Physical Sciences and Mathematics Commons^™

Predicting Indoor Crowd Density Using Column-Structured Deep Neural Network, Akihito Sudo, Teck Hou (Deng Dehao) Teng, Hoong Chuin Lau, Yoshihide Sekimoto

Research Collection School Of Computing and Information Systems

This work proposes a deep neural network approach known as the column-structured deep neural network (COL-DNN-R) for predicting crowd density in an indoor environment using historical Wi-Fi traces of individual visitors. With a structure designed to minimize feature engineering, COL-DNN accepts raw features such as crowd density, opening and closing hours and peak visitor counts for extracting features. The extracted features are used by a regression model R for predicting the crowd densities. Standard regression models such as MLP, RF and SVM can be used as R. Experiments are performed to investigate the effect of feature representation and model structure …

Temporal Understanding Of Human Mobility: A Multi-Time Scale Analysis, Tongtong Liu, Zheng Yang, Yi Zhao, Chenshu Wu, Zimu Zhou, Yunhao Liu

Research Collection School Of Computing and Information Systems

The recent availability of digital traces generated by cellphone calls has significantly increased the scientific understanding of human mobility. Until now, however, based on low time resolution measurements, previous works have ignored to study human mobility under various time scales due to sparse and irregular calls, particularly in the era of mobile Internet. In this paper, we introduced Mobile Flow Records, flow-level data access records of online activity of smartphone users, to explore human mobility. Mobile Flow Records collect high-resolution information of large populations. By exploiting this kind of data, we show the models and statistics of human mobility at …

Sourcevote: Fusing Multi-Valued Data Via Inter-Source Agreements, Xiu Susie Fang, Quan Z. Sheng, Xianzhi Wang, Mahmoud Barhamgi, Lina Yao, Anne H.H. Ngu

Research Collection School Of Computing and Information Systems

Data fusion is a fundamental research problem of identifyingtrue values of data items of interest from conflicting multi-sourceddata. Although considerable research efforts have been conducted on thistopic, existing approaches generally assume every data item has exactlyone true value, which fails to reflect the real world where data items withmultiple true values widely exist. In this paper, we propose a novel approach,SourceVote, to estimate value veracity for multi-valued data items.SourceVote models the endorsement relations among sources by quantifyingtheir two-sided inter-source agreements. In particular, two graphs areconstructed to model inter-source relations. Then two aspects of sourcereliability are derived from these graphs and …

A Fast Trajectory Outlier Detection Approach Via Driving Behavior Modeling, Hao Wu, Weiwei Sun, Baihua Zheng

Research Collection School Of Computing and Information Systems

Trajectory outlier detection is a fundamental building block for many location-based service (LBS) applications, with a large application base. We dedicate this paper on detecting the outliers from vehicle trajectories efficiently and effectively. In addition, we want our solution to be able to issue an alarm early when an outlier trajectory is only partially observed (i.e., the trajectory has not yet reached the destination). Most existing works study the problem on general Euclidean trajectories and require accesses to the historical trajectory database or computations on the distance metric that are very expensive. Furthermore, few of existing works consider some specific …

Semvis: Semantic Visualization For Interactive Topical Analysis, Le Van Minh Tuan, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Exploratory analysis of a text corpus is an important task that can be aided by informative visualization. One spatially-oriented form of document visualization is a scatterplot, whereby every document is associated with a coordinate, and relationships among documents can be perceived through their spatial distances. Semantic visualization further infuses the visualization space with latent semantics, by incorporating a topic model that has a representation in the visualization space, allowing users to also perceive relationships between documents and topics spatially. We illustrate how a semantic visualization system called SemVis could be used to navigate a text corpus interactively and topically via …

File-Level Defect Prediction: Unsupervised Vs. Supervised Models, Meng Yan, Yicheng Fang, David Lo, Xin Xia, Xiaohong Zhang

Research Collection School Of Computing and Information Systems

Background: Software defect models can help software quality assurance teams to allocate testing or code review resources. A variety of techniques have been used to build defect prediction models, including supervised and unsupervised methods. Recently, Yang et al. [1] surprisingly find that unsupervised models can perform statistically significantly better than supervised models in effort-aware change-level defect prediction. However, little is known about relative performance of unsupervised and supervised models for effort-aware file-level defect prediction. Goal: Inspired by their work, we aim to investigate whether a similar finding holds in effort-aware file-level defect prediction. Method: We replicate Yang et al.'s study …

Interactive Social Recommendation, Xin Wang, Steven C. H. Hoi, Chenghao Liu, Martin Ester

Research Collection School Of Computing and Information Systems

Social recommendation has been an active research topic over the last decade, based on the assumption that social information from friendship networks is beneficial for improving recommendation accuracy, especially when dealing with cold-start users who lack sufficient past behavior information for accurate recommendation. However, it is nontrivial to use such information, since some of a person's friends may share similar preferences in certain aspects, but others may be totally irrelevant for recommendations. Thus one challenge is to explore and exploit the extend to which a user trusts his/her friends when utilizing social information to improve recommendations. On the other hand, …

On Analyzing Job Hop Behavior And Talent Flow Networks, Richard J. Oentaryo, Xavier Jayaraj Siddarth Ashok, Ee-Peng Lim, Philips Kokoh Prasetyo

Research Collection School Of Computing and Information Systems

Analyzing job hopping behavior is important for theunderstanding of job preference and career progression of working individuals.When analyzed at the workforce population level, job hop analysis helps to gaininsights of talent flow and organization competition. Traditionally, surveysare conducted on job seekers and employers to study job behavior. While surveysare good at getting direct user input to specially designed questions, they areoften not scalable and timely enough to cope with fast-changing job landscape.In this paper, we present a data science approach to analyze job hops performedby about 490,000 working professionals located in a city using their publiclyshared profiles. We develop several …

Eeg-Based Emotion Recognition Via Fast And Robust Feature Smoothing, Cheng Tang, Di Wang, Ah-Hwee Tan, Chunyan Miao

Research Collection School Of Computing and Information Systems

Electroencephalograph (EEG) signals reveal much of our brain states and have been widely used in emotion recognition. However, the recognition accuracy is hardly ideal mainly due to the following reasons: (i) the features extracted from EEG signals may not solely reflect one’s emotional patterns and their quality is easily affected by noise; and (ii) increasing feature dimension may enhance the recognition accuracy, but it often requires extra computation time. In this paper, we propose a feature smoothing method to alleviate the aforementioned problems. Specifically, we extract six statistical features from raw EEG signals and apply a simple yet cost-effective feature …

Vireo @ Trecvid 2017: Video-To-Text, Ad-Hoc Video Search And Video Hyperlinking, Phuong Anh Nguyen, Qing Li, Zhi-Qi Cheng, Yi-Jie Lu, Hao Zhang, Xiao Wu, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

In this paper, we describe the systems developed for Video-to-Text (VTT), Ad-hoc Video Search (AVS) and Video Hyper-linking (LNK) tasks at TRECVID 2017 [1] and the achieved results.

Leveraging Social Analytics Data For Identifying Customer Segments For Online News Media, Jansen, Bernard J, Soon-Gyo Jung, Jisun An, Haewoon Kwak, Haewoon Kwak

Research Collection School Of Computing and Information Systems

In this work, we describe a methodology for leveraging large amounts of customer interaction data with online content from major social media platforms in order to isolate meaningful customer segments. The methodology is robust in that it can rapidly identify diverse customer segments using solely online behaviors and then associate these behavioral customer segments with the related distinct demographic segments, presenting a holistic picture of the customer base of an organization. We validate our methodology via the implementation of a working system that rapidly and in near real-time processes tens of millions of online customer interactions with content posted on …

Surface Impedance And Optimum Surface Resistance Of A Superconductor With An Imperfect Surface, Alex Gurevich, Takayuki Kubo

Physics Faculty Publications

We calculate a low-frequency surface impedance of a dirty, s-wave superconductor with an imperfect surface incorporating either a thin layer with a reduced pairing constant or a thin, proximity-coupled normal layer. Such structures model realistic surfaces of superconducting materials which can contain oxide layers, absorbed impurities, or nonstoichiometric composition. We solved the Usadel equations self-consistently and obtained spatial distributions of the order parameter and the quasiparticle density of states which then were used to calculate a low-frequency surface resistance R_s (T) and the magnetic penetration depth λ(T) as functions of temperature in the limit of local London electrodynamics. It …

Interproximal Distance Analysis Of Stereolithographic Casts Made By Cad-Cam Technology: An In Vitro Study, Melanie Hoffman, Seok-Hwan Cho, Naveen K. Bansal

Mathematics, Statistics and Computer Science Faculty Research and Publications

Statement of problem

The accuracy of interproximal distances of the definitive casts made by computer-aided design and computer-aided manufacturing (CAD-CAM) technology is not yet known.

Purpose

The purpose of this in vitro study was to compare the interproximal distances of stereolithographic casts made by CAD-CAM technology with those of stone casts made by the conventional method.

Material and methods

Dentoform teeth were prepared for a single ceramic crown on the maxillary left central incisor, a 3-unit fixed dental prosthesis (FDP) on the second premolar for a metal-ceramic crown, and a maxillary right first molar for a metal crown. Twenty digital …

Defending Our Coasts: Ensuring Military Readiness & Economic Viability As Waters Rise, Deborah Kornblut, Angela King, Virginia Coastal Policy Center

Virginia Coastal Policy Center

No abstract provided.

Automated Cluster Provisioning And Workflow Management For Parallel Scientific Applications In The Cloud, Brandon Posey, Christopher Gropp, Alexander Herzog, Amy Apon

Publications

Many commercial cloud providers and tools are available that researchers could utilize to advance computational science research. However, adoption by the research community has been slow. In this paper we describe the automated Pro-visioning And Workflow (PAW) management tool for parallel scientific applications in the cloud. PAW is a comprehensive resource provisioning and workflow tool that automates the steps of dynamically provisioning a large scale cluster environment in the cloud, executing a set of jobs or a custom workflow and, after the jobs have completed, de-provisioning the cluster environment in a single operation. A key characteristic of PAW is that …

Nutrient Contamination From Non-Point Sources: Dissolved Phosphate In Surface And Subsurface Waters At Eku Meadowbrook Farm, Madison County, Kentucky, Hunter R. Evans, Reid E. Buskirk, Walter S. Borowski, Jonathan M. Malzone

EKU Faculty and Staff Scholarship

Farms are non-point sources for nutrient contaminants that drain into watersheds and contribute to eutrophication and other environmental problems. Eastern Kentucky University’s Meadowbrook Farm raises both crops and livestock, causing dissolved phosphorus in the form of orthophosphate (PO₄^3-) from fertilizer and animal manure to enter surface and subsurface waters, eventually flowing into Muddy Creek, a tributary of the Kentucky River.

We sampled surface water, springs, and water from French drains that emanate from the farm, and also sampled Muddy Creek waters from May through August 2016. Typically, 1 to 2 days after sampling, we colorimetrically measured dissolved …

Groundwater And Subsurface Water In A Landscape With Shallow Bedrock: Implications For Agricultural Nutrient Export, Laura Kelley, Hunter R. Evans, Reid E. Buskirk, Jonathan M. Malzone, Walter S. Borowski

EKU Faculty and Staff Scholarship

Controls on nutrient export from agricultural landscapes include regional hydrological and geological conditions. In many central Kentucky basins shallow fractured bedrock produces focused groundwater discharge and flashy runoff events. Eastern Kentucky University’s Meadowbrook Farm is currently experimenting with nutrient sequestration techniques; however the effectiveness of these techniques given the local hydrogeology needs to be quantified. Our objective was to determine the potential pathways for nutrient export by mapping key hydrologic features and using a watershed approach. The key features mapped were springs, tile drains, runoff channels, land use and the underlying geology. We chose a 0.46 km² watershed to …

Phosphoproteomics Profiling Of Nonsmall Cell Lung Cancer Cells Treated With A Novel Phosphatase Activator, Danica Wiredja, Marzieh Ayati, Sahar Mazhar, Jaya Sangodkar, Sean Maxwell, Daniela Schlatzer, Goutham Narla, Mehmet Koyutürk, Mark R. Chance

Computer Science Faculty Publications and Presentations

Activation of protein phosphatase 2A (PP2A) is a promising anti-cancer therapeutic strategy, as this tumor suppressor has the ability to coordinately downregulate multiple pathways involved in the regulation of cellular growth and proliferation. In order to understand the systems-level perturbations mediated by PP2A activation, we carried out mass spectrometry-based phosphoproteomic analysis of two KRAS mutated non-small cell lung cancer (NSCLC) cell lines (A549 and H358) treated with a novel Small Molecule Activator of PP2A (SMAP). Overall, this permitted quantification of differential signaling across over 1,600 phosphoproteins and 3,000 phosphosites. Kinase activity assessment and pathway enrichment implicated collective downregulation of RAS …

Maritime Object Detection, Tracking, And Classification Using Lidar And Vision-Based Sensor Fusion, David John Thompson

Doctoral Dissertations and Master's Theses

Autonomous Surface Vehicles have the capability of replacing dull, dirty, and dangerous jobs in the maritime field. However, few successful ASV systems exist today, as there is a need for greater sensing capabilities. Furthermore, a successful ASV system requires object detection and recognition capabilities to enable autonomous navigation and situational awareness. This thesis demonstrates an application of LiDAR sensors in maritime environments for object detection, classification, and camera sensor fusion. This is accomplished through the integration of a high-fidelity GPS/INS system, 3D LiDAR sensors, and a pair of cameras. After rotating LiDAR returns into a global reference frame, they are …

Book Review: Chandra's Cosmos: Dark Matter, Black Holes, And Other Wonders Revealed By Nasa's Premier X-Ray Observatory, T. D. Oswalt

Publications

This document is Dr. Oswalt’s review of Chandra's cosmos: dark matter, black holes, and other wonders revealed by NASA's premier X-ray observatory by Wallace H. Tucker. Smithsonian Books, 2017. 266p bibl index ISBN 9781588345875, $29.95; ISBN 9781588345882 ebook, contact publiser for price.

Faraday-Talbot Effect From A Circular Array Of Pillars, Jessica J. Pilgram

Physics

When an oil bath is vertically oscillating with an acceleration above some critical value, known as the Faraday threshold, the bath surface becomes unstable and nonlinear standing wave patterns emerge. One phenomenon that has been observed above the Faraday threshold is the formation of Faraday-Talbot carpets, resulting from near-field diffraction. The optical Talbot effect occurs when a monochromatic wave passes through a diffraction grating. In the near-field, the formation of self- images is observed at integer multiples of what is known as the Talbot length. These two-dimensional patterns have various applications including X-ray imaging and atom and particle trapping. Two- …

Investigation Of Neutron Induced Ternary Fission With The Niffte Time Projection Chamber, Alex C. Kemnitz

Physics

Ternary fission is a rare occurrence in which three particles are produced from a single fission event. This analysis uses tracked fission event data recorded by NIFFTE’s time projection chamber with a series of refined cuts to isolate all possible ternary events. The experiment used two targets, each consisting of two isotopes; one target was Pu-239 and U-235, and the other was U-238 and U-235. The data was used to measure the ternary/binary fission ratios for each isotope. The ratios for the Pu-239 and U-235 target that were found are shown to be too high due to alpha contamination. The …

Climate Process Team On Internal Wave-Driven Ocean Mixing, Jennifer A. Mackinnon, Zhongxiang Zhao, Caitlin B. Whalen, Amy F. Waterhouse, David S. Trossman, Oliver M. Sun, Louis C. St. Laurent, Harper L. Simmons, Kurt Polzin, Robert Pinkel, Andrew Pickering, Nancy J. Norton, Jonathan D. Nash, Ruth Musgrave, Lynne M. Merchant, Angelique V. Melet, Benjamin Mater, Sonya Legg, Willima G. Large, Eric Kunze, Jody M. Klymak, Markus Jochum, Steven R. Jayne, Robert W. Hallberg, Stephen M. Griffies, Steve Diggs, Gokhan Danabasoglu, Eric P. Chassignet, Maarten C. Buijsman, Frank O. Bryan, Bruce P. Briegleb, Andrew Barna, Brian K. Arbic, Joseph K. Ansong, Matthew H. Alford

Faculty Publications

The study summarizes recent advances in our understanding of internal wave–driven turbulent mixing in the ocean interior and introduces new parameterizations for global climate ocean models and their climate impacts.

A Geophysical Model For The Origin Of Volcano Vent Clusters In A Colorado Plateau Volcanic Field, Fanghui Deng, Charles B. Connor, Rocco Malservisi, Laura J. Connor, Jeremy White, Aurélie Germa, Paul H. Wetmore

School of Geosciences Faculty and Staff Publications

Variation in spatial density of Quaternary volcanic vents, and the occurrence of vent clusters, correlates with boundaries in Proterozoic crust in the Springerville volcanic field (SVF), Arizona, USA. Inverse modeling using 538 gravity measurements shows that vent clusters correlate with gradients in the gravity field due to lateral variation in crustal density. These lateral discontinuities in the crustal density can be explained by boundaries in the North American crust formed during Proterozoic accretion. Spatial density of volcanic vents is low in regions of high‐density Proterozoic crust, high in areas of relatively low density Proterozoic crust, and is greatest adjacent to …

Introducing People With Asd To Crowd Work, Kotaro Hara, Jeffrey P. Bigham

Research Collection School Of Computing and Information Systems

Adults with Autism Spectrum Disorders (ASD) are unemployed at a high rate, in part because the constraints and expectations of traditional employment can be difficult for them. In this paper, we report on our work in introducing people with ASD to remote work on a crowdsourcing platform and a prototype tool we developed by working with participants. We conducted a six-week long user-centered design study with three participants with ASD. The early stage of the study focused on assessing the abilities of our participants to search and work on micro-tasks available on the crowdsourcing market. Based on our preliminary findings, …

Guest Editor's Introduction To The Special Issue On Source Code Analysis And Manipulation (Scam 2015), Foutse Khomh, David Lo, Michael W. Godfrey

Research Collection School Of Computing and Information Systems

We are happy to introduce you to this special issue that presents selected papers from the 15th IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM 2015). SCAM is a leading conference that brings together researchers and practitioners working on theory, techniques, and applications that concern analysis and/or manipulation of the source code of computer systems. While much attention in the wider software engineering community is properly directed towards other aspects of systems development and evolution, such as specification, design, and requirements engineering, it is the source code that contains the only precise description of the behavior of …

Assessing Morphodynamics Of The Lower Mississippi River From 1985 To 2015 With Remote Sensing And Gis Techniques, Bo Wang

LSU Doctoral Dissertations

The Lower Mississippi River is one of the most highly engineered rivers in the world. The river is now completely regulated by a combination of levees, artificial cutoffs, bank revetments, and dike fields; however, the river engineering has also complicated the geomorphological response to the sediment brought in the river. This dissertation research examined morphodynamics of the middle portion of the Lower Mississippi River from Vicksburg, Mississippi (river kilometer: 737) to Red River Landing, Louisiana (river kilometer: 486) to elucidate river engineering effects on sediment transport, storage, and distribution. The Old River Control Structure (ORCS) diverts approximately 25% of the …

First Exclusive Measurement Of Deeply Virtual Compton Scattering Off 4He: Toward The 3d Tomography Of Nuclei, M. Hattawy, N. A. Baltzell, R. Dupré, K. Hafidi, S. Stepanyan, S. Bültmann, R. De Vita, A. El Alaoui, L. El Fassi, H. Egiyan, B. Torayev, D. Adikaram, M. J. Amaryan, G. Charles, M. Khachatryan, A. Klein, S. E. Kuhn, M. Mayer, Y. Prok, L. B. Weinstein, Z. W. Zhao

Physics Faculty Publications

We report on the first measurement of the beam-spin asymmetry in the exclusive process of coherent deeply virtual Compton scattering off a nucleus. The experiment uses the 6 GeV electron beam from the Continuous Electron Beam Accelerator Facility (CEBAF) accelerator at Jefferson Lab incident on a pressurized ⁴He gaseous target placed in front of the CEBAF Large Acceptance Spectrometer (CLAS). The scattered electron is detected by CLAS and the photon by a dedicated electromagnetic calorimeter at forward angles. To ensure the exclusivity of the process, a specially designed radial time projection chamber is used to detect the recoiling ^{4 …}

Would You Like To Motivate Software Testers? Ask Them How, Ronnie Santos, Cleyton Magalhaes, Jorge S. Correia-Neto, Fabio Q. B. Silva Dr., Luiz Fernando Capretz, Rodrigo E. C. Souza

Electrical and Computer Engineering Publications

Considering the importance of software testing to the development of high quality and reliable software systems, this paper aims to investigate how can work-related factors influence the motivation of software testers. Method. We applied a questionnaire that was developed using a previous theory of motivation and satisfaction of software engineers to conduct a survey-based study to explore and understand how professional software testers perceive and value work-related factors that could influence their motivation at work. Results. With a sample of 80 software testers we observed that software testers are strongly motivated by variety of work, creative tasks, recognition for their …

On Demonstrating The Impact Of Defeasible Reasoning Via A Multi-Layer Argument-Based Framework (Doctoral Consortium), Lucas Middeldorf Rizzo

Conference papers

Promising results have indicated Argumentation Theory as a solid research area for implementing defeasible reasoning in practice. However, applications are usually domain dependent, not incorporating all the layers and steps required in an argumentation process, thus limit- ing their applicability in different areas. This PhD project is focused on the development of a multi-layer defeasible argument-based framework which is in turn used across different applications in the fields of decision making and knowledge representation and reasoning. The inference produced is compared against the inference of different quantitative theories of reasoning under uncertainty such as expert systems and fuzzy logic. The …