Digital Commons Network^™

Scars & Lyres, William Wright Harris

EWU Masters Thesis Collection

No abstract provided.

Effectiveness Of Executive Functioning Interventions Among Homeless Elementary Aged Students, Julia Warmack, Abby Jessen, Taylor Koopmeiners

Critically Appraised Topics

Elementary-aged children who are homeless face challenges in the areas of self-regulation, working memory, attention, and time management (Wanger-Fuhs et al., 2014). Currently, there is a lack of research on homeless elementary-aged children and the influence occupational therapy can have on their academic success. Specifically, there is no comprehensive source that details the effects of the role of occupational therapy interventions on executive functioning skills such as self-regulation, working memory, attention, and time management for the population of homeless elementary-aged school children. The purpose of this CAT paper was to determine the effect of occupational therapy interventions that focus on …

New Political Ecologies Of Renewable Energy, Sarah Knuth, Ingrid Behrsin, Anthony Levenda, James Mccarthy

Geography

The critique of fossil fuel regimes has been a foundational concern for the field of political ecology, in its drives to expose the injustices and harms of energy extractivism and its early warnings of the climate crisis. However, it is increasingly evident that renewable energy sources and their infrastructures will carry their own costs and trade-offs, and that critique, resistance and alternative movement-building are needed to forge a truly just renewable energy transition. This theme issue underlines the many ways in which political ecology is well-positioned to lead critical and engaged scholarship in support of energy/climate justice. In this introduction …

Phytoplankton Bloom Stages Estimated From Chlorophyll Pigment Proportions Suggest Delayed Summer Production In Low Sea Ice Years In The Northern Bering Sea, Clare B. Gaffey, Karen E. Frey, Lee W. Cooper, Jacqueline M. Grebmeier

Geography

Decreased sea ice cover in the northern Bering Sea has altered annual phytoplankton phenology owing to an expansion of open water duration and its impact on ocean stratification. Limitations of satellite remote sensing such as the inability to detect bloom activity throughout the water column, under ice, and in cloudy conditions dictate the need for shipboard based measurements to provide more information on bloom dynamics. In this study, we adapted remote sensing land cover classification techniques to provide a new means to determine bloom stage from shipboard samples. Specifically, we used multiyear satellite time series of chlorophyll a to determine …

The Pacific Drought Knowledge Exchange: A Co-Production Approach To Deliver Climate Resources To User Groups, Ryan J. Longman, Abby G. Frazier, Christian P. Giardina, Elliott W. Parsons, Sierra Mcdaniel

Geography

Drought is a growing threat to hydrological, ecological, agricultural, and socio-cultural systems of the tropics, especially tropical islands of the Pacific where severe droughts can compromise food and water security. Overcoming barriers to knowledge sharing between land managers and researchers is a critical cross-sector strategy for engaging and mitigating or adapting to drought. Here we describe the establishment and functioning of the Pacific Drought Knowledge Exchange (PDKE), which provides users with easier access to: (1) sector- and geography-specific climate information; (2) better and more comprehensive information; (3) improved technical assistance; and (4) a more collaborative information-transfer environment through participation in …

Incorporating Complex Sampling Weights In Multilevel Analyses Of Education Data, Ting Shen, Spyros Konstantopoulos

Psychological Science Faculty Research & Creative Works

Large-scale assessment survey (LSAS) data are collected via complex sampling designs with special features (e.g., clustering and unequal probability of selection). Multilevel models have been utilized to account for clustering effects whereas the probability weighting approach (PWA) has been used to deal with design informativeness derived from the unequal probability selection. However, the difficulty of applying PWA in multilevel models (MLM) has been generally underestimated and practical guidance is scarce. This study utilizes an empirical as well as a Monte Carlo simulation investigation to examine the performance of the multilevel pseudo maximum likelihood (MPML) estimation based on information derived from …

Journey With Ting Peng Liang In Pacific Asia Information Systems Field, J. Lee, J. Jiang, P. Chau, A. Kankanhalli, M. Nelson, W. Huang, K. Wei, C. Sia, D. Vogel, M. Myers, G. Gable, N. Shen, C. Wei, S. Hung, Keng Siau, D. Liang

Research Collection School Of Computing and Information Systems

Our respectful old friend Professor Ting-Peng Liang (in short, TP) whom we loved suddenly passed away on May 20, 2021. But we cannot forget his smile and passion, and his inerasable footprints in PACIS, PAJAIS, and AIS Community. He was the founder of PACIS, founding editor-in-chief of PAJAIS, and past president of AIS to list just a few. He was the pioneer who received the first AIS Fellow and the first LEO Award from Asia Pacific. That is why the leaders of the information systems field organized the first ever special tribute session in PACIS 2021 in memory of TP

Accessibility In Software Practice: A Practitioner's Perspective, Tingting Bi, Xin Xia, David Lo, John C. Grundy, Thomas Zimmermann, Denae Ford

Research Collection School Of Computing and Information Systems

Being able to access software in daily life is vital for everyone, and thus accessibility is a fundamental challenge for software development. However, given the number of accessibility issues reported by many users, e.g., in app reviews, it is not clear if accessibility is widely integrated into current software projects and how software projects address accessibility issues. In this article, we report a study of the critical challenges and benefits of incorporating accessibility into software development and design. We applied a mixed qualitative and quantitative approach for gathering data from 15 interviews and 365 survey respondents from 26 countries across …

Codematcher: Searching Code Based On Sequential Semantics Of Important Query Words, Chao Liu, Xin Xia, David Lo, Zhiwei Liu, Ahmed E. Hassan, Shanping Li

Research Collection School Of Computing and Information Systems

To accelerate software development, developers frequently search and reuse existing code snippets from a large-scale codebase, e.g., GitHub. Over the years, researchers proposed many information retrieval (IR)-based models for code search, but they fail to connect the semantic gap between query and code. An early successful deep learning (DL)-based model DeepCS solved this issue by learning the relationship between pairs of code methods and corresponding natural language descriptions. Two major advantages of DeepCS are the capability of understanding irrelevant/noisy keywords and capturing sequential relationships between words in query and code. In this article, we proposed an IR-based model CodeMatcher that …

Why Do Smart Contracts Self-Destruct? Investigating The Selfdestruct Function On Ethereum, Jiachi Chen, Xin Xia, David Lo, John C. Grundy

Research Collection School Of Computing and Information Systems

The selfdestruct function is provided by Ethereum smart contracts to destroy a contract on the blockchain system. However, it is a double-edged sword for developers. On the one hand, using the selfdestruct function enables developers to remove smart contracts (SCs) from Ethereum and transfers Ethers when emergency situations happen, e.g., being attacked. On the other hand, this function can increase the complexity for the development and open an attack vector for attackers. To better understand the reasons why SC developers include or exclude the selfdestruct function in their contracts, we conducted an online survey to collect feedback from them and …

Toward Video-Conferencing Tools For Hands-On Activities In Online Teaching, Audrey Labrie, Terrance Mok, Anthony Tang, Michelle Lui, Lora Oehlberg, Lev Poretski

Research Collection School Of Computing and Information Systems

Many instructors in computing and HCI disciplines use hands-on activities for teaching and training new skills. Beyond simply teaching hands-on skills like sketching and programming, instructors also use these activities so students can acquire tacit skills. Yet, current video-conferencing technologies may not effectively support hands-on activities in online teaching contexts. To develop an understanding of the inadequacies of current video-conferencing technologies for hands-on activities, we conducted 15 interviews with university-level instructors who had quickly pivoted their use of hands-on activities to an online context during the early part of the COVID-19 pandemic. Based on our analysis, we uncovered four pedagogical …

"More Than Deep Learning": Post-Processing For Api Sequence Recommendation, Chi Chen, Xin Peng, Bihuan Chen, Jun Sun, Zhenchang Xing, Xin Wang, Wenyun Zhao

Research Collection School Of Computing and Information Systems

In the daily development process, developers often need assistance in finding a sequence of APIs to accomplish their development tasks. Existing deep learning models, which have recently been developed for recommending one single API, can be adapted by using encoder-decoder models together with beam search to generate API sequence recommendations. However, the generated API sequence recommendations heavily rely on the probabilities of API suggestions at each decoding step, which do not take into account other domain-specific factors (e.g., whether an API suggestion satisfies the program syntax and how diverse the API sequence recommendations are). Moreover, it is difficult for developers …

Kg4vis: A Knowledge Graph-Based Approach For Visualization Recommendation, Haotian Li, Yong Wang, Songheng Zhang, Yangqiu Song, Huamin. Qu

Research Collection School Of Computing and Information Systems

Visualization recommendation or automatic visualization generation can significantly lower the barriers for general users to rapidly create effective data visualizations, especially for those users without a background in data visualizations. However, existing rule-based approaches require tedious manual specifications of visualization rules by visualization experts. Other machine learning-based approaches often work like black-box and are difficult to understand why a specific visualization is recommended, limiting the wider adoption of these approaches. This paper fills the gap by presenting KG4Vis, a knowledge graph (KG)-based approach for visualization recommendation. It does not require manual specifications of visualization rules and can also guarantee good …

M2lens: Visualizing And Explaining Multimodal Models For Sentiment Analysis, Xingbo Wang, Jianben He, Zhihua Jin, Muqiao Yang, Yong Wang, Huamin Qu

Research Collection School Of Computing and Information Systems

Multimodal sentiment analysis aims to recognize people's attitudes from multiple communication channels such as verbal content (i.e., text), voice, and facial expressions. It has become a vibrant and important research topic in natural language processing. Much research focuses on modeling the complex intra- and inter-modal interactions between different communication channels. However, current multimodal models with strong performance are often deep-learning-based techniques and work like black boxes. It is not clear how models utilize multimodal information for sentiment predictions. Despite recent advances in techniques for enhancing the explainability of machine learning models, they often target unimodal scenarios (e.g., images, sentences), and …

Do Sequels Outperform Or Disappoint? Insights From An Analysis Of Amazon Echo Consumer Reviews, Kyong Jin Shim, Siaw Ling Lo, Su Yee Liew

Research Collection School Of Computing and Information Systems

Rapid technological advances in recent years drastically transformed our world. Amidst modern technological inventions such as smart phones, smart watches and smart home devices, consumers of electronic digital devices experience greatly improved automation, productivity, and efficiency in conducting routine daily tasks, information searching, shopping as well as finding entertainment. In the last few years, the global smart speaker market has undergone significant growth. As technology continues to advance and smart speakers are equipped with innovative features, the adoption of smart speakers will increase and so will consumer expectations. This research paper presents an aspect-specific sentiment analysis of consumer reviews of …

Defining Smart Contract Defects On Ethereum, Jiachi Chen, Xin Xia, David Lo, John Grundy, Xiapu Luo, Ting Chen

Research Collection School Of Computing and Information Systems

Smart contracts are programs running on a blockchain. They are immutable to change, and hence can not be patched for bugs once deployed. Thus it is critical to ensure they are bug-free and well-designed before deployment. A Contract defect is an error, flaw or fault in a smart contract that causes it to produce an incorrect or unexpected result, or to behave in unintended ways. The detection of contract defects is a method to avoid potential bugs and improve the design of existing code. Since smart contracts contain numerous distinctive features, such as the gas system. decentralized, it is important …

On Discovering Motifs And Frequent Patterns In Spatial Trajectories With Discrete Fréchet Distance, Bo Tang, Man Lung Yiu, Kyriakos Mouratidis, Jiahao Zhang, Kai Wang

Research Collection School Of Computing and Information Systems

The discrete Fréchet distance (DFD) captures perceptual and geographical similarity between two trajectories. It has been successfully adopted in a multitude of applications, such as signature and handwriting recognition, computer graphics, as well as geographic applications. Spatial applications, e.g., sports analysis, traffic analysis, etc. require discovering similar subtrajectories within a single trajectory or across multiple trajectories. In this paper, we adopt DFD as the similarity measure, and study two representative trajectory analysis problems, namely, motif discovery and frequent pattern discovery. Due to the time complexity of DFD, these tasks are computationally challenging. We address that challenge with a suite of …

Towards An Instant Structure-Property Prediction Quality Control Tool For Additive Manufactured Steel Using A Crystal Plasticity Trained Deep Learning Surrogate, Yuhui Tu, Zhongzhou Liu, Luiz Carneiro, Caitriona M. Ryan, Andrew C. Parnell, Sean B. Leen

Research Collection School Of Computing and Information Systems

The ability to conduct in-situ real-time process-structure-property checks has the potential to overcome process and material uncertainties, which are key obstacles to improved uptake of metal powder bed fusion in industry. Efforts are underway for live process monitoring such as thermal and image-based data gathering for every layer printed. Current crystal plasticity finite element (CPFE) modelling is capable of predicting the associated strength based on a microstructural image and material data but is computationally expensive. This work utilizes a large database of input–output samples from CPFE modelling to develop a trained deep neural network (DNN) model which instantly estimates the …

Learning From Web Recipe-Image Pairs For Food Recognition: Problem, Baselines And Performance, Bin Zhu, Chong-Wah Ngo, Wing-Kwong Chan

Research Collection School Of Computing and Information Systems

Cross-modal recipe retrieval has recently been explored for food recognition and understanding. Text-rich recipe provides not only visual content information (e.g., ingredients, dish presentation) but also procedure of food preparation (cutting and cooking styles). The paired data is leveraged to train deep models to retrieve recipes for food images. Most recipes on the Web include sample pictures as the references. The paired multimedia data is not noise-free, due to errors such as pairing of images containing partially prepared dishes with recipes. The content of recipes and food images are not always consistent due to free-style writing and preparation of food …

Lightweight And Expressive Fine-Grained Access Control For Healthcare Internet-Of-Things, Shengmin Xu, Yingjiu Li, Robert H. Deng, Yinghui Zhang, Xiangyang Luo, Ximeng Liu

Research Collection School Of Computing and Information Systems

Healthcare Internet-of-Things (IoT) is an emerging paradigm that enables embedded devices to monitor patients vital signals and allows these data to be aggregated and outsourced to the cloud. The cloud enables authorized users to store and share data to enjoy on-demand services. Nevertheless, it also causes many security concerns because of the untrusted network environment, dishonest cloud service providers and resource-limited devices. To preserve patients' privacy, existing solutions usually apply cryptographic tools to offer access controls. However, fine-grained access control among authorized users is still a challenge, especially for lightweight and resource-limited end-devices. In this paper, we propose a novel …

Secure Cloud Data Deduplication With Efficient Re-Encryption, Haoran Yuan, Xiaofeng Chen, Jin Li, Tao Jiang, Jianfeng Wang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Data deduplication technique has been widely adopted by commercial cloud storage providers, which is both important and necessary in coping with the explosive growth of data. To further protect the security of users' sensitive data in the outsourced storage mode, many secure data deduplication schemes have been designed and applied in various scenarios. Among these schemes, secure and efficient re-encryption for encrypted data deduplication attracted the attention of many scholars, and many solutions have been designed to support dynamic ownership management. In this paper, we focus on the re-encryption deduplication storage system and show that the recently designed lightweight rekeying-aware …

A Blockchain-Based Self-Tallying Voting Protocol In Decentralized Iot, Yannan Li, Willy Susilo, Guomin Yang, Yong Yu, Dongxi Liu, Xiaojiang Du, Mohsen Guizani

Research Collection School Of Computing and Information Systems

The Internet of Things (IoT) is experiencing explosive growth and has gained extensive attention from academia and industry in recent years. However, most of the existing IoT infrastructures are centralized, which may cause the issues of unscalability and single-point-of-failure. Consequently, decentralized IoT has been proposed by taking advantage of the emerging technology called blockchain. Voting systems are widely adopted in IoT, for example a leader election in wireless sensor networks. Self-tallying voting systems are alternatives to unsuitable, traditional centralized voting systems in decentralized IoT. Unfortunately, self-tallying voting systems inherently suffer from fairness issues, such as adaptive and abortive issues caused …

Monetization For Content Generation And User Engagement On Social Media Platforms: Evidence From Paid Q&A, Jonathan Hua Ye, Cecil Eng Huang Chua

Business and Information Technology Faculty Research & Creative Works

Social media platforms want to increase their valuation in terms of total content quantity and user engagement. Monetization is often used to induce user content generation. However, research documents that while monetization increases the quantity of specific kinds of content, it does not necessarily increase the total content quantity or user engagement (i.e., platform value). Furthermore, the impact of monetization may depend on the social status of content creators. This article investigates paid question and answer (paid Q&A). Based on expectancy theory and relevant research, this article hypothesizes the effects of introducing paid Q&A on both total content quantity and …

Information Systems Analysis And Design: Past Revolutions, Present Challenges, And Future Research Directions, Keng Siau, Carson Woo, Veda C. Storey, Roger H.L. Chiang, Cecil Eng Huang Chua, Jon W. Beard

Business and Information Technology Faculty Research & Creative Works

Systems Analysis and Design (SAND) is Undoubtedly a Pillar in the Field of Information Systems (IS). Some Researchers Have Even Claimed that SAND is the Field that Defines the Information Systems Discipline and is the Core of Information Systems. the Past Decades Have Seen the Development of Structured SAND Methodologies and Object-Oriented Methodologies. in the Early 1990s, Key Players in the Field Collaborated to Develop the Unified Modeling Language and the Unified Process. Agile Approaches Followed, as Did Other Dynamic Methods. These Approaches Remain Heavily Employed in the Development of Contemporary Information Systems. at the Same Time, New Approaches Such …

Assessment Of Scientific Payload Carrying Spirulina Onboard Blue Origin’S New Shepard Vehicle, Pedro J. Llanos, Morgan Shilling, Kristina Andrijauskaite, Kody Kidder, Vijay V. Duraisamy

Publications

The research team at ERAU and UTHSCSA analyzed the effects of suborbital flight stressors and various light conditions (red, white, no light) on the Arthrospira platensis (Spirulina), onboard Blue Origin’s New Shepard vehicle. Commercially available cyanobacterium species were cultivated and closely monitored in mother colonies several months before the suborbital flight mission. The aim of this study was to estimate the biomass production and growth as a potential dietary alternative for prospective human spaceflight's life support system. Spirulina samples were flown in a NanoLab with adjacent avionics supporting the light conditions and sensors to monitor the temperature, relative humidity, and …

A Drone-Based Application For Scouting Halyomorpha Halys Bugs In Orchards With Multifunctional Nets, Francesco Betti Sorbelli, Federico Coro, Sajal K. Das, Emanuele Di Bella, Lara Maistrello, Lorenzo Palazzetti, Cristina M. Pinotti

Computer Science Faculty Research & Creative Works

In this work, we consider the problem of using a drone to collect information within orchards in order to scout insect pests, i.e., the stink bug Halyomorpha halys. An orchard can be modeled as an aisle-graph, which is a regular and constrained data structure formed by consecutive aisles where trees are arranged in a straight line. For monitoring the presence of bugs, a drone flies close to the trees and takes videos and/or pictures that will be analyzed offline. As the drone's energy is limited, only a subset of locations in the orchard can be visited with a fully charged …

Scale Formation, Properties And De-Scaling In Steelmaking, Richard Osei

Doctoral Dissertations

During continuous castings, reheating, and hot rolling, slab surfaces are exposed to atmospheres containing oxidizing gases which results in scale formation. Inefficient removal of the formed scale during reheating affects product surface quality. The effect of steel composition and operating parameters on scale formation and scale removal efficiencies were investigated. Experimental investigations were carried out using a thermogravimetric (TGA) apparatus designed to replicate the combustion gas atmosphere and temperature in actual industrial slab reheat furnaces. Report on oxidation kinetics, scale structure and properties, and descaling were conducted on laboratory cast and industrial samples. Different characterization techniques were used to analyze …

Pet Imaging Reveals Reduced Synaptic Density In People With Well-Controlled Hiv Infection, Julian Joseph Weiss

Yale Medicine Thesis Digital Library

Background: Synaptic injury is a pathological hallmark of neurological impairment in people living with HIV (PLWH), a common complication despite viral suppression with antiretroviral therapy (ART). However, there are no biomarkers sensitive to neurocognitive impairment in PLWH. Measurement of synaptic density in living humans may allow better understanding of HIV neuropathogenesis and provide a dynamic biomarker for therapeutic studies. We applied novel synaptic vesical protein 2A (SV2A) positron emission tomographic (PET) imaging to investigate synaptic density in the frontostriatalthalamic region in PLWH and HIV-uninfected (HIV-) participants.

Methods: In this cross-sectional pilot study,13 older male PLWH on ART underwent neurocognitive assessments, …

Graph Neural Networks For Improved Interpretability And Efficiency, Patrick Pho

Electronic Theses and Dissertations, 2020-2023

Attributed graph is a powerful tool to model real-life systems which exist in many domains such as social science, biology, e-commerce, etc. The behaviors of those systems are mostly defined by or dependent on their corresponding network structures. Graph analysis has become an important line of research due to the rapid integration of such systems into every aspect of human life and the profound impact they have on human behaviors. Graph structured data contains a rich amount of information from the network connectivity and the supplementary input features of nodes. Machine learning algorithms or traditional network science tools have limitation …

Artificially Intelligent Boards And The Future Of Delaware Corporate Law, Christopher Bruner

Scholarly Works

The prospects for Artificial Intelligence (AI) to impact the development of Delaware corporate law are at once over- and under-stated. As a general matter, claims to the effect that AI systems might ultimately displace human directors not only exaggerate the foreseeable technological potential of these systems, but also tend to ignore doctrinal and institutional impediments intrinsic to Delaware's competitive model – notably, heavy reliance on nuanced and context-specific applications of the fiduciary duty of loyalty by a true court of equity. At the same time, however, there are specific applications of AI systems that might not merely be accommodated by …