Numerical Analysis and Scientific Computing Commons^™

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 …

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 …

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 …

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 …

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 …

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 …

Cooperation In Delay-Tolerant Networks With Wireless Energy Transfer: Performance Analysis And Optimization, Dusit Niyato, Ping Wang, Hwee-Pink Tan, Walid Saad, Dong In Kim

Research Collection School Of Computing and Information Systems

We consider a delay-tolerant network (DTN) whose mobile nodes are assigned to collect packets from data sources and deliver them to a sink (i.e., a gateway). Each mobile node operates by using energy transferred wirelessly from the gateway. For such a network, two main issues are studied. First, when a mobile node is at the data source, this node must decide on whether to accept the packet received from the data source or not. In contrast, whenever a mobile node is at the gateway, it has to decide on whether to transmit the packets collected from the data sources or …

Deep Learning For Just-In-Time Defect Prediction, Xinli Yang, David Lo, Xin Xia, Yun Zhang, Jianling Sun

Research Collection School Of Computing and Information Systems

Defect prediction is a very meaningful topic, particularly at change-level. Change-level defect prediction, which is also referred as just-in-time defect prediction, could not only ensure software quality in the development process, but also make the developers check and fix the defects in time. Nowadays, deep learning is a hot topic in the machine learning literature. Whether deep learning can be used to improve the performance of just-in-time defect prediction is still uninvestigated. In this paper, to bridge this research gap, we propose an approach Deeper which leverages deep learning techniques to predict defect-prone changes. We first build a set of …

Distributed Caching Using The Htcondor Cached, Derek J. Weitzel, Brian Bockelman, David Swanson

Holland Computing Center: Faculty Publications

A batch processing job in a distributed system has three clear steps, stage-in, execution, and stage-out. As data sizes have increased, the stage-in time has also increased. In order to optimize stage-in time for shared inputs, we propose the CacheD, a caching mechanism for high throughput computing. Along with caching on worker nodes for rapid transfers, we also introduce a novel transfer method to distribute shared caches to multiple worker nodes utilizing BitTorrent. We show that our caching method significantly improves workflow completion times by minimizing stage-in time while being non-intrusive to the computational resources, allowing for opportunistic resources to …

Message Passing For Collective Graphical Models, Tao Sun, Daniel Sheldon, Akshat Kumar

Research Collection School Of Computing and Information Systems

Collective graphical models (CGMs) are a formalism for inference and learning about a population of independent and identically distributed individuals when only noisy aggregate data are available. We highlight a close connection between approximate MAP inference in CGMs and marginal inference in standard graphical models. The connection leads us to derive a novel Belief Propagation (BP) style algorithm for collective graphical models. Mathematically, the algorithm is a strict generalization of BP—it can be viewed as an extension to minimize the Bethe free energy plus additional energy terms that are non-linear functions of the marginals. For CGMs, the algorithm is much …