Numerical Analysis and Scientific Computing Commons^™

Active Crowdsourcing For Annotation, Shuji Hao, Chunyan Miao, Steven C. H. Hoi, Peilin Zhao

Research Collection School Of Computing and Information Systems

Crowdsourcing has shown great potential in obtaining large-scale and cheap labels for different tasks. However, obtaining reliable labels is challenging due to several reasons, such as noisy annotators, limited budget and so on. The state-of-the-art approaches, either suffer in some noisy scenarios, or rely on unlimited resources to acquire reliable labels. In this article, we adopt the learning with expert~(AKA worker in crowdsourcing) advice framework to robustly infer accurate labels by considering the reliability of each worker. However, in order to accurately predict the reliability of each worker, traditional learning with expert advice will consult with external oracles~(AKA domain experts) …

Incorporating Analytics Into A Business Process Modelling Course, Gottipati Swapna, Shankararaman, Venky

Research Collection School Of Computing and Information Systems

Embedding analytics is about integrating data analytics into operational systems that are part of an organization’s business processes. Currently, most organizations focus on automation business processes and enhancing productivity. However, going forward, in order to stay competitive, organizations have to go beyond automating their processes, by making them more intelligent, by embedding analytics into their processes and business applications. Therefore, there is need for enhancing the knowledge and skills of BPM professionals with know-how on improving a business process by embedding analytics into the workflow. In this paper contribution, the authors share their experience on how an existing process modelling, …

Building Crowd Movement Model Using Sample-Based Mobility Survey, Larry J. J. Lin, Shih-Fen Cheng, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Crowd simulation is a well-studied topic, yet it usually focuses on visualization. In this paper, we study a special class of crowd simulation, where individual agents have diverse backgrounds, ad hoc objectives, and non-repeating visits. Such crowd simulation is particularly useful when modeling human agents movement in leisure settings such as visiting museums or theme parks. In these settings, we are interested in accurately estimating aggregate crowd-related movement statistics. As comprehensive monitoring is usually not feasible for a large crowd, we propose to conduct mobility surveys on only a small group of sampled individuals. We demonstrate via simulation that we …

A Layered Hidden Markov Model For Predicting Human Trajectories In A Multi-Floor Building, Qian Li, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Tracking and modeling huge amount of users’ movement in a multi-floor building by using wireless devices is a challenging task, due to crowd movement complexity and signal sensing accuracy. In this paper, we use Layered Hidden Markov Model (LHMM) to fit the spatial-temporal trajectories (with large number of missing values). We decompose the problem into distinct layers that Hidden Markov Models (HMMs) are operated at different spatial granularities separately. Baum-Welch algorithm and Viterbi algorithm are used for finding the probable location sequences at each layer. By measuring the predicted result of trajectories, we compared the predicted results of both single …

Functionalized Nanodiamond Reinforced Biopolymers, Gongyao Zhou, Peter I. Lelkes, Yury Gogotsi, Vadym Mochalin

Chemistry Faculty Research & Creative Works

The present invention includes a composition for implantation in a patient, comprising surface-functionalized nanodiamonds and at least one biodegradable biocompatible polymer. The present invention also includes a surgical fixation device for use in a patient.

Infinite-Noise Criticality: Nonequilibrium Phase Transitions In Fluctuating Environments, Thomas Vojta, José A. Hoyos

Physics Faculty Research & Creative Works

We study the effects of time-varying environmental noise on nonequilibrium phase transitions in spreading and growth processes. Using the examples of the logistic evolution equation as well as the contact process, we show that such temporal disorder gives rise to a distinct type of critical points at which the effective noise amplitude diverges on long time scales. This leads to enormous density fluctuations characterized by an infinitely broad probability distribution at criticality. We develop a real-time renormalization-group theory that provides a general framework for the effects of temporal disorder on nonequilibrium processes. We also discuss how general this exotic critical …

Using Digital Genomics To Create An Intelligent Enterprise, Mario Domingo

Asian Management Insights

Every business knows that it needs to leverage customer data, but few know the potential it has to transform business processes, decisions and performance.

Whom Should We Sense In 'Social Sensing' - Analyzing Which Users Work Best For Social Media Now-Casting, Jisun An, Ingmar Weber

Research Collection School Of Computing and Information Systems

Given the ever increasing amount of publicly available social media data, there is growing interest in using online data to study and quantify phenomena in the offline 'real' world. As social media data can be obtained in near real-time and at low cost, it is often used for 'now-casting' indices such as levels of flu activity or unemployment. The term 'social sensing' is often used in this context to describe the idea that users act as 'sensors', publicly reporting their health status or job losses. Sensor activity during a time period is then typically aggregated in a 'one tweet, one …

A Method And System For Sentiment Classification And Emotion Classification [Us Patent 20170308523a1], Zhaoxia Wang, Rick Siow Mong Goh, Yinping Yang

Research Collection School Of Computing and Information Systems

A system and a method for classifying text messages, such as social media messages into sentiment valence categories are provided. The system comprising a module for decomposing text messages, a module for cleaning text messages, a module for producing feature data of text messages, and a module for classifying text messages into sentiment valence categories. The module for decomposing text messages is configured to: receive a text message, parse the text message into separate portions in response to parsing criteria based on sentence delimiters, wherein the separate portions are sentences, phrases and words, and rejoin at least some of the …

Chemometric And Bioinformatic Analyses Of Cellular Biochemistry, Bradley Worley

Department of Chemistry: Dissertations, Theses, and Student Research

The amount of information collected and analyzed in biochemical and bioanalytical research has exploded over the last few decades, due in large part to the increasing availability of analytical instrumentation that yields information-rich spectra. Datasets from Nuclear Magnetic Resonance (NMR), Mass Spectrometry (MS), infrared (IR) or Raman spectroscopy may easily carry tens to hundreds of thousands of potentially correlated variables observed from only a few samples, making the application of classical statistical methods inappropriate, if not impossible. Drawing useful biochemical conclusions from these unique sources of data requires the use of specialized multivariate data handling techniques.

Unfortunately, proper implementation of …

Comparison Of Experimental And Theoretical Electron-Impact-Ionization Triple-Differential Cross Sections For Ethane, Esam Ali, Kate Nixon, Andrw Murray, Chuangang Ning, James Colgan, Don H. Madison

Physics Faculty Research & Creative Works

We have recently examined electron-impact ionization of molecules that have one large atom at the center, surrounded by H nuclei (H₂O, NH₃, CH₄). All of these molecules have ten electrons; however, they vary in their molecular symmetry. We found that the triple-differential cross sections (TDCSs) for the highest occupied molecular orbitals (HOMOs) were similar, as was the character of the HOMO orbitals which had a p-type "peanut" shape. In this work, we examine ethane (C₂H₆) which is a molecule that has two large atoms surrounded by H nuclei, so that …

A Joint Receiver Function And Gravity Study Of Crustal Structure Beneath The Incipient Okavango Rift, Botswana, Youqiang Yu, Kelly H. Liu, Cory A. Reed, Moikwathai Moidaki, Kevin Mickus, Estella A. Atekwana, Stephen S. Gao

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Rifting incorporates the fundamental processes concerning the breakup of continental lithosphere and plays a significant role in the formation and evolution of sedimentary basins. In order to decipher the characteristics of rifting at its earliest stage, we conduct the first teleseismic crustal study of one of the world's youngest continental rifts, the Okavango Rift Zone (ORZ), where the magma has not yet breached the surface. Results from receiver function stacking and gravity modeling indicate that the crust/mantle boundary beneath the ORZ is uplifted by 4-5 km, and the initiation of the ORZ is closely related to lithospheric stretching. Possible decompression …

A Forecasting Tool For Predicting Australia's Domestic Airline Passenger Demand Using A Genetic Algorithm, Panarat Srisaeng, Glenn Baxter, Steven Richardson, Graham Wild

Research outputs 2014 to 2021

This study has proposed and empirically tested for the first time genetic algorithm optimization models for modelling Australia’s domestic airline passenger demand, as measured by enplaned passengers (GAPAXDE model) and revenue passenger kilometres performed (GARPKSDE model). Data was divided into training and testing datasets; 74 training datasets were used to estimate the weighting factors of the genetic algorithm models and 13 out-of-sample datasets were used for testing the robustness of the genetic algorithm models. The genetic algorithm parameters used in this study comprised population size (n): 200; the generation number: 1,000; and mutation rate: 0.01. The modelling results have shown …

Scheduled Approximation For Personalized Pagerank With Utility-Based Hub Selection, Fanwei Zhu, Yuan Fang, Kevin Chen-Chuan Chang, Jing Ying

Research Collection School Of Computing and Information Systems

As Personalized PageRank has been widely leveraged for ranking on a graph, the efficient computation of Personalized PageRank Vector (PPV) becomes a prominent issue. In this paper, we propose FastPPV, an approximate PPV computation algorithm that is incremental and accuracy-aware. Our approach hinges on a novel paradigm of scheduled approximation: the computation is partitioned and scheduled for processing in an “organized” way, such that we can gradually improve our PPV estimation in an incremental manner and quantify the accuracy of our approximation at query time. Guided by this principle, we develop an efficient hub-based realization, where we adopt the metric …

Choosing Your Weapons: On Sentiment Analysis Tools For Software Engineering Research, Robbert Jongeling, Subhajit Datta, Alexander Serebrenik

Research Collection School Of Computing and Information Systems

Recent years have seen an increasing attention to social aspects of software engineering, including studies of emotions and sentiments experienced and expressed by the software developers. Most of these studies reuse existing sentiment analysis tools such as SentiStrength and NLTK. However, these tools have been trained on product reviews and movie reviews and, therefore, their results might not be applicable in the software engineering domain. In this paper we study whether the sentiment analysis tools agree with the sentiment recognized by human evaluators (as reported in an earlier study) as well as with each other. Furthermore, we evaluate the impact …

The Importance Of Being Isolated: An Empirical Study On Chromium Reviews, Subhajit Datta, Devarshi Bhatt, Manish Jain, Proshanta Sarkar, Santonu Sarkar

Research Collection School Of Computing and Information Systems

As large scale software development has become more collaborative, and software teams more globally distributed, several studies have explored how developer interaction influences software development outcomes. The emphasis so far has been largely on outcomes like defect count, the time to close modification requests etc. In the paper, we examine data from the Chromium project to understand how different aspects of developer discussion relate to the closure time of reviews. On the basis of analyzing reviews discussed by 2000+ developers, our results indicate that quicker closure of reviews owned by a developer relates to higher reception of information and insights …

A Gene-Based Association Method For Mapping Traits Using Reference Transcriptome Data, Eric R. Gamazon, Heather Wheeler, Kaanan P. Shah, Sahar V. Mozaffari, Keston Aquino-Michaels, Robert J. Carroll, Anne E. Eyler, Joshua C. Denny, Gtex Consortium, Dan L. Nicolae, Nancy J. Cox, Hae Kyung Im

Bioinformatics Faculty Publications

Genome-wide association studies (GWAS) have identified thousands of variants robustly associated with complex traits. However, the biological mechanisms underlying these associations are, in general, not well understood. We propose a gene-based association method called PrediXcan that directly tests the molecular mechanisms through which genetic variation affects phenotype. The approach estimates the component of gene expression determined by an individual’s genetic profile and correlates ‘imputed’ gene expression with the phenotype under investigation to identify genes involved in the etiology of the phenotype. Genetically regulated gene expression is estimated using whole-genome tissue-dependent prediction models trained with reference transcriptome data sets. PrediXcan enjoys …

Evidence For Unnatural-Parity Contributions To Electron-Impact Ionization Of Laser-Aligned Atoms, G. S. J. Armstrong, J. Colgan, M. S. Pindzola, S. Amami, Don H. Madison, J. Pursehouse, K. L. Nixon, A. J. Murray

Physics Faculty Research & Creative Works

Recent measurements have examined the electron-impact ionization of excited-state laser-aligned Mg atoms. In this work we show that the ionization cross section arising from the geometry where the aligned atom is perpendicular to the scattering plane directly probes the unnatural parity contributions to the ionization amplitude. The contributions from natural parity partial waves cancel exactly in this geometry. Our calculations resolve the discrepancy between the nonzero measured cross sections in this plane and the zero cross section predicted by distorted-wave approaches. We demonstrate that this is a general feature of ionization from p-state targets by additional studies of ionization from …

Simulations Of Hl-Lhc Crab Cavity Noise Using Headtail, Stanley Steeper

Physics

The High Luminosity Large Hadron Collider (Hi-Lumi LHC) upgrade -- scheduled to be completed by 2025 -- will improve the existing LHC in many ways. One such upgrade is the addition of Crab Cavities (CCs). The CCs are resonant structures that provide strong transverse kicks to the circulating clouds of particles around each interaction region. As such, the CCs result in a head-on collision of the clouds and a large increase in event rate, leading to reduced statistical uncertainty and potentially faster discoveries. However, the CC field will be modulated by phase and amplitude noise which can have detrimental effects …

Clustering Data Of Mixed Categorical And Numerical Type With Unsupervised Feature Learning, Dao Lam, Mingzhen Wei, Donald C. Wunsch

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Mixed-type categorical and numerical data are a challenge in many applications. This general area of mixed-type data is among the frontier areas, where computational intelligence approaches are often brittle compared with the capabilities of living creatures. In this paper, unsupervised feature learning (UFL) is applied to the mixed-type data to achieve a sparse representation, which makes it easier for clustering algorithms to separate the data. Unlike other UFL methods that work with homogeneous data, such as image and video data, the presented UFL works with the mixed-type data using fuzzy adaptive resonance theory (ART). UFL with fuzzy ART (UFLA) obtains …

Trace Element Composition Of Pm2.5 And Pm10 From Kolkata - A Heavily Polluted Indian Metropolis, Reshmi Das, Bahareh Khezri, Bijayen Srivastava, Subhajit Datta, Pradip Kumar Sikdar, Richard D. Webster, Xianfeng Wang

Research Collection School Of Computing and Information Systems

Elemental composition of PM_2.5 and PM₁₀ was measured from 16 locations in Greater Kolkata in Eastern India. Sampling was carried out in the winter months of 2013–2014. PM_2.5 and PM₁₀ mass concentrations ranged from 83–783 μg/m³ and 167–928 μg/m³ respectively. 20 elements were measured with an Agilent 7700 series ICP–MS equipped with a 3^rd generation He reaction/collision cell following closed vessel microwave digestion. In both size fractions Fe, Na, Al, K, Ca were present in high concentrations (>1 000 ng/m³), Mn, Zn and Pb demonstrated medium concentrations (>100 ng/m …

Need Accurate User Behaviour?: Pay Attention To Groups!, Kasthuri Jayarajah, Youngki Lee, Archan Misra, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

In this paper, we show that characterizing user behaviour from location or smartphone usage traces, without accounting for the interaction of individuals in physical-world groups, can lead to erroneous results. We conducted one of the largest studies in the UbiComp domain thus far, involving indoor location traces of more than 6,000 users, collected over a 4-month period at our university campus, and further studied fine-grained App usage of a subset of 156 Android users. We apply a state-of-the-art group detection algorithm to annotate such location traces with group vs. individual context, and then show that individuals vs. groups exhibit significant …

Evaluation And Improvement Of Procurement Process With Data Analytics, Melvin H. C. Tan, Wee Leong Lee

Research Collection School Of Computing and Information Systems

Analytics can be applied in procurement to benefit organizations beyond just prevention and detection of fraud. This study aims to demonstrate how advanced data mining techniques such as text mining and cluster analysis can be used to improve visibility of procurement patterns and provide decision-makers with insight to develop more efficient sourcing strategies, in terms of cost and effort. A case study of an organization’s effort to improve its procurement process is presented in this paper. The findings from this study suggest that opportunities exist for organizations to aggregate common goods and services among the purchases made under and across …

Mapping Open Water Bodeis With Optical Remote Sensing, Mary Ellen O'Donnell, Erika Podest

STAR Program Research Presentations

There is interest in mapping open water bodies using remote sensing data. Coverage and persistence of open water is currently a poorly measured variable due to its spatial and temporal variability across landscapes, especially in remote areas. The presence and persistence of open water is one of the primary indicators of conditions suitable for mosquito breeding habitats. Predicting the risk of mosquito caused disease outbreaks is a required step towards their control and eradication. Satellite observations can provide needed data to support agency decisions for deployment of preventative measures and control resources. This study, which will try to map open …

Anharmonic Properties In Mg₂X (X= C, Si, Ge, Sn, Pb) From First-Principles Calculations, Aleksandr V. Chernatynskiy, Simon R. Phillpot

Physics Faculty Research & Creative Works

Thermal conductivity reduction is one of the potential routes to improve the performance of thermoelectric materials. However, detailed understanding of the thermal transport of many promising materials is still missing. In this paper, we employ electronic-structure calculations at the level of density functional theory to elucidate thermal transport properties of the Mg₂X (X=C, Si, Ge, Sn, and Pb) family of compounds, which includes Mg₂Si, a material already identified as a potential thermoelectric. All these materials crystallize into the same antifluorite structure. Systematic trends in the anharmonic properties of these materials are presented and examined. Our calculations …

Vibrational Energy Levels Of The Simplest Criegee Intermediate (Ch₂Oo) From Full-Dimensional Lanczos, Mctdh, And Multimode Calculations, Hua-Gen Yu, Steve Alexandre Ndengué, Jun Li, Richard Dawes, Hua Guo

Chemistry Faculty Research & Creative Works

Accurate vibrational energy levels of the simplest Criegee intermediate (CH₂OO) were determined on a recently developed ab initio based nine-dimensional potential energy surface using three quantum mechanical methods. the first is the iterative Lanczos method using a conventional basis expansion with an exact Hamiltonian. the second and more efficient method is the multi-configurational time-dependent Hartree (MCTDH) method in which the potential energy surface is refit to conform to the sums-of-products requirement of MCTDH. Finally, the energy levels were computed with a vibrational self-consistent field/virtual configuration interaction method in MULTIMODE. the low-lying levels obtained from the three methods are …

System And Process For Upgrading Hydrocarbons, Dennis N. Bingham, Kerry M. Klingler, Joseph D. Smith, Terry D. Turner, Bruce M. Wilding

Chemical and Biochemical Engineering Faculty Research & Creative Works

In one embodiment, a system for upgrading a hydrocarbon material may include a black wax upgrade subsystem and a molten salt gasification (MSG) subsystem. The black wax upgrade subsystem and the MSG subsystem may be located within a common pressure boundary, such as within a pressure vessel. Gaseous materials produced by the MSG subsystem may be used in the process carried out within the black wax upgrade subsystem. For example, hydrogen may pass through a gaseous transfer interface to interact with black wax feed material to hydrogenate such material during a cracking process. In one embodiment, the gaseous transfer interface …

A Study On The Efficacy Of Sentiment Analysis In Author Attribution, Michael J. Schneider

Electronic Theses and Dissertations

The field of authorship attribution seeks to characterize an author’s writing style well enough to determine whether he or she has written a text of interest. One subfield of authorship attribution, stylometry, seeks to find the necessary literary attributes to quantify an author’s writing style. The research presented here sought to determine the efficacy of sentiment analysis as a new stylometric feature, by comparing its performance in attributing authorship against the performance of traditional stylometric features. Experimentation, with a corpus of sci-fi texts, found sentiment analysis to have a much lower performance in assigning authorship than the traditional stylometric features.

Enabling Real Time In-Situ Context Based Experimentation To Observe User Behaviour, Kartik Muralidaran

Dissertations and Theses Collection (Open Access)

Today’s mobile phones represent a rich and powerful computing platform, given their sensing, processing and communication capabilities. These devices are also part of the everyday life of millions of people, and coupled with the unprecedented access to personal context, make them the ideal tool for conducting behavioural experiments in an unobtrusive way. Transforming the mobile device from a mere observer of human context to an enabler of behavioural experiments however, requires not only providing experimenters access to the deep, near-real time human context (e.g., location, activity, group dynamics) but also exposing a disciplined scientific experimentation service that frees them from …

Automatic Detection And Denoising Of Signals In Large Geophysical Datasets, Gabriel O. Trisca

Boise State University Theses and Dissertations

To fully understand the complex interactions of various phenomena in the natural world, scientific disciplines such as geology and seismology increasingly rely upon analyzing large amounts of observations. However, data collection is growing at a faster rate than what is currently possible to analyze through traditional approaches. These datasets, supplied by the increasing use of sensors and remote sensing, require specialized computer programs to effectively analyze complex and expansive volumes of data.

Elaborating on existing geophysical data processing approaches for infrasound data collected from an avalanche-prone area, this project proposes new techniques for processing large geophysical datasets. These improved techniques …