Digital Commons Network^™

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 …

Intent Recognition In Smart Living Through Deep Recurrent Neural Networks, Xiang Zhang, Lina Yao, Chaoran Huang, Quan Z. Sheng, Xianzhi Wang

Research Collection School Of Computing and Information Systems

Electroencephalography (EEG) signal based intent recognition has recently attracted much attention in both academia and industries, due to helping the elderly or motor-disabled people controlling smart devices to communicate with outer world. However, the utilization of EEG signals is challenged by low accuracy, arduous and time-consuming feature extraction. This paper proposes a 7-layer deep learning model to classify raw EEG signals with the aim of recognizing subjects’ intents, to avoid the time consumed in pre-processing and feature extraction. The hyper-parameters are selected by an Orthogonal Array experiment method for efficiency. Our model is applied to an open EEG dataset provided …

Collaborative Topic Regression With Denoising Autoencoder For Content And Community Co-Representation, Trong T. Nguyen, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Personalized recommendation of items frequently faces scenarios where we have sparse observations on users' adoption of items. In the literature, there are two promising directions. One is to connect sparse items through similarity in content. The other is to connect sparse users through similarity in social relations. We seek to integrate both types of information, in addition to the adoption information, within a single integrated model. Our proposed method models item content via a topic model, and user communities via an autoencoder model, while bridging a user's community-based preference to her topic-based preference. Experiments on public real-life data showcase the …

Indexable Bayesian Personalized Ranking For Efficient Top-K Recommendation, Dung D. Le, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Top-k recommendation seeks to deliver a personalized recommendation list of k items to a user. The dual objectives are (1) accuracy in identifying the items a user is likely to prefer, and (2) efficiency in constructing the recommendation list in real time. One direction towards retrieval efficiency is to formulate retrieval as approximate k nearest neighbor (kNN) search aided by indexing schemes, such as locality-sensitive hashing, spatial trees, and inverted index. These schemes, applied on the output representations of recommendation algorithms, speed up the retrieval process by automatically discarding a large number of potentially irrelevant items when given a user …

Tweet Geolocation: Leveraging Location, User And Peer Signals, Wen-Haw Chong, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Which venue is a tweet posted from? We referred this as fine-grained geolocation. To solve this problem effectively, we develop novel techniques to exploit each posting user's content history. This is motivated by our finding that most users do not share their visitation history, but have ample content history from tweet posts. We formulate fine-grained geolocation as a ranking problem whereby given a test tweet, we rank candidate venues. We propose several models that leverage on three types of signals from locations, users and peers. Firstly, the location signals are words that are indicative of venues. We propose a location-indicative …

Modeling Check-In Behavior With Geographical Neighborhood Influence Of Venues, Thanh Nam Doan, Ee Peng Lim

Research Collection School Of Computing and Information Systems

With many users adopting location-based social networks (LBSNs) to share their daily activities, LBSNs become a gold mine for researchers to study human check-in behavior. Modeling such behavior can benefit many useful applications such as urban planning and location-aware recommender systems. Unlike previous studies [4,6,12,17] that focus on the effect of distance on users checking in venues, we consider two venue-specific effects of geographical neighborhood influence, namely, spatial homophily and neighborhood competition. The former refers to the fact that venues share more common features with their spatial neighbors, while the latter captures the rivalry of a venue and its nearby …

Large Scale Kernel Methods For Online Auc Maximization, Yi Ding, Chenghao Liu, Peilin Zhao, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Learning to optimize AUC performance for classifying label imbalanced data in online scenarios has been extensively studied in recent years. Most of the existing work has attempted to address the problem directly in the original feature space, which may not suitable for non-linearly separable datasets. To solve this issue, some kernel-based learning methods are proposed for non-linearly separable datasets. However, such kernel approaches have been shown to be inefficient and failed to scale well on large scale datasets in practice. Taking this cue, in this work, we explore the use of scalable kernel-based learning techniques as surrogates to existing approaches: …

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 …

Highly Efficient Mining Of Overlapping Clusters In Signed Weighted Networks, Tuan-Anh Hoang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

In many practical contexts, networks are weighted as their links are assigned numerical weights representing relationship strengths or intensities of inter-node interaction. Moreover, the links' weight can be positive or negative, depending on the relationship or interaction between the connected nodes. The existing methods for network clustering however are not ideal for handling very large signed weighted networks. In this paper, we present a novel method called LPOCSIN (short for "Linear Programming based Overlapping Clustering on Signed Weighted Networks") for efficient mining of overlapping clusters in signed weighted networks. Different from existing methods that rely on computationally expensive cluster cohesiveness …

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 …

Language Inclusion Checking Of Timed Automata With Non-Zenoness, Xinyu Wang, Jun Sun, Ting Wang, Shengchao Qin

Research Collection School Of Computing and Information Systems

Given a timed automaton P modeling an implementation and a timed automaton S as a specification, the problem of language inclusion checking is to decide whether the language of P is a subset of that of S. It is known to be undecidable. The problem gets more complicated if non-Zenoness is taken into consideration. A run is Zeno if it permits infinitely many actions within finite time. Otherwise it is non-Zeno. Zeno runs might present in both P and S. It is necessary to check whether a run is Zeno or not so as to avoid presenting Zeno runs as …

Improving Probability Estimation Through Active Probabilistic Model Learning, Jingyi Wang, Xiaohong Chen, Jun Sun, Shengchao Qin

Research Collection School Of Computing and Information Systems

It is often necessary to estimate the probability of certain events occurring in a system. For instance, knowing the probability of events triggering a shutdown sequence allows us to estimate the availability of the system. One approach is to run the system multiple times and then construct a probabilistic model to estimate the probability. When the probability of the event to be estimated is low, many system runs are necessary in order to generate an accurate estimation. For complex cyber-physical systems, each system run is costly and time-consuming, and thus it is important to reduce the number of system runs …

A Semantics Comparison Workbench For A Concurrent, Asynchronous, Distributed Programming Language, Claudio Corrodi, Alexander Heußner, Christopher M. Poskitt

Research Collection School Of Computing and Information Systems

A number of high-level languages and libraries have been proposed that offer novel and simple to use abstractions for concurrent, asynchronous, and distributed programming. The execution models that realise them, however, often change over time---whether to improve performance, or to extend them to new language features---potentially affecting behavioural and safety properties of existing programs. This is exemplified by SCOOP, a message-passing approach to concurrent object-oriented programming that has seen multiple changes proposed and implemented, with demonstrable consequences for an idiomatic usage of its core abstraction. We propose a semantics comparison workbench for SCOOP with fully and semi-automatic tools for analysing …

Enabling Phased Array Signal Processing For Mobile Wifi Devices, Kun Qian, Chenshu Wu, Zheng Yang, Zimu Zhou, Xu Wang, Yunhao Liu

Research Collection School Of Computing and Information Systems

Modern mobile devices are equipped with multiple antennas, which brings various wireless sensing applications such as accurate localization, contactless human detection, and wireless human-device interaction. A key enabler for these applications is phased array signal processing, especially Angle of Arrival (AoA) estimation. However, accurate AoA estimation on commodity devices is non-trivial due to limited number of antennas and uncertain phase offsets. Previous works either rely on elaborate calibration or involve contrived human interactions. In this paper, we aim to enable practical AoA measurements on commodity off-the-shelf (COTS) mobile devices. The key insight is to involve users’ natural rotation to formulate …

Lysdexic, Kaylee Dudley

USU Student Folklore Fieldwork

So dyslexia is very prominent in my family um we got I my grandpa has dyslexia my mom and dad both have dyslexia my little brother has dyslexia um cousins. I mean everybody in my I swear half my family has dyslexia um and so… but my grandpa to save his life cannot say “dyslexia”. Um he calls it “lysdexia”, or “lysdexic” he’s “lysdexic”. Um and so it’s kind of it’s it’s kinda funny because dyslexic people are teased all the time for reversing things or saying doing things backwards writing letters in reverse order um. And my grandpa can’t …

Standardized Testing, Kaylee Dudley

USU Student Folklore Fieldwork

When we do standardized assessments um there’s one in particular that we use and when you follow like the standardized protocol you do every test item in order. Um and that’s the way you are expected to do the test protocol that’s the only way it’s standardized assessment but I have never met a therapist in my entire life who goes in that order. There’s def [Inaudible as speaker and collector say something at once.] There’s an unspoken rule between therapists that you do similar test items together. (Okay) So like um some of the test has um kids imitate …

Math Lady Meme, Melissa Herrera

USU Student Folklore Fieldwork

No abstract provided.

Funny Looking Kid, Kaylee Dudley

USU Student Folklore Fieldwork

So FLK is like stands for “funny looking kid” and it’s not like meant as a mean…thing.

Reproducible Research For Computing In Science & Engineering, Lorena A. Barba, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

The editors of the new track for reproducible research outline the parameters for future peer review, submission, and access, highlighting the magazine’s previous work in this field and some of the challenges still to come.

Monitoring Learning Against The Sustainable Development Goals, Australian Council For Educational Research (Acer)

Monitoring Learning

The Global Alliance to Monitor Learning (GAML) is an international collaboration to improve learning around the world, led by the UNESCO Institute for Statistics (UIS). The Australian Council for Educational Research Centre for Global Education Monitoring (ACER-GEM) has a major role in supporting GAML, as the UIS’s technical partner. This publication outlines ACER’s role in the work plan of the Global Alliance to Monitor Learning.

The Sequence Stratigraphic Context Of Mixed Basin Margin Evaporites In The Harrisburg Member Of The Permian Kaibab Formation, Northern Arizona And Southern Utah, Cole Hendrickson

Electronic Theses and Dissertations

The Kaibab Formation is a mixed carbonate system including evaporites and siliciclastics deposited on a westward dipping epeiric carbonate ramp during the middle Permian in northern Arizona, southern Utah, and eastern Nevada. It consists of the Fossil Mountain Member deposited in open-marine conditions and the overlying Harrisburg Member deposited in restricted conditions. The Harrisburg Member includes facies and depositional environments ranging from open-marine shallow-subtidal wackestone - packstone, restricted subtidal dolomitic mudstone, dolomitic sandstone, peritidal oolitic grainstone as well as gypsum and red siltstones deposited in a sabkha environment.

Fourteen stratigraphic sections were measured across northern Arizona and southern Utah to …

Genetic Identification And Population Characteristics Of Deep-Sea Cephalopod Species In The Gulf Of Mexico And Northwestern Atlantic Ocean, Amanda Sosnowski

USF Tampa Graduate Theses and Dissertations

Nearly all deep-sea cephalopod life history studies have been completed by examination of specimens collected in the wild. Much of this work is like piecing together a puzzle; knowledge of the life history of many species remains fragmented and hence, taxonomically and phylogenetically confused. Molecular approaches and sequencing technologies are powerful tools for deciphering wild-type cephalopod life history and population dynamics. Use of molecular markers offers additional certainty for identifying specimens damaged during deep-sea collections and can elucidate often cryptic, intra- and interspecific diversity. The research presented in this study assessed broad genetic patterns of biodiversity in deep-sea cephalopods from …

Building Planner Commitment: Are California’S Sb 375 And Oregon’S Sb 1059 Models For Climate-Change Mitigation?, Keith Bartholomew, David Proffitt

TREC Final Reports

California’s Sustainable Communities and Climate Protection Act (SB 375) and the Oregon Sustainable Transportation Initiative (SB 1059) have made them the first states in the nation to try and reduce greenhouse gas (GHG) emissions using the transportation-planning process. Evaluating how these pioneering laws have changed local planning processes – as well as plans themselves – in each state provides insight into the laws’ effectiveness at changing development patterns in a way that reduces GHG emissions, without waiting decades to see the effects in the built environment. Both states’ laws require metropolitan planning organizations (MPOs) and the municipalities that comprise them …

Using The Planning Process To Mitigate Climate Change, Keith Bartholomew

TREC Project Briefs

This research evaluates how Oregon’s SB 1059 and California’s SB 375 have integrated climate change mitigation strategies into local planning processes, and seeks to understand how transportation planning can help slow climate change.

Deconstruction In Portland: Summary Of Activity, Emma Willingham, Peter Hulseman, Mike Paruszkiewicz

Northwest Economic Research Center Publications and Reports

On October 31st, 2016, the City of Portland instituted an ordinance requiring the deconstruction of all residential homes and duplexes built prior to 1917 or possessing a historical designation. Deconstruction is a relatively new industry, and with this local regulatory encouragement, several new contractors became certified to participate in the expanded market. This report provides background on the industry, largely from the 2016 report researched and written by the Northwest Economic Research Center (NERC) in anticipation of the requirement, and an examination of what has occurred in the year following the ordinance’s passage, using deconstruction and demolition permit data and …

Inquiry At The Heart Of Teacher Preparation, Maika Yeigh

Curriculum and Instruction Faculty Publications and Presentations

This essay describes the action research projects and culminating conference for a Graduate Teacher Education Program. Teacher candidates conduct year-long research projects with the dual-goal of building a reflective inquiry stance and improving instructional practice.

Spice: Secure Proximity-Based Infrastructure For Close Encounters, Aarathi Prasad, Xiaohui Liang, David Kotz

Dartmouth Scholarship

We present a crowdsourcing system that extends the capabilities of location-based applications and allows users to connect and exchange information with users in spatial and temporal proximity. We define this incident of spatio-temporal proximity as a \em close encounter. Typically, location-based application users store their information on a server, and trust the server to provide access only to authorized users, not misuse the data or disclose their location history. Our system, called SPICE, addresses these privacy issues by leveraging Wi-Fi access points to connect users and encrypt their information before it is exchanged, so only users in close encounters have …

40ar/39ar Ages, Compositions, And Likely Source Of The Eocene Fallout Tuffs In The Duchesne River Formation, Northeastern Utah, Michael Seth Jensen

Theses and Dissertations

Thin fallout tuffs in the Duchesne River Formation in the Uinta Basin, Utah are evidence that volcanism was active in northern Nevada and Utah in the late Eocene. The Uinta Basin is a sedimentary basin that formed during the Laramide orogeny. Ponded lakes of various salinity filled and emptied and during the late Eocene the northern rim was dominated by a wetland/floodplain depositional setting. Most of the tuffs have rhyolitic mineral assemblages including quartz, biotite, sanidine, and allanite. Rhyolitic glass shards were also found in one of the ash beds. Biotite compositions have Fe/(Fe+Mg) ratios typical of calc-alkaline igneous rocks …

From Quantum To Classical Interactions Between A Free Electron And A Surface, Peter Beierle

Department of Physics and Astronomy: Dissertations, Theses, and Student Research

Quantum theory is often cited as being one of the most empirically validated theories in terms of its predictive power and precision. These attributes have led to numerous scientific discoveries and technological advancements. However, the precise relationship between quantum and classical physics remains obscure. The prevailing description is known as decoherence theory, where classical physics emerges from a more general quantum theory through environmental interaction. Sometimes referred to as the decoherence program, it does not solve the quantum measurement problem. We believe experiments performed between the microscopic and macroscopic world may help finish the program. The following considers a free …

The Evolutionary Origin Of Digit Patterning, T Stewart, Ramray Bhat, Stuart Newman

NYMC Faculty Publications

The evolution of tetrapod limbs from paired fins has long been of interest to both evolutionary and developmental biologists. Several recent investigative tracks have converged to restructure hypotheses in this area. First, there is now general agreement that the limb skeleton is patterned by one or more Turing-type reaction-diffusion, or reaction-diffusion-adhesion, mechanism that involves the dynamical breaking of spatial symmetry. Second, experimental studies in finned vertebrates, such as catshark and zebrafish, have disclosed unexpected correspondence between the development of digits and the development of both the endoskeleton and the dermal skeleton of fins. Finally, detailed mathematical models in conjunction with …