Physical Sciences and Mathematics Commons^™

A Framework For Identifying Host-Based Artifacts In Dark Web Investigations, Arica Kulm

Masters Theses & Doctoral Dissertations

The dark web is the hidden part of the internet that is not indexed by search engines and is only accessible with a specific browser like The Onion Router (Tor). Tor was originally developed as a means of secure communications and is still used worldwide for individuals seeking privacy or those wanting to circumvent restrictive regimes. The dark web has become synonymous with nefarious and illicit content which manifests itself in underground marketplaces containing illegal goods such as drugs, stolen credit cards, stolen user credentials, child pornography, and more (Kohen, 2017). Dark web marketplaces contribute both to illegal drug usage …

Iowa Waste Reduction Center Newsletter, November 2020, University Of Northern Iowa. Iowa Waste Reduction Center.

Iowa Waste Reduction Center Newsletter

Inside this Issue:

--- IWRC End of 2020 Director Address
--- IWRC Providing Compressed Air Assessment and Lighting Analysis
--- Iowa DNR creates EASY Air Equipment Deactivation Form
--- Industry News

Erica: Enabling Real-Time Mistake Detection And Corrective Feedback For Free-Weights Exercises, Meeralakshmi Radhakrishnan, Darshana Rathnayake, Koon Han Ong, Inseok Hwang, Archan Misra

Research Collection School Of Computing and Information Systems

We present ERICA, a digital personal trainer for users performing free weights exercises, with two key differentiators: (a) First, unlike prior approaches that either require multiple on-body wearables or specialized infrastructural sensing, ERICA uses a single in-ear "earable" device (piggybacking on a form factor routinely used by millions of gym-goers) and a simple inertial sensor mounted on each weight equipment; (b) Second, unlike prior work that focuses primarily on quantifying a workout, ERICA additionally identifies a variety of fine-grained exercising mistakes and delivers real-time, in-situ corrective instructions. To achieve this, we (a) design a robust approach for user-equipment association that …

Quotient-Transitivity And Cyclic Subgroup-Transitivity, Brendan Goldsmith, Ketao Gong

Articles

We introduce two new notions of transitivity for Abelian 𝑝-groups based on isomorphism of quotients rather than the classical use of equality of height sequences associated with Abelian 𝑝-group theory. Unlike the classical theory where “most” groups are transitive, these new notions lead to much smaller classes, but even these classes are sufficiently large to be interesting.

Contact Graphs Of Ball Packings, Alexey Glazyrin

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

A contact graph of a packing of closed balls is a graph with balls as vertices and pairs of tangent balls as edges. We prove that the average degree of the contact graph of a packing of balls (with possibly different radii) in R3 is not greater than 13.955. We also find new upper bounds for the average degree of contact graphs in R4 and R5.

Multi-Hop Inference For Question-Driven Summarization, Yang Deng, Wenxuan Zhang, Wai Lam

Research Collection School Of Computing and Information Systems

Question-driven summarization has been recently studied as an effective approach to summarizing the source document to produce concise but informative answers for non-factoid questions. In this work, we propose a novel question-driven abstractive summarization method, Multi-hop Selective Generator (MSG), to incorporate multi-hop reasoning into question-driven summarization and, meanwhile, provide justifications for the generated summaries. Specifically, we jointly model the relevance to the question and the interrelation among different sentences via a human-like multi-hop inference module, which captures important sentences for justifying the summarized answer. A gated selective pointer generator network with a multi-view coverage mechanism is designed to integrate diverse …

Learning Personal Conscientiousness From Footprints In E-Learning Systems, Lo Pang-Yun Ting, Shan Yun Teng, Kun Ta Chuang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Personality inference has received widespread attention for its potential to infer psychological well being, job satisfaction, romantic relationship success, and professional performance. In this research, we focus on Conscientiousness, one of the well studied Big Five personality traits, which determines if a person is self-disciplined, organized, and hard-working. Research has shown that Conscientiousness is related to a person's academic and workplace success. For an expert to evaluate a person's Conscientiousness, long-term observation of the person's behavior at work place or at home is usually required. To reduce this evaluation effort as well as to cope with the increasing trend of …

Attribute-Based Keyword Search Over Hierarchical Data In Cloud Computing, Yinbin Miao, Jianfeng Ma, Ximeng Liu, Xinghua Li, Qi Jiang, Junwei Zhang

Research Collection School Of Computing and Information Systems

Searchable encryption (SE) has been a promising technology which allows users to perform search queries over encrypted data. However, the most of existing SE schemes cannot deal with the shared records that have hierarchical structures. In this paper, we devise a basic cryptographic primitive called as attribute-based keyword search over hierarchical data (ABKS-HD) scheme by using the ciphertext-policy attribute-based encryption (CP-ABE) technique, but this basic scheme cannot satisfy all the desirable requirements of cloud systems. The facts that the single keyword search will yield many irrelevant search results and the revoked users can access the unauthorized data with the old …

Beyond Accuracy: Assessing Software Documentation Quality, Christoph Treude, Justin Middleton, Thushari Atapattu

Research Collection School Of Computing and Information Systems

Good software documentation encourages good software engineering, but the meaning of “good” documentation is vaguely defined in the software engineering literature. To clarify this ambiguity, we draw on work from the data and information quality community to propose a framework that decomposes documentation quality into ten dimensions of structure, content, and style. To demonstrate its application, we recruited technical editors to apply the framework when evaluating examples from several genres of software documentation. We summarise their assessments—for example, reference documentation and README files excel in quality whereas blog articles have more problems—and we describe our vision for reasoning about software …

Selecting Third-Party Libraries: The Practitioners' Perspective, Enrique Larios Vargas, Maurício Aniche, Christoph Treude, Magiel Bruntink, Georgios Gousios

Research Collection School Of Computing and Information Systems

The selection of third-party libraries is an essential element of virtually any software development project. However, deciding which libraries to choose is a challenging practical problem. Selecting the wrong library can severely impact a software project in terms of cost, time, and development effort, with the severity of the impact depending on the role of the library in the software architecture, among others. Despite the importance of following a careful library selection process, in practice, the selection of third-party libraries is still conducted in an ad-hoc manner, where dozens of factors play an influential role in the decision. In this …

Exploring The Impact Of Covid-19 On Aviation Industry: A Text Mining Approach, Gottipati Swapna, Kyong Jin Shim, Weiling Angeline Jiang, Sheng Wei Andre Justin Lee

Research Collection School Of Computing and Information Systems

Our study presents a comprehensive analysis of news articles from FlightGlobal website during the first half of 2020. Our analyses reveal useful insights on themes and trends concerning the aviation industry during the COVID-19 period. We applied text mining and NLP techniques to analyse the articles for extracting the aviation themes and article sentiments (positive and negative). Our results show that there is a variation in the sentiment trends for themes aligned with the real-world developments of the pandemic. The article sentiment analysis can offer industry players a quick sense of the nature of developments in the industry. Our article …

Enhancing Developer Interactions With Programming Screencasts Through Accurate Code Extraction, Lingfeng Bao, Shengyi Pan, Zhenchang Xing, Xin Xia, David Lo, Xiaohu Yang

Research Collection School Of Computing and Information Systems

Programming screencasts have become a pervasive resource on the Internet, which is favoured by many developers for learning new programming skills. For developers, the source code in screencasts is valuable and important. However, the streaming nature of screencasts limits the choice that they have for interacting with the code. Many studies apply the Optical Character Recognition (OCR) technique to convert screen images into text, which can be easily searched and indexed. However, we observe that the noise in the screen images significantly affects the quality of OCRed code.In this paper, we develop a tool named psc2code, which has two components, …

Potential Virus-Mediated Nitrogen Cycling In Oxygen-Depleted Oceanic Waters, M. Consuelo Gazitúa, Dean R. Vik, Simon Roux, Ann C. Gregory, Benjamin Bolduc, Brittany Widner, Margaret R. Mulholland, Steven J. Hallam, Osvaldo Ulloa, Matthew B. Sullivan

OES Faculty Publications

Viruses play an important role in the ecology and biogeochemistry of marine ecosystems. Beyond mortality and gene transfer, viruses can reprogram microbial metabolism during infection by expressing auxiliary metabolic genes (AMGs) involved in photosynthesis, central carbon metabolism, and nutrient cycling. While previous studies have focused on AMG diversity in the sunlit and dark ocean, less is known about the role of viruses in shaping metabolic networks along redox gradients associated with marine oxygen minimum zones (OMZs). Here, we analyzed relatively quantitative viral metagenomic datasets that profiled the oxygen gradient across Eastern Tropical South Pacific (ETSP) OMZ waters, assessing whether OMZ …

Deepfrag-K: A Fragment-Based Deep Learning Approach For Protein Fold Recognition, Wessam Elhefnawy, Min Li, Jianxin Wang, Yaohang Li

Computer Science Faculty Publications

Background: One of the most essential problems in structural bioinformatics is protein fold recognition. In this paper, we design a novel deep learning architecture, so-called DeepFrag-k, which identifies fold discriminative features at fragment level to improve the accuracy of protein fold recognition. DeepFrag-k is composed of two stages: the first stage employs a multi-modal Deep Belief Network (DBN) to predict the potential structural fragments given a sequence, represented as a fragment vector, and then the second stage uses a deep convolutional neural network (CNN) to classify the fragment vector into the corresponding fold.

Results: Our results show that DeepFrag-k yields …

Extreme Events And Emergency Scales, Veniamin Smirnov, Zhuanzhuan Ma, Dimitri Volchenkov

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

An event is extreme if its magnitude exceeds the threshold. A choice of a threshold is subject to uncertainty caused by a method, the size of available data, a hypothesis on statistics, etc. We assess the degree of uncertainty by the Shannon's entropy calculated on the probability that the threshold changes at any given time. If the amount of data is not sufficient, an observer is in the state of Lewis Carroll's Red Queen who said "When you say hill, I could show you hills, in comparison with which you'd call that a valley". If we have enough data, the …

Galaxy And Mass Assembly: A Comparison Between Galaxy⇓Galaxy Lens Searches In Kids/Gama, Shawn Knabel, Rebecca L. Steele, Benne W. Holwerda, Joanna S. Bridge, Alice Jacques, Andrew M. Hopkins, Stephen P. Bamford, Michael J.I. Brown, Sarah Brough, Lee Kelvin, Maciej Bilicki, John Kielkopf

Faculty and Staff Scholarship

Strong gravitational lenses are a rare and instructive type of astronomical object. Identification has long relied on serendipity, but different strategies—such as mixed spectroscopy of multiple galaxies along the line of sight, machine-learning algorithms, and citizen science—have been employed to identify these objects as new imaging surveys become available. We report on the comparison between spectroscopic, machine-learning, and citizen-science identification of galaxy–galaxy lens candidates from independently constructed lens catalogs in the common survey area of the equatorial fields of the Galaxy and Mass Assembly survey. In these, we have the opportunity to compare high completeness spectroscopic identifications against high-fidelity imaging …

Re-Examining The Radial Distributions Of M13 Multiple Populations, Jason P. Smolinski, Willem B. Hoogendam, Alex J. Van Kooten, Peyton Benac

University Faculty Publications and Creative Works

We seek to resolve the tension in the literature regarding the presence of radially segregated multiple populations in the Galactic globular cluster M13. Previous studies of this nearby cluster have presented discordant results about the degree of dynamical mixing in M13's inner region. Using ground-based (UBVI) photometry, we show that cumulative radial distributions of stars on the blue and red sides of the red giant branch are statistically identical. Interestingly, these results are obtained using data from large-aperture, ground-based telescopes as well as a more modestly sized instrument, and both are in agreement with previous work done using Hubble Space …

Galaxy And Mass Assembly: Luminosity And Stellar Mass Functions In Gama Groups, J. A. Vazquez-Mata, J. Loveday, S. D. Riggs, I. K. Baldry, L. J.M. Davies, A. S.G. Robotham, Benne W. Holwerda, M. J.I. Brown, M. E. Cluver, L. Wang, M. Alpaslan, J. Bland-Hawthorn, S. Brough, S. P. Driver, A. M. Hopkins, E. N. Taylor, A. H. Wright

Faculty and Staff Scholarship

How do galaxy properties (such as stellar mass, luminosity, star formation rate, and morphology) and their evolution depend on the mass of their host dark matter halo? Using the Galaxy and Mass Assembly group catalogue, we address this question by exploring the dependence on host halo mass of the luminosity function (LF) and stellar mass function (SMF) for grouped galaxies subdivided by colour, morphology, and central/satellite. We find that spheroidal galaxies in particular dominate the bright and massive ends of the LF and SMF, respectively. More massive haloes host more massive and more luminous central galaxies. The satellites LF and …

Telescope Parallel Actuator Mount: Control And Testing, Samuel S. Artho-Bentz

Master's Theses

This thesis approaches the task of designing a control system for the Parallel Actuator Mount developed by Dr. John Ridgely and Mr. Garrett Gudgel. It aims to create a base framework that directly controls the telescope and can be expanded to accept external command. It incorporates lower priced components and develops more easily approachable software with great functionality. An open-loop method for velocity control is established. Developing repeatable tests is a major focus. Testing finds the control methods developed result in velocity error of less than 5% and position error of less than 1.5% despite several mechanical issues and inaccuracies. …

Sfuzz: An Efficient Adaptive Fuzzer For Solidity Smart Contracts, Tai D. Nguyen, Long H. Pham, Jun Sun, Yun Lin, Minh Quang Tran

Research Collection School Of Computing and Information Systems

Smart contracts are Turing-complete programs that execute on the infrastructure of the blockchain, which often manage valuable digital assets. Solidity is one of the most popular programming languages for writing smart contracts on the Ethereum platform. Like traditional programs, smart contracts may contain vulnerabilities. Unlike traditional programs, smart contracts cannot be easily patched once they are deployed. It is thus important that smart contracts are tested thoroughly before deployment. In this work, we present an adaptive fuzzer for smart contracts on the Ethereum platform called sFuzz. Compared to existing Solidity fuzzers, sFuzz combines the strategy in the AFL fuzzer and …

A Survey Of Typical Attributed Graph Queries, Yanhao Wang, Yuchen Li, Ju Fan, Chang Ye, Mingke Chai

Research Collection School Of Computing and Information Systems

Graphs are commonly used for representing complex structures such as social relationships, biological interactions, and knowledge bases. In many scenarios, graphs not only represent topological relationships but also store the attributes that denote the semantics associated with their vertices and edges, known as attributed graphs. Attributed graphs can meet demands for a wide range of applications, and thus a variety of queries on attributed graphs have been proposed. However, these diverse types of attributed graph queries have not been systematically investigated yet. In this paper, we provide an extensive survey of several typical types of attributed graph queries. We propose …

Machine Learning Integrated Design For Additive Manufacturing, Jingchao Jiang, Yi Xiong, Zhiyuan Zhang, David W. Rosen

Research Collection School Of Computing and Information Systems

For improving manufacturing efficiency and minimizing costs, design for additive manufacturing (AM) has been accordingly proposed. The existing design for AM methods are mainly surrogate model based. Due to the increasingly available data nowadays, machine learning (ML) has been applied to medical diagnosis, image processing, prediction, classification, learning association, etc. A variety of studies have also been carried out to use machine learning for optimizing the process parameters of AM with corresponding objectives. In this paper, a ML integrated design for AM framework is proposed, which takes advantage of ML that can learn the complex relationships between the design and …

Global Context Aware Convolutions For 3d Point Cloud Understanding, Zhiyuan Zhang, Binh-Son Hua, Wei Chen, Yibin Tian, Sai-Kit Yeung

Research Collection School Of Computing and Information Systems

Recent advances in deep learning for 3D point clouds have shown great promises in scene understanding tasks thanks to the introduction of convolution operators to consume 3D point clouds directly in a neural network. Point cloud data, however, could have arbitrary rotations, especially those acquired from 3D scanning. Recent works show that it is possible to design point cloud convolutions with rotation invariance property, but such methods generally do not perform as well as translation-invariant only convolution. We found that a key reason is that compared to point coordinates, rotation-invariant features consumed by point cloud convolution are not as distinctive. …

Tangi: Tangible Proxies For Embodied Object Exploration And Manipulation In Virtual Reality, Martin Feick, Scott Bateman, Anthony Tang, Anthony Tang

Research Collection School Of Computing and Information Systems

Exploring and manipulating complex virtual objects is challenging due to limitations of conventional controllers and free-hand interaction techniques. We present the TanGi toolkit which enables novices to rapidly build physical proxy objects using Composable Shape Primitives. TanGi also provides Manipulators allowing users to build objects including movable parts, making them suitable for rich object exploration and manipulation in VR. With a set of different use cases and applications we show the capabilities of the TanGi toolkit and evaluate its use. In a study with 16 participants, we demonstrate that novices can quickly build physical proxy objects using the Composable Shape …

Highly Efficient And Scalable Multi-Hop Ride-Sharing, Yixin Xu, Lars Kulik, Renata Borovica‐Gajic, Abdullah Aldwyish, Jianzhong Qi

Research Collection School Of Computing and Information Systems

On-demand ride-sharing services such as Uber and Lyft have gained tremendous popularity over the past decade, largely driven by the omnipresence of mobile devices. Ride-sharing services can provide economic and environmental benefits such as reducing traffic congestion and vehicle emissions. Multi-hop ride-sharing enables passengers to transfer between vehicles within a single trip, which significantly extends the benefits of ride-sharing and provides ride opportunities that are not possible otherwise. Despite its advantages, offering real-time multi-hop ride-sharing services at large scale is a challenging computational task due to the large combination of vehicles and passenger transfer points. To address these challenges, we …

Base-Package Recommendation Framework Based On Consumer Behaviours In Iptv Platform, Kuruparan Shanmugalingam, Ruwinda Ranganayanke, Chanka Gunawardhaha, Rajitha Navarathna

Research Collection School Of Computing and Information Systems

Internet Protocol TeleVision (IPTV) provides many services such as live television streaming, time-shifted media, and Video On Demand (VOD). However, many customers do not engage properly with their subscribed packages due to a lack of knowledge and poor guidance. Many customers fail to identify the proper IPTV service package based on their needs and to utilise their current package to the maximum. In this paper, we propose a base-package recommendation model with a novel customer scoring-meter based on customers behaviour. Initially, our paper describes an algorithm to measure customers engagement score, which illustrates a novel approach to track customer engagement …

How Should We Understand The Digital Economy In Asia? Critical Assessment And Research Agenda, Kai Li, Dan J. Kim, Karl R. Lang, Robert J. Kauffman, Maurizio Naldi

Research Collection School Of Computing and Information Systems

By Asian digital economy, we refer to high-tech developments, business and social transformations, and information-driven changes in the region's growth. We discuss its background and foundations, significance in Asia and contribution to removal of historical barriers in traditional business. We assess how new value chains are transforming country-level involvement in worldwide manufacturing and note "smiling curve theory" predictions about the global value chain in Asia for high-tech firms and their economies. The takeaway is that the digital economy in Asian nations involves revamping business processes through technology innovation, government policies for growth, and digital entrepreneurship. We analyze the "digital economy …

Empowering Singapore’S Smes: Fintech P2p Lending — A Lifeline For Smes’ Survival?, Grace Lee, Alan Megargel

Research Collection School Of Computing and Information Systems

The COVID-19 pandemic has sent shock waves throughout the world, pushed countries into lockdown, and wreaked havoc on the world’s people and the global economy. The damage to economies around the world caused by the COVID-19 pandemic has far exceeded that of the global financial crisis. While all businesses suffered hugely, it would be of grave consequence if the small and medium-sized enterprises (SMEs), an important segment of every country’s economy, are unable to withstand the shock wave and sustain themselves beyond this pandemic. The COVID-19 pandemic has highlighted the importance of cash flow or working capital for the viability …

Perceptions, Expectations, And Challenges In Defect Prediction, Zhiyuan Wan, Xin Xia, Ahmed E. Hassan, David Lo, Jianwei Yin, Xiaohu Yang

Research Collection School Of Computing and Information Systems

Defect prediction has been an active research area for over four decades. Despite numerous studies on defect prediction, the potential value of defect prediction in practice remains unclear. To address this issue, we performed a mixed qualitative and quantitative study to investigate what practitioners think, behave and expect in contrast to research findings when it comes to defect prediction. We collected hypotheses from open-ended interviews and a literature review, followed by a validation survey. We received 395 responses from practitioners. Some of our key findings include: 1) Over 90% of respondents are willing to adopt defect prediction techniques. 2) There …

The Dark Side Of Sustainability Orientation For Sme Performance, Teemu Kautonen, Simon J.D. Schillebeeckx, Johannes Gartner, Henri Hakata, Katariina Salmela-Aro, Kirsi Snellmand

Research Collection Lee Kong Chian School Of Business

This article examines how a firm’s willingness to make trade-offs that favour sustainability over commercial goals attenuates the relationship between firm-level sustainability orientation and subsequent performance. The hypothesis development draws on stakeholder theory and the literature on mission and revenue drifts, while the empirical analysis is based on two waves of original survey data on Finnish manufacturing SMEs. We find that sustainability orientation is positively associated with performance only when the willingness to make sustainability trade-offs is low, whereas the relationship becomes negative when the willingness to make such trade-offs is high. Our findings thus suggest that the popular adage …