spatial keyword (RkBSK) retrieval, which assumes objects are on the road network and considers both spatial and textual information. Given a data set P on a road network and a …

Developing A Fuzzy Expert System To Examine Hazard Analysis In The United States Army, Charles J. Karels

Theses and Dissertations

The research conducted in this thesis is an attempt to determine if there are any biographical similarities between second lieutenants in the US Army who view risk in a similar manner and if so, which are the most significant. A study was conducted using in-group surveys of 72 second lieutenants receiving training in Infantry Basic Officer Leader Course (IBOLC). The participants were provided with two written surveys each presenting a scenario based on military activities. They were asked to evaluate the scenarios and fill out Risk Management (RM) worksheets based on the US Army's doctrinal process for conducing RM. The …

Accelerated Radar Signal Processing In Large Geophysical Datasets, Ravi Preesha Geetha

Computer Science Graduate Projects and Theses

No abstract provided.

Classical Description Of H(1s) And H* (N=2) For Cross-Section Calculations Relevant To Charge-Exchange Diagnostics, N. D. Cariatore, Sebastian Otranto, Ronald E. Olson

Physics Faculty Research & Creative Works

In this work, we introduce a classical trajectory Monte Carlo (CTMC) methodology, specially conceived to provide a more accurate representation of charge-exchange processes between highly charged ions and H(1s) and H* (n=2). These processes are of particular relevance in power fusion reactor programs, for which charge-exchange spectroscopy has become a useful plasma diagnostics tool. To test the methodology, electron-capture reactions from these targets by C⁶⁺,N⁷⁺, and O⁸⁺ are studied at impact energies in the 10-150keV/amu range. State-selective cross sections are contrasted with those predicted by the standard microcanonical formulation of the CTMC method, the CTMC …

Azimuthal Anisotropy Beneath North Central Africa From Shear Wave Splitting Analyses, Awad A. Lemnifi, Kelly H. Liu, Stephen S. Gao, Cory A. Reed, Ahmed A. Elsheikh, Youqiang Yu, Abdala A. Elmelade

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

This study represents the first multistation investigation of azimuthal anisotropy beneath the interior of north central Africa, including Libya and adjacent regions, using shear wave splitting (SWS) analysis. Data used in the study include recently available broadband seismic data obtained from 15 stations managed by the Libyan Center for Remote Sensing and Space Science, and those from five other stations at which data are publicly accessible. A total of 583 pairs of high-quality SWS measurements utilizing the PKS, SKKS, and SKS phases demonstrate primarily N-S fast orientations with an average splitting delay time of approximately 1.2 s. An absence of …

Best Upgrade Plans For Single And Multiple Source-Destination Pairs, Yimin Lin, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

In this paper, we study Resource Constrained Best Upgrade Plan (BUP) computation in road network databases. Consider a transportation network (weighted graph) G where a subset of the edges are upgradable, i.e., for each such edge there is a cost, which if spent, the weight of the edge can be reduced to a specific new value. In the single-pair version of BUP, the input includes a source and a destination in G, and a budget B (resource constraint). The goal is to identify which upgradable edges should be upgraded so that the shortest path distance between source and …

Cofaçade: A Customizable Assistive Approach For Elders And Their Helpers, Jason Chen Zhao, Richard Christopher Davis, Pin Sym Foong, Shengdong Zhao

Research Collection School Of Computing and Information Systems

We present CoFaçade, a novel approach to helping elders reach their goals with IT products by working collaboratively with helpers. In this approach, the elder uses an interface with a small number of triggers, where each trigger is a single button (or card) that can execute a procedure. The helper uses a customization interface to link triggers to procedures that accomplish frequently-recurring high-level goals with IT products. Customization can be done either locally or remotely. We conducted an experiment to compare the CoFaçade approach with a baseline approach where helpers taught elders to perform IT tasks. Our results showed that …

Review Selection Using Micro-Reviews, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas

Research Collection School Of Computing and Information Systems

Given the proliferation of review content, and the fact that reviews are highly diverse and often unnecessarily verbose, users frequently face the problem of selecting the appropriate reviews to consume. Micro-reviews are emerging as a new type of online review content in the social media. Micro-reviews are posted by users of check-in services such as Foursquare. They are concise (up to 200 characters long) and highly focused, in contrast to the comprehensive and verbose reviews. In this paper, we propose a novel mining problem, which brings together these two disparate sources of review content. Specifically, we use coverage of micro-reviews …

Using Support Vector Machine Ensembles For Target Audience Classification On Twitter, Siaw Ling Lo, Raymond Chiong, David Cornforth

Research Collection School Of Computing and Information Systems

The vast amount and diversity of the content shared on social media can pose a challenge for any business wanting to use it to identify potential customers. In this paper, our aim is to investigate the use of both unsupervised and supervised learning methods for target audience classification on Twitter with minimal annotation efforts. Topic domains were automatically discovered from contents shared by followers of an account owner using Twitter Latent Dirichlet Allocation (LDA). A Support Vector Machine (SVM) ensemble was then trained using contents from different account owners of the various topic domains identified by Twitter LDA. Experimental results …

Leading Undergraduate Students To Big Data Generation, Jianjun Yang, Ju Shen

Computer Science Faculty Publications

People are facing a flood of data today. Data are being collected at unprecedented scale in many areas, such as networking, image processing, virtualization, scientific computation, and algorithms. The huge data nowadays are called Big Data. Big data is an all encompassing term for any collection of data sets so large and complex that it becomes difficult to process them using traditional data processing applications. In this article, the authors present a unique way which uses network simulator and tools of image processing to train students abilities to learn, analyze, manipulate, and apply Big Data. Thus they develop students hands-on …

Kinematically Complete Study Of Low-Energy Electron-Impact Ionization Of Neon: Internormalized Cross Sections In Three-Dimensional Kinematics, Xueguang Ren, Sadek Amami, Oleg Zatsarinny, Thomas Pflüger, Marvin Weyland, Woon Yong Baek, Hans Rabus, Klaus Bartschat, Don H. Madison, Alexander Dorn

Physics Faculty Research & Creative Works

Low-energy (E₀ 0=65eV) electron-impact single ionization of Ne (2p) has been investigated to thoroughly test state-of-the-art theoretical approaches. The experimental data were measured using a reaction microscope, which can cover nearly the entire 4π solid angle for the secondary electron emission energies ranging from 2 to 8 eV, and projectile scattering angles ranging from 8.5⁰ to 20.0⁰. The experimental triple-differential cross sections are internormalized across all measured scattering angles and ejected energies. The experimental data are compared to predictions from a hybrid second-order distorted-wave Born plus R-matrix approach, the distorted-wave Born approximation with the inclusion of postcollision interaction (PCI), …

Joint Search By Social And Spatial Proximity, Kyriakos Mouratidis, Jing Li, Yu Tang, Nikos Mamoulis

Research Collection School Of Computing and Information Systems

The diffusion of social networks introduces new challenges and opportunities for advanced services, especially so with their ongoing addition of location-based features. We show how applications like company and friend recommendation could significantly benefit from incorporating social and spatial proximity, and study a query type that captures these two-fold semantics. We develop highly scalable algorithms for its processing, and enhance them with elaborate optimizations. Finally, we use real social network data to empirically verify the efficiency and efficacy of our solutions.

On Efficient K-Optimal-Location-Selection Query Processing In Metric Spaces, Yunjun Gao, Shuyao Qi, Lu Chen, Baihua Zheng, Xinhan Li

Research Collection School Of Computing and Information Systems

This paper studies the problem of k-optimal-location-selection (kOLS) retrieval in metric spaces. Given a set D_A of customers, a set D_B of locations, a constrained region R , and a critical distance d_c, a metric kOLS (MkOLS) query retrieves k locations in D_B that are outside R but have the maximal optimality scores. Here, the optimality score of a location l∈D_B located outside R is defined as the number of the customers in D_A that are inside R and meanwhile have their distances to l bounded by …

Beyond Support And Confidence: Exploring Interestingness Measures For Rule-Based Specification Mining, Bui Tien Duy Le, David Lo

Research Collection School Of Computing and Information Systems

Numerous rule-based specification mining approaches have been proposed in the literature. Many of these approaches analyze a set of execution traces to discover interesting usage rules, e.g., whenever lock() is invoked, eventually unlock() is invoked. These techniques often generate and enumerate a set of candidate rules and compute some interestingness scores. Rules whose interestingness scores are above a certain threshold would then be output. In past studies, two measures, namely support and confidence, which are well-known measures, are often used to compute these scores. However, aside from these two, many other interestingness measures have been proposed. It is thus unclear …

Systems, Methods And Devices For Vector Control Of Permanent Magnet Synchronous Machines Using Artificial Neural Networks, Shuhui Li, Michael Fairbank, Xingang Fu, Donald C. Wunsch, Eduardo Alonso

Electrical and Computer Engineering Faculty Research & Creative Works

An example method for controlling an AC electrical machine can include providing a PWM converter operably connected between an electrical power source and the AC electrical machine and providing a neural network vector control system operably connected to the PWM converter. The control system can include a current-loop neural network configured to receive a plurality of inputs. The current-loop neural network can be configured to optimize the compensating dq-control voltage. The inputs can be d- and q-axis currents, d- and q-axis error signals, predicted d- and q-axis current signals, and a feedback compensating dq-control voltage. The d- and q-axis error …

Person Identification From Streaming Surveillance Video Using Mid-Level Features From Joint Action-Pose Distribution, Binu M. Nair, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

We propose a real time person identification algorithm for surveillance based scenarios from low-resolution streaming video, based on mid-level features extracted from the joint distribution of various types of human actions and human poses.

The proposed algorithm uses the combination of an auto-encoder based action association framework which produces per-frame probability estimates of the action being performed, and a pose recognition framework which gives per-frame body part locations.

The main focus in this manuscript is to effectively combine these per-frame action probability estimates and pose trajectories from a short temporal window to obtain mid-level features. We demonstrate that these mid-level …