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Articles 62851 - 62880 of 294419

Full-Text Articles in Physical Sciences and Mathematics

Aligning Recovery Objectives With Organizational Capabilities, Jude C. Ejiobi Mar 2022

Aligning Recovery Objectives With Organizational Capabilities, Jude C. Ejiobi

Masters Theses & Doctoral Dissertations

To reduce or eliminate the impact of a cyber-attack on an organization, preparations to recover a failed system and/or data are usually made in anticipation of such an attack. To avoid a false sense of security, these preparations should, as closely as possible, reflect the organization’s capabilities, in order to inform future improvement and avoid unattainable goals. There is an absence of a strong basis for the selection of the metrics that are used to measure preparation. Informal and unreliable processes are widely used, and they often result in metrics that conflict with the organization’s capabilities and interests. The goal …

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Nebraska Statewide Groundwater-Level Monitoring Report 2021, Aaron R. Young, Mark E. Burbach, Leslie M. Howard, Sue Olafsen Lackey, Robert Matthew Joeckel Mar 2022

Nebraska Statewide Groundwater-Level Monitoring Report 2021, Aaron R. Young, Mark E. Burbach, Leslie M. Howard, Sue Olafsen Lackey, Robert Matthew Joeckel

Conservation and Survey Division: Faculty and Staff Publications

This report is a synthesis of groundwater-level monitoring programs in Nebraska. It is a continuation of the series of annual reports and maps produced by the Conservation and Survey Division (CSD) of the University of Nebraska in cooperation with the U.S. Geological Survey (USGS) since the 1950s. Groundwater-level monitoring began in Nebraska in 1930 in an effort to survey the state’s groundwater resources and to observe changes in its availability on a continuing basis. The CSD and USGS cooperatively developed, maintained, and operated an observation-well network throughout the state. These two agencies were responsible for collecting and archiving this information, …

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Ecosystem Duties, Green Infrastructure, And Environmental Injustice In Los Angeles, Sayd Randle Mar 2022

Ecosystem Duties, Green Infrastructure, And Environmental Injustice In Los Angeles, Sayd Randle

Research Collection College of Integrative Studies

In Los Angeles, water managers and environmentalist NGOs champion green infrastructure retrofits, installations intended to maximize the water-absorbing capacity of the urban landscape. In such arrangements, the work of water management is necessarily spread among a more-than-human community, including (but certainly not limited to) humans, plants, soils, and gravels. This article analyzes the human labor within these collaborations, tracking when and how this work gets enrolled in networks of water management and circuits of value. I develop the term ecosystem duties to characterize these exertions and as a useful analytic for assessing emergent dynamics of environmental justice.

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Transition Metal‐Catalyzed And Mao‐Assisted Olefin Polymerization. Cyclic Isomers Of Sinn’S Dimer Are Excellent Ligands In Iron Complexes And Great Methylating Reagents, Kaidi Yang, Rainer Glaser Mar 2022

Transition Metal‐Catalyzed And Mao‐Assisted Olefin Polymerization. Cyclic Isomers Of Sinn’S Dimer Are Excellent Ligands In Iron Complexes And Great Methylating Reagents, Kaidi Yang, Rainer Glaser

Chemistry Faculty Research & Creative Works

Methylaluminoxane (MAO) is the most commonly used co‐catalyst for transition metalcatalyzed olefin polymerization, but the structures of MAO species and their catalytic functions remain topics of intensive study. We are interested in MAO‐assisted polymerization with catalysts L(R2)FeCl2 (L = tridentate pyridine‐2,6‐diyldimethanimine; imine‐R = Me, Ph). It is our hypothesis that the MAO species is not merely enabling Fe−Me bond formation but functions as an integral part of the active catalyst, a MAO adduct of the Fe‐precatalyst [L(R2)FeCl]+. In this paper, we explored the possible structures of acyclic and cyclic MAO species and their …

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Using Modified Technology Acceptance Model To Evaluate The Adoption Of A Proposed Iot-Based Indoor Disaster Management Software Tool By Rescue Workers, Preetinder Singh Brar, Babar Shah, Jaiteg Singh, Farman Ali, Daehan Kwak Mar 2022

Using Modified Technology Acceptance Model To Evaluate The Adoption Of A Proposed Iot-Based Indoor Disaster Management Software Tool By Rescue Workers, Preetinder Singh Brar, Babar Shah, Jaiteg Singh, Farman Ali, Daehan Kwak

All Works

Advancements in IoT technology have been instrumental in the design and implementation of various ubiquitous services. One such design activity was carried out by the authors of this paper, who proposed a novel cloud-centric IoT-based disaster management framework and developed a multimedia-based prototype that employed real-time geographical maps. The multimediabased system can provide vital information on maps that can improve the planning and execution of evacuation tasks. This study was intended to explore the acceptance of the proposed technology by the specific set of users that could potentially lead to its adoption by rescue agencies for carrying out indoor rescue …

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Analysing Tweets On Covid-19 Vaccine : A Text Mining Approach, Swetha Gottipati, Debashis Guha Mar 2022

Analysing Tweets On Covid-19 Vaccine : A Text Mining Approach, Swetha Gottipati, Debashis Guha

Research Collection School Of Computing and Information Systems

The COVID-19 pandemic has caused large scale health, economic, and social crisis. Scientists throughout the globe have been working on producing effective vaccines to combat this pandemic. COVID-19 vaccine release started in 2020, and low take-up rates among the public have been observed initially. There has been a soar in social media data on vaccines. This paper presents a comprehensive analysis of COVID-19 vaccine-related tweets. Sentiments shared by people through tweets and common topics have been extracted using classification and sentiment analysis. Our results showed a higher negative sentiment when the pandemic was declared, and it gradually changed to positive …

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Gender Influence On Communication Initiated Within Student Teams, Rita Garcia, Chieh-Ju Trinity Liao, Ariane Pearce, Christoph Treude Mar 2022

Gender Influence On Communication Initiated Within Student Teams, Rita Garcia, Chieh-Ju Trinity Liao, Ariane Pearce, Christoph Treude

Research Collection School Of Computing and Information Systems

Collaboration is important during software development, but related work has found gender differences can influence the collaboration process, creating inequality in the team’s dynamics. In this paper, we present a gender analysis study that involved 39 students, examining their teams’ online collaborations while contributing to a large open-source software project. Eight teams of 4-6 Software Engineering (SE) students communicated over an online messaging platform, Slack, to complete an eight-week project. The goal of this study is to identify gender differences emerging from team collaboration. A mixed-methods approach was used to collect students’ teamwork experiences and analyse their collaboration. Our research …

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Estimating Financial Information Asymmetry In Real Estate Transactions In China: An Application Of Two-Tier Frontier Model, Ganlin Pu, Ying Zhang, Li-Chen Chou Mar 2022

Estimating Financial Information Asymmetry In Real Estate Transactions In China: An Application Of Two-Tier Frontier Model, Ganlin Pu, Ying Zhang, Li-Chen Chou

Research Collection School Of Computing and Information Systems

This study applies the two-tier stochastic frontier model to estimate the distribution of housing transaction information in Hangzhou, Wenzhou, Ningbo, and Jinhua (four cities in Zhejiang Province, China) during the year 2018, to analyze the difference in the price information acquired by the buyers and sellers in the transaction, and the effect of information asymmetry on the transaction price. The empirical results show that in each city, during the housing transaction process, the supplier has more complete information about house prices than consumers, and can therefore implement price discrimination strategies in setting service prices. Due to the disadvantage in acquired …

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Viral Pneumonia Screening On Chest X-Rays Using Confidence-Aware Anomaly Detection, Jianpeng Zhang, Yutong Xie, Guansong Pang, Zhibin Liao, Johan Verjans, Wenxing Li, Zongji Sun, Jian He, Yi Li, Chunhua Shen, Yong Xia Mar 2022

Viral Pneumonia Screening On Chest X-Rays Using Confidence-Aware Anomaly Detection, Jianpeng Zhang, Yutong Xie, Guansong Pang, Zhibin Liao, Johan Verjans, Wenxing Li, Zongji Sun, Jian He, Yi Li, Chunhua Shen, Yong Xia

Research Collection School Of Computing and Information Systems

Clusters of viral pneumonia occurrences over a short period may be a harbinger of an outbreak or pandemic. Rapid and accurate detection of viral pneumonia using chest X-rays can be of significant value for large-scale screening and epidemic prevention, particularly when other more sophisticated imaging modalities are not readily accessible. However, the emergence of novel mutated viruses causes a substantial dataset shift, which can greatly limit the performance of classification-based approaches. In this paper, we formulate the task of differentiating viral pneumonia from non-viral pneumonia and healthy controls into a one-class classification-based anomaly detection problem. We therefore propose the confidence-aware …

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Coders Assembly: Peer Assisted Learning Model For Freshman Programming Courses, Kyong Jin Shim, Gottipati Swapna, Shankararaman, Venky Mar 2022

Coders Assembly: Peer Assisted Learning Model For Freshman Programming Courses, Kyong Jin Shim, Gottipati Swapna, Shankararaman, Venky

Research Collection School Of Computing and Information Systems

Today, computing graduates see a bright outlook thanks to the high demand for skills driven by the increasing importance of technology as the main driving force behind business transformation. As technology continues to grow exponentially over recent years, computing graduates have some of the highest starting salaries in the market. Even though universities have increased production of computing degree graduates in recent years, it is insufficient to fill the jobs available in the market. Therefore, going forward, the demand is likely to further increase. The continued demand for computing programs in universities has led to an increased intake size, thus …

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Mwptoolkit: An Open-Source Framework For Deep Learning-Based Math Word Problem Solvers, Yihuai Lan, Lei Wang, Qiyuan Zhang, Yunshi Lan, Bing Tian Dai, Yan Wang, Dongxiang Zhang, Ee-Peng Lim Mar 2022

Mwptoolkit: An Open-Source Framework For Deep Learning-Based Math Word Problem Solvers, Yihuai Lan, Lei Wang, Qiyuan Zhang, Yunshi Lan, Bing Tian Dai, Yan Wang, Dongxiang Zhang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

While Math Word Problem (MWP) solving has emerged as a popular field of study and made great progress in recent years, most existing methods are benchmarked solely on one or two datasets and implemented with different configurations. In this paper, we introduce the first open-source library for solving MWPs called MWPToolkit, which provides a unified, comprehensive, and extensible framework for the research purpose. Specifically, we deploy 17 deep learning-based MWP solvers and 6 MWP datasets in our toolkit. These MWP solvers are advanced models for MWP solving, covering the categories of Seq2seq, Seq2Tree, Graph2Tree, and Pre-trained Language Models. And these …

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Efficient Search Of Live-Coding Screencasts From Online Videos, Chengran Yang, Ferdian Thung, David Lo Mar 2022

Efficient Search Of Live-Coding Screencasts From Online Videos, Chengran Yang, Ferdian Thung, David Lo

Research Collection School Of Computing and Information Systems

Programming videos on the Internet are valuable resources for learning programming skills. To find relevant videos, developers typically search online video platforms (e.g., YouTube) with keywords on topics they wish to learn. Developers often look for live-coding screencasts, in which the videos’ authors perform live coding. Yet, not all programming videos are livecoding screencasts. In this work, we develop a tool named PSFinder to identify live-coding screencasts. PSFinder leverages a classifier to identify whether a video frame contains an IDE window. It uses a sampling strategy to pick a number of frames from an input video, runs the classifer on …

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Aspect-Based Api Review Classification: How Far Can Pre-Trained Transformer Model Go?, Chengran Yang, Bowen Xu, Junaed Younus Khan, Gias Uddin, Donggyun Han, Zhou Yang, David Lo Mar 2022

Aspect-Based Api Review Classification: How Far Can Pre-Trained Transformer Model Go?, Chengran Yang, Bowen Xu, Junaed Younus Khan, Gias Uddin, Donggyun Han, Zhou Yang, David Lo

Research Collection School Of Computing and Information Systems

APIs (Application Programming Interfaces) are reusable software libraries and are building blocks for modern rapid software development. Previous research shows that programmers frequently share and search for reviews of APIs on the mainstream software question and answer (Q&A) platforms like Stack Overflow, which motivates researchers to design tasks and approaches related to process API reviews automatically. Among these tasks, classifying API reviews into different aspects (e.g., performance or security), which is called the aspect-based API review classification, is of great importance. The current state-of-the-art (SOTA) solution to this task is based on the traditional machine learning algorithm. Inspired by the …

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Meta-Transfer Learning Through Hard Tasks, Qianru Sun, Yaoyao Liu, Zhaozheng Chen, Chua Tat-Seng, Schiele Bernt Mar 2022

Meta-Transfer Learning Through Hard Tasks, Qianru Sun, Yaoyao Liu, Zhaozheng Chen, Chua Tat-Seng, Schiele Bernt

Research Collection School Of Computing and Information Systems

Meta-learning has been proposed as a framework to address the challenging few-shot learning setting. The key idea is to leverage a large number of similar few-shot tasks in order to learn how to adapt a base-learner to a new task for which only a few labeled samples are available. As deep neural networks (DNNs) tend to overfit using a few samples only, typical meta-learning models use shallow neural networks, thus limiting its effectiveness. In order to achieve top performance, some recent works tried to use the DNNs pre-trained on large-scale datasets but mostly in straight-forward manners, e.g., (1) taking their …

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The Role Of 3d Ct Imaging In The Accurate Diagnosis Of Lung Function In Coronavirus Patients, Ibrahim Shawky Farahat, Ahmed Sharafeldeen, Mohamed Elsharkawy, Ahmed Soliman, Ali Mahmoud, Mohammed Ghazal, Fatma Taher, Maha Bilal, Ahmed Abdel Khalek Abdel Razek, Waleed Aladrousy, Samir Elmougy, Ahmed Elsaid Tolba, Moumen El-Melegy, Ayman El-Baz Mar 2022

The Role Of 3d Ct Imaging In The Accurate Diagnosis Of Lung Function In Coronavirus Patients, Ibrahim Shawky Farahat, Ahmed Sharafeldeen, Mohamed Elsharkawy, Ahmed Soliman, Ali Mahmoud, Mohammed Ghazal, Fatma Taher, Maha Bilal, Ahmed Abdel Khalek Abdel Razek, Waleed Aladrousy, Samir Elmougy, Ahmed Elsaid Tolba, Moumen El-Melegy, Ayman El-Baz

All Works

Early grading of coronavirus disease 2019 (COVID-19), as well as ventilator support machines, are prime ways to help the world fight this virus and reduce the mortality rate. To reduce the burden on physicians, we developed an automatic Computer-Aided Diagnostic (CAD) system to grade COVID-19 from Computed Tomography (CT) images. This system segments the lung region from chest CT scans using an unsupervised approach based on an appearance model, followed by 3D rotation invariant Markov–Gibbs Random Field (MGRF)-based morphological constraints. This system analyzes the segmented lung and generates precise, analytical imaging markers by estimating the MGRF-based analytical potentials. Three Gibbs …

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Monitoring Extinction Risk And Threats Of The World's Fishes Based On The Sampled Red List Index, Rafael Miranda, Imanol Miqueleiz, William Darwall, Catherine Sayer, Nicholas K. Dulvy, Kent E. Carpenter, Beth Polidoro, Nadia Dewhurst-Richman, Caroline Pollock, Craig Hilton-Taylor, Robin Freeman, Ben Collen, Monika Böhm Mar 2022

Monitoring Extinction Risk And Threats Of The World's Fishes Based On The Sampled Red List Index, Rafael Miranda, Imanol Miqueleiz, William Darwall, Catherine Sayer, Nicholas K. Dulvy, Kent E. Carpenter, Beth Polidoro, Nadia Dewhurst-Richman, Caroline Pollock, Craig Hilton-Taylor, Robin Freeman, Ben Collen, Monika Böhm

Biological Sciences Faculty Publications

Global biodiversitytargets require us to identify species at risk of extinction and quantify status and trends of biodiversity. The Red List Index (RLI) tracks trends in the conservation status of entire species groups over time by monitoring changes in categories assigned to species. Here, we calculate this index for the world’s fishes in 2010, using a sampled approach to the RLI based on a randomly selected sample of 1,500 species, and also present RLI splits for freshwater and marine systems separately. We further compare specific traits of a worldwide fish list to our sample to assess its representativeness. Overall, 15.1% …

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Habitat Restoration Restores Underwater Soundscapes And Larval Recruitment, Jack Butler, Emily R. Anderson, Mark J. Butler Mar 2022

Habitat Restoration Restores Underwater Soundscapes And Larval Recruitment, Jack Butler, Emily R. Anderson, Mark J. Butler

Biological Sciences Faculty Publications

Habitat degradation alters many ecosystem processes, and the potential for the reestablishment of ecosystem function through restoration is an area of active research. Among marine systems, coastal habitats are particularly vulnerable to anthropogenic degradation and, in response, are the focus of marine ecological restoration. One of the crucial functions of structurally complex coastal habitats (e.g., saltmarshes, seagrass meadows, kelp forests, coral reefs) are as nurseries to coastal and offshore species, many of whose larvae utilize sound to locate suitable nursery habitat. However, the effect of habitat degradation and subsequent restoration on underwater soundscapes and their function as navigational cues for …

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Thermo-Fluidic Transport Process In A Novel M-Shaped Cavity Packed With Non-Darcian Porous Medium And Hybrid Nanofluid: Application Of Artificial Neural Network (Ann), Dipak Kumar Mandal, Nirmalendu Biswas, Nirmal K. Manna, Dilip Kumar Gayen, Rama S. R. Gorla, Ali J. Chamkha Mar 2022

Thermo-Fluidic Transport Process In A Novel M-Shaped Cavity Packed With Non-Darcian Porous Medium And Hybrid Nanofluid: Application Of Artificial Neural Network (Ann), Dipak Kumar Mandal, Nirmalendu Biswas, Nirmal K. Manna, Dilip Kumar Gayen, Rama S. R. Gorla, Ali J. Chamkha

Faculty Publications

In this work, an attempt has been made to explore numerically the thermo-fluidic transport process in a novel M-shaped enclosure filled with permeable material along with Al2O3-Cu hybrid nanoparticles suspended in water under the influence of a horizontal magnetizing field. To exercise the influence of geometric parameters, a classical trapezoidal cavity is modified with an inverted triangle at the top to construct an M-shaped cavity. The cavity is heated isothermally from the bottom and cooled from the top, whereas the inclined sidewalls are insulated. The role of geometric parameters on the thermal performance is scrutinized thoroughly …

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Robots Need The Ability To Navigate Abusive Interactions, Hideki Garcia Goo, Katie Winkle, Tom Williams, Megan K. Strait Mar 2022

Robots Need The Ability To Navigate Abusive Interactions, Hideki Garcia Goo, Katie Winkle, Tom Williams, Megan K. Strait

Computer Science Faculty Publications

Researchers are seeing more and more cases of abusive disinhibition towards robots in public realms. Because robots embody gendered identities, poor navigation of antisocial dynamics may reinforce or exacerbate gender-based violence. It is essential that robots deployed in social settings be able to recognize and respond to abuse in a way that minimises ethical risk. Enabling this capability requires designers to first understand the risk posed by abuse of robots, and hence how humans perceive robot-directed abuse. To that end, we experimentally investigated reactions to a physically abusive interaction between a human perpetrator and a victimized agent. Given extensions of …

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Counterfactual Analysis Of Differential Comorbidity Risk Factors In Alzheimer’S Disease And Related Dementias, Paul E Schulz, Xiaoqian Jiang Mar 2022

Counterfactual Analysis Of Differential Comorbidity Risk Factors In Alzheimer’S Disease And Related Dementias, Paul E Schulz, Xiaoqian Jiang

Faculty, Staff and Student Publications

Alzheimer’s disease and related dementias (ADRD) is a multifactorial disease that involves several different etiologic mechanisms with various comorbidities. There is also significant heterogeneity in the prevalence of ADRD across diverse demographics groups. Association studies on such heterogeneous comorbidity risk factors are limited in their ability to determine causation. We aim to compare counterfactual treatment effects of various comorbidity in ADRD in different racial groups (African Americans and Caucasians). We used 138,026 ADRD and 1:1 matched older adults without ADRD from nationwide electronic health records, which extensively cover a large population’s long medical history in breadth. We matched African Americans …

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Bandgap Tuning Of Mose2 And Wse2 Monolayers Through Alloying And Substitution: An Ab Initio Study, Shahida Maqsood Mar 2022

Bandgap Tuning Of Mose2 And Wse2 Monolayers Through Alloying And Substitution: An Ab Initio Study, Shahida Maqsood

Theses

2D materials attracted considerable interest in the research community following the first report in 2004 on the preparation of graphene by simple micromechanical exfoliation of highly oriented pyrolytic graphite. For example, single-layer Molybdenum Di selenide (MoSe2) and Tungsten Di selenide (WSe2) transistors with on/off ratios of 108 and ultra-low standby power dissipation were demonstrated. Graphene electrodes have been used to develop fully transparent resistive memories to suppress unwanted surface effects that occur in oxide memory devices. Photodetectors based on MoSe2 with few layers have shown excellent photodetection properties. Phototransistors based on WSe2 monolayers exhibit …

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Application Of Natural Radioactivity For Hydrogeological And Environmental Assessment Of Groundwater In Ras Alkhaimah, Uae, Mohammed Nasser Abdullah Al-Saqri Mar 2022

Application Of Natural Radioactivity For Hydrogeological And Environmental Assessment Of Groundwater In Ras Alkhaimah, Uae, Mohammed Nasser Abdullah Al-Saqri

Theses

Groundwater includes a certain concentration of natural radioactive isotopes of uranium (U) and its decay products (daughters) like radon (Rn). Defining the concentration levels, spatial distribution, and possible environmental impact of these isotopes in groundwater is vital for sustainable groundwater resources in the United Arab Emirates (UAE). This dissertation focuses on documenting the distribution and determining the probable environmental impact and sources of Uranium-235 (235U), Uranium-238 (238U), and Radon-222 (222Rn) in groundwater in the Northern part of the UAE and specifically in the Wadi Al Bih aquifer in Ras Al Khaimah Emirate. The sampled …

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Finitely Generated Modules Over A Principal Ideal Domain, Mariam Mutawa Meshaab Shemal Al-Dhaheri Mar 2022

Finitely Generated Modules Over A Principal Ideal Domain, Mariam Mutawa Meshaab Shemal Al-Dhaheri

Theses

This thesis covers the main theory of modules: modules, submodules, cosets, quotient modules, homomorphisms, ideals, direct sums, and some related topics. Using these notions, a theorem on the structure of finitely generated modules over domains of principal ideals is proved. As an application of this theorem, the theory of the structure of normal forms of matrices over various fields is presented.

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The Correlation Between The Effects Of Strain And Stochiometric Coefficient On The Magnetic Properties Of Srsno₃ And Sr₃Sno, Amal Sameh Kashcoul Mar 2022

The Correlation Between The Effects Of Strain And Stochiometric Coefficient On The Magnetic Properties Of Srsno₃ And Sr₃Sno, Amal Sameh Kashcoul

Theses

Perovskites (ABX3) are one of the most prominent families of crystalline alloys have received excellent research attention globally because of their diverse multi-functionalities and the interesting physics underpinning them. On the other hand, antiperovskites (X3BA) are electronically inverted perovskite derivates, yet they are not an insignificant class of functional materials. Antiperovskites, inheriting the flexible structural characteristics of perovskites and rich in cations at X sites, display unusual chemical and physical properties. The SrSnO3 is a distinctive perovskite oxide in that it possesses a higher electron conductivity despite its sizeable optical band gap. This dissertation has …

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On The Influence Of Biases In Bug Localization: Evaluation And Benchmark, Ratnadira Widyasari, Stefanus Agus Haryono, Ferdian Thung, Jieke Shi, Constance Tan, Fiona Wee, Jack Phan, David Lo Mar 2022

On The Influence Of Biases In Bug Localization: Evaluation And Benchmark, Ratnadira Widyasari, Stefanus Agus Haryono, Ferdian Thung, Jieke Shi, Constance Tan, Fiona Wee, Jack Phan, David Lo

Research Collection School Of Computing and Information Systems

Bug localization is the task of identifying parts of thesource code that needs to be changed to resolve a bug report.As this task is difficult, automatic bug localization tools havebeen proposed. The development and evaluation of these toolsrely on the availability of high-quality bug report datasets. In2014, Kochhar et al. identified three biases in datasets used toevaluate bug localization techniques: (1) misclassified bug report,(2) already localized bug report, and (3) incorrect ground truthfile in a bug report. They reported that already localized bugreports statistically significantly and substantially impact buglocalization results, and thus should be removed. However, theirevaluation is still limited, …

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Analyzing Offline Social Engagements: An Empirical Study Of Meetup Events Related To Software Development, Abhishek Sharma, Gede Artha Azriadi Prana, Anamika Sawhney, Nachiappan Nagappan, David Lo Mar 2022

Analyzing Offline Social Engagements: An Empirical Study Of Meetup Events Related To Software Development, Abhishek Sharma, Gede Artha Azriadi Prana, Anamika Sawhney, Nachiappan Nagappan, David Lo

Research Collection School Of Computing and Information Systems

Software developers use a variety of social mediachannels and tools in order to keep themselves up to date,collaborate with other developers, and find projects to contributeto. Meetup is one of such social media used by softwaredevelopers to organize community gatherings. We in this work,investigate the dynamics of Meetup groups and events relatedto software development. Our work is different from previouswork as we focus on the actual event and group data that wascollected using Meetup API.In this work, we performed an empirical study of eventsand groups present on Meetup which are related to softwaredevelopment. First, we identified 6,327 Meetup groups related …

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Can Identifier Splitting Improve Open-Vocabulary Language Model Of Code?, Jieke Shi, Zhou Yang, Junda He, Bowen Xu, David Lo Mar 2022

Can Identifier Splitting Improve Open-Vocabulary Language Model Of Code?, Jieke Shi, Zhou Yang, Junda He, Bowen Xu, David Lo

Research Collection School Of Computing and Information Systems

Statistical language models on source code have successfully assisted software engineering tasks. However, developers can create or pick arbitrary identifiers when writing source code. Freely chosen identifiers lead to the notorious out-of-vocabulary (OOV) problem that negatively affects model performance. Recently, Karampatsis et al. showed that using the Byte Pair Encoding (BPE) algorithm to address the OOV problem can improve the language models’ predictive performance on source code. However, a drawback of BPE is that it cannot split the identifiers in a way that preserves the meaningful semantics. Prior researchers also show that splitting compound identifiers into sub-words that reflect the …

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Sample-Efficient Iterative Lower Bound Optimization Of Deep Reactive Policies For Planning In Continuous Mdps, Siow Meng Low, Akshat Kumar, Scott Sanner Mar 2022

Sample-Efficient Iterative Lower Bound Optimization Of Deep Reactive Policies For Planning In Continuous Mdps, Siow Meng Low, Akshat Kumar, Scott Sanner

Research Collection School Of Computing and Information Systems

Recent advances in deep learning have enabled optimization of deep reactive policies (DRPs) for continuous MDP planning by encoding a parametric policy as a deep neural network and exploiting automatic differentiation in an end-toend model-based gradient descent framework. This approach has proven effective for optimizing DRPs in nonlinear continuous MDPs, but it requires a large number of sampled trajectories to learn effectively and can suffer from high variance in solution quality. In this work, we revisit the overall model-based DRP objective and instead take a minorizationmaximization perspective to iteratively optimize the DRP w.r.t. a locally tight lower-bounded objective. This novel …

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Hermes: Using Commit-Issue Linking To Detect Vulnerability-Fixing Commits, Truong Giang Nguyen, Hong Jin Kang, David Lo, Abhishek Sharma, Andrew E. Santosa, Asankhaya Sharma, Ming Yi Ang Mar 2022

Hermes: Using Commit-Issue Linking To Detect Vulnerability-Fixing Commits, Truong Giang Nguyen, Hong Jin Kang, David Lo, Abhishek Sharma, Andrew E. Santosa, Asankhaya Sharma, Ming Yi Ang

Research Collection School Of Computing and Information Systems

Software projects today rely on many third-party libraries, and therefore, are exposed to vulnerabilities in these libraries. When a library vulnerability is fixed, users are notified and advised to upgrade to a new version of the library. However, not all vulnerabilities are publicly disclosed, and users may not be aware of vulnerabilities that may affect their applications. Due to the above challenges, there is a need for techniques which can identify and alert users to silent fixes in libraries; commits that fix bugs with security implications that are not officially disclosed. We propose a machine learning approach to automatically identify …

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Interpretable Knowledge Tracing: Simple And Efficient Student Modeling With Causal Relations, Sein Minn, Jill-Jênn Vie, Koh Takeuchi, Feida Zhu Mar 2022

Interpretable Knowledge Tracing: Simple And Efficient Student Modeling With Causal Relations, Sein Minn, Jill-Jênn Vie, Koh Takeuchi, Feida Zhu

Research Collection School Of Computing and Information Systems

Intelligent Tutoring Systems have become critically important in future learning environments. Knowledge Tracing (KT) is a crucial part of that system. It is about inferring the skill mastery of students and predicting their performance to adjust the curriculum accordingly. Deep Learning based models like Deep Knowledge Tracing (DKT) and Dynamic Key-Value Memory Network (DKVMN) have shown significant predictive performance compared with traditional models like Bayesian Knowledge Tracing (BKT) and Performance Factors Analysis (PFA). However, it is difficult to extract psychologically meaningful explanations from the tens of thousands of parameters in neural networks, that would relate to cognitive theory. There are …

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