Numerical Analysis and Scientific Computing Commons^™

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 …

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 …

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. …

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

Computer Science Graduate Projects and Theses

No abstract provided.

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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.

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), …

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 …

Hole Detection And Shape-Free Representation And Double Landmarks Based Geographic Routing In Wireless Sensor Networks, Jianjun Yang, Zongming Fei, Ju Shen

Computer Science Faculty Publications

In wireless sensor networks, an important issue of geographic routing is “local minimum” problem, which is caused by a “hole” that blocks the greedy forwarding process. Existing geographic routing algorithms use perimeter routing strategies to find a long detour path when such a situation occurs. To avoid the long detour path, recent research focuses on detecting the hole in advance, then the nodes located on the boundary of the hole advertise the hole information to the nodes near the hole. Hence the long detour path can be avoided in future routing. We propose a heuristic hole detecting algorithm which identifies …