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2023

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Articles 601 - 630 of 14121

Full-Text Articles in Physical Sciences and Mathematics

The Effects Of Aggregation Of Tetrafluoro(Trifluoromethyl-Λ6-Sulfanyl) Ethanes On The Secondary Structure Stabilization Of Melittin: A Molecular Dynamics Simulation Study, Samadrita Biswas Dec 2023

The Effects Of Aggregation Of Tetrafluoro(Trifluoromethyl-Λ6-Sulfanyl) Ethanes On The Secondary Structure Stabilization Of Melittin: A Molecular Dynamics Simulation Study, Samadrita Biswas

Legacy Theses & Dissertations (2009 - 2024)

Introduction of novel tetrafluoro(trifluoromethyl-λ6-sulfanyl) (CF3SF4) functional group has garnered substantial interest because of its increased hydrophobicity. This super fluorinated group attributed to increased lipophilicity, decreased heat of vaporization, and lowered dielectric constants. The highly electronegative nature of this group can profoundly influence the reactivity of compounds containing the CF3SF4 moiety. The hypervalency associated with this new group presents an exciting platform to explore the fundamental understanding of molecular interactions, reactivity patterns, and electronic behaviors. This dissertation investigates the molecular properties and behaviors of tetrafluoro(trifluoromethyl-λ6-sulfanyl) ethanes (CF3SF4-ethanes), with a specific emphasis on 2-tetrafluoro(trifluoromethyl)-λ6-sulfanylethan-1-ol (CF3SF4-ethanol) and 2-tetrafluoro(trifluoromethyl)-λ6-sulfanylethanamine (CF3SF4-ethanamine). Utilizing ab initio calculations …

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An Investigation Into Past And Future Freezing Level Height And Equilibrium Line Altitude In The Tropical Andes Using Cmip6, Shelby Turner Dec 2023

An Investigation Into Past And Future Freezing Level Height And Equilibrium Line Altitude In The Tropical Andes Using Cmip6, Shelby Turner

Legacy Theses & Dissertations (2009 - 2024)

The freezing level height (FLH) in the tropical Andes has increased over the past several decades, as is evident with the receding of alpine glaciers in this region. The accuracy of Global Climate Models (GCMs)—specifically previous generations of the Coupled Model Intercomparison Project (CMIP)—in this region remains an issue, as the complex terrain and climate characteristics are difficult to simulate realistically. The changes seen in these tropical alpine glaciers in the past few decades are a clear indicator of the effects climate change is having in this tropical mountain region, making it important to better understand current and projected future …

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Photosensitized Chemically Amplified Resist (Pscar) For Extreme Ultraviolet Lithography (Euvl), Israt Hossain Dec 2023

Photosensitized Chemically Amplified Resist (Pscar) For Extreme Ultraviolet Lithography (Euvl), Israt Hossain

Legacy Theses & Dissertations (2009 - 2024)

As Deep Ultraviolet (DUV) Photolithography has hit the limit in further shrinking semiconductor devices' critical dimension (CD) down to below 10 nm, using Extreme Ultraviolet (EUV) 13.5 nm wavelength is under intense development. EUV has higher resolution (R) as a consequence of the shorter wavelength, but EUV sources have much lower light intensity than DUV light sources, leading to sensitivity challenges. While light source intensity and photoresist sensitivity (S) have a complementary relationship, and high intensity EUV light source development only progresses slowly, this paper discusses other novel approaches to improve photoresist sensitivity with low intensity EUV light. Photosensitization chemistry …

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Characterizing And Understanding Orographic Precipitation Over The Mountains Of Extratropical South America, Yazmina Rojas Beltran Dec 2023

Characterizing And Understanding Orographic Precipitation Over The Mountains Of Extratropical South America, Yazmina Rojas Beltran

Legacy Theses & Dissertations (2009 - 2024)

Extratropical South-America (30-40°S) varies significantly in topography, including a coastal mountain range with elevation from 700-1300 m, a central valley, and the Andes, with elevation from 1000-2500 m on the western side of the continent. The topography of the area can disrupt frontal systems approaching from the Pacific Ocean, leading to enhanced orographic precipitation over the windward slope of the Andes and a sharp rain shadow, with less precipitation in the leeside. These phenomena are also observed over the coastal mountains of south-central Chile. The main goals of this study are to characterize and understand orographic precipitation and rain shadow …

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Planar, Twisted, And Macrocyclic Polyarenes: Structures, Reduction Limits, And Reactivity, Matthew John Pennachio Dec 2023

Planar, Twisted, And Macrocyclic Polyarenes: Structures, Reduction Limits, And Reactivity, Matthew John Pennachio

Legacy Theses & Dissertations (2009 - 2024)

Molecular nanocarbons, which can be considered as fragments of fullerenes, carbon nanotubes, or graphene have invigorated the rapid development of carbon chemistry at the nanoscale in recent decades. Not only do molecular nanocarbons possess extraordinary chemical and physical properties, but they also exhibit such unique features as controllable and scalable molecular compositions, atomically uniform precision, and good stability. The advance of nanocarbon chemistry give rise to unique applications such as electron transfer, semiconductors, superconductors, and lithium-ion batteries. However, an in-depth understanding of controlled doping, charge transfer effects, and structure–property correlations has been limited in nanocarbon chemistry due to the lack …

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Leveraging Generative Agents: Autonomous Ai With Simulated Personas For Interactive Simulacra And Collaborative Research, James Hutson, Jay Ratican Dec 2023

Leveraging Generative Agents: Autonomous Ai With Simulated Personas For Interactive Simulacra And Collaborative Research, James Hutson, Jay Ratican

Faculty Scholarship

The advent of large language models (LLMs) and AI learning have fundamentally reshaped the research landscape, paving the way for novel problem-solving approaches. This paper introduces a unique framework that leverages the capabilities of autonomous AI agents with simulated personas to drive collaborative research in groundbreaking ways. Inspired by a recent study of autonomous agents mirroring human behavior, this concept encourages the use of a cadre of AI agents, each possessing specialized expertise for collective endeavors. By replicating human diversity in teamwork, this approach targets complex and hitherto unsolvable issues. The key to this strategy is persona and emotional simulation, …

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Draft Final Butte Treatment Lagoons (Btl) Groundwater Treatment System Routine Operations, Maintenance, And Monitoring (Om&M) Plan, Pioneer Technical Services, Inc. Dec 2023

Draft Final Butte Treatment Lagoons (Btl) Groundwater Treatment System Routine Operations, Maintenance, And Monitoring (Om&M) Plan, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Enhanced Content-Based Fake News Detection Methods With Context-Labeled News Sources, Duncan Arnfield Dec 2023

Enhanced Content-Based Fake News Detection Methods With Context-Labeled News Sources, Duncan Arnfield

Electronic Theses and Dissertations

This work examined the relative effectiveness of multilayer perceptron, random forest, and multinomial naïve Bayes classifiers, trained using bag of words and term frequency-inverse dense frequency transformations of documents in the Fake News Corpus and Fake and Real News Dataset. The goal of this work was to help meet the formidable challenges posed by proliferation of fake news to society, including the erosion of public trust, disruption of social harmony, and endangerment of lives. This training included the use of context-categorized fake news in an effort to enhance the tools’ effectiveness. It was found that term frequency-inverse dense frequency provided …

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Implementation Of Hierarchical And K-Means Clustering Techniques On The Trend And Seasonality Components Of Temperature Profile Data, Emmanuel Ogedegbe Dec 2023

Implementation Of Hierarchical And K-Means Clustering Techniques On The Trend And Seasonality Components Of Temperature Profile Data, Emmanuel Ogedegbe

Electronic Theses and Dissertations

In this study, time series decomposition techniques are used in conjunction with Kmeans clustering and Hierarchical clustering, two well-known clustering algorithms, to climate data. Their implementation and comparisons are then examined. The main objective is to identify similar climate trends and group geographical areas with similar environmental conditions. Climate data from specific places are collected and analyzed as part of the project. The time series is then split into trend, seasonality, and residual components. In order to categorize growing regions according to their climatic inclinations, the deconstructed time series are then submitted to K-means clustering and Hierarchical clustering with dynamic …

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Publication Of Undergraduate Experiments, Development Of Additional X-Ray Crystallography Experiments, And Proof-Of-Concept Cyclopropanation Reactions, Alain Beauparlant Dec 2023

Publication Of Undergraduate Experiments, Development Of Additional X-Ray Crystallography Experiments, And Proof-Of-Concept Cyclopropanation Reactions, Alain Beauparlant

Electronic Theses and Dissertations

Single crystal X-ray crystallography instructional materials were developed using a variety of compounds including sugar, Epsom salt, pyrite, copper(II) acetate, and rhodium(II) acetate. Rhodium(II) acetate was reacted with a variety of functionalized benzonitriles, and when crystals were obtained, characterized using single crystal X-ray crystallography. Rhodium(II) acetate with adducts of 4-nitrobenzonitrile and 4-(dimethylamino)benzonitrile were also characterized using proton NMR spectroscopy and Fourier Transform Infrared Spectroscopy. Rhodium(II) acetate with adducts of 4-(dimethylamino)benzonitrile was used as a catalyst in a proof-ofconcept reaction to determine if it acts as a catalyst in cyclopropanation reactions. Further, the new rhodium(II) acetate dinitrile compounds were investigated to …

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Isotopic Ecology Of Bison And Bootherium At Big Bone Lick, Kentucky, Frances Stephenson Dec 2023

Isotopic Ecology Of Bison And Bootherium At Big Bone Lick, Kentucky, Frances Stephenson

Electronic Theses and Dissertations

Big Bone Lick (BBL) is a late Pleistocene and Holocene fossil locality in the Ohio River valley of Kentucky. This study utilized stable isotopes (δ13C, δ18O, and 87Sr/86Sr) in tooth enamel to reconstruct mobility and diet in Bison, as well as diet in Bootherium bombifrons. Isotopic results from seven Bison and two B. bombifrons are reported. Results suggest Pleistocene Bison and Bootherium occupied different dietary niches. Although both had C3-dominated diets, Bison occupied more open environments than B. bombifrons. Two bison from the late Holocene deposit had diets that consisted …

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Computational Quantum Chemistry Studies Of The Stabilities Of Radical Adducts Formed During The Oxidation Of Melatonin Derivatives, James Horne Dec 2023

Computational Quantum Chemistry Studies Of The Stabilities Of Radical Adducts Formed During The Oxidation Of Melatonin Derivatives, James Horne

Electronic Theses and Dissertations

Melatonin is a natural antioxidant that has been investigated for properties as a potential spin trap to identify short-lived free radicals. Computational quantum chemistry studies have been performed for the oxidation of melatonin to N1-acetyl-N2-formyl-5-methoxykynuramine. This research focused on modification of melatonin into derivatives and analyzing the change in total molecular energy from melatonin to its oxidation product, as well as the corresponding derivatives. Each of the molecular geometries were optimized at the DFT/B3LYP/6-31G(d), DFT/B3LYP/cc-pVXZ (X = D, T), HF/6-31G(d), HF/cc-PVXZ (X = D, T), MP2/6-31G(d), and MP2/cc-PVXZ (X = D, T) levels of theory. …

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Synthesis Of Bacterial Glycerophospholipids For Biomembrane Model Studies: A Means To Advanced Biofuels, Felix Adulley Dec 2023

Synthesis Of Bacterial Glycerophospholipids For Biomembrane Model Studies: A Means To Advanced Biofuels, Felix Adulley

Electronic Theses and Dissertations

To reduce reliance on fossil fuels, sustainable biofuels are being pursued, especially advanced biofuels like 1-butanol that have higher energy content and greater compatibility with existing infrastructure than ethanol. A persistent challenge is the yield-limiting toxicity of biofuels and process solvents, such as tetrahydrofuran, to the microbes that ferment biomass into biofuel. The cell membrane is a focal point of toxicity, and understanding how it interacts with fuels and solvents is key to improving yield. Phospholipid bilayers are the core of biomembranes, and model biomembranes of defined composition provide the ideal platform for biophysical studies. To this end, glycerophospholipids characteristic …

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A Bridge Between Graph Neural Networks And Transformers: Positional Encodings As Node Embeddings, Bright Kwaku Manu Dec 2023

A Bridge Between Graph Neural Networks And Transformers: Positional Encodings As Node Embeddings, Bright Kwaku Manu

Electronic Theses and Dissertations

Graph Neural Networks and Transformers are very powerful frameworks for learning machine learning tasks. While they were evolved separately in diverse fields, current research has revealed some similarities and links between them. This work focuses on bridging the gap between GNNs and Transformers by offering a uniform framework that highlights their similarities and distinctions. We perform positional encodings and identify key properties that make the positional encodings node embeddings. We found that the properties of expressiveness, efficiency and interpretability were achieved in the process. We saw that it is possible to use positional encodings as node embeddings, which can be …

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Convolution And Autoencoders Applied To Nonlinear Differential Equations, Noah Borquaye Dec 2023

Convolution And Autoencoders Applied To Nonlinear Differential Equations, Noah Borquaye

Electronic Theses and Dissertations

Autoencoders, a type of artificial neural network, have gained recognition by researchers in various fields, especially machine learning due to their vast applications in data representations from inputs. Recently researchers have explored the possibility to extend the application of autoencoders to solve nonlinear differential equations. Algorithms and methods employed in an autoencoder framework include sparse identification of nonlinear dynamics (SINDy), dynamic mode decomposition (DMD), Koopman operator theory and singular value decomposition (SVD). These approaches use matrix multiplication to represent linear transformation. However, machine learning algorithms often use convolution to represent linear transformations. In our work, we modify these approaches to …

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Early Pliocene Mice And Rats From The Gray Fossil Site Of Eastern Tennessee: Implications For The Evolution Of Cricetidae And Understanding Of The Past Ecosystem, Ziqi Xu Dec 2023

Early Pliocene Mice And Rats From The Gray Fossil Site Of Eastern Tennessee: Implications For The Evolution Of Cricetidae And Understanding Of The Past Ecosystem, Ziqi Xu

Electronic Theses and Dissertations

Cricetidae ranks as the second-most species-rich and abundant mammalian family, with limited studies on eastern North American records prior to the Pleistocene. While cricetids has been previously noted at the early Pliocene Gray Fossil Site (GFS), this study provides a detailed description of eight taxa: Postcopemys (two species), Symmetrodontomys, Oryzomyini, Peromyscus, Neotoma, Neotomodon, and Xenomys. Postcopemys is the most common cricetid taxon at GFS, followed by Peromyscus and Neotoma. These records expand the stratigraphic and geographic range of multiple genera. Distinctive morphological features of GFS taxa suggest presence of several new species. The …

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Proteomics And Machine Learning For Pulmonary Embolism Risk With Protein Markers, Yaa Amankwah Awuah Dec 2023

Proteomics And Machine Learning For Pulmonary Embolism Risk With Protein Markers, Yaa Amankwah Awuah

Electronic Theses and Dissertations

This thesis investigates protein markers linked to pulmonary embolism risk using proteomics and statistical methods, employing unsupervised and supervised machine learning techniques. The research analyzes existing datasets, identifies significant features, and observes gender differences through MANOVA. Principal Component Analysis reduces variables from 378 to 59, and Random Forest achieves 70% accuracy. These findings contribute to our understanding of pulmonary embolism and may lead to diagnostic biomarkers. MANOVA reveals significant gender differences, and applying proteomics holds promise for clinical practice and research.

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The Surface Atmosphere Integrated Field Laboratory (Sail) Campaign, D. R. Feldman, A. C. Aiken, W. R. Boos, R. W. H. Carroll, V. Chandrasekar, S. Collis, J. M. Creamean, G. De Boer, J. Deems, P. J. Demott, J. Fan, A. N. Flores, D. Gochis, M. Grover, T. C. J. Hill, A. Hodshire, E. Hulm, C. C. Hume, R. Jackson, F. Junyent, A. Kennedy, M. Kumjian, E. J. T. Levin, J. D. Lundquist, J. O'Brien, M. S. Raleigh, J. Reithel, A. Rhoades, K. Rittger, W. Rudisill, Z. Sherman, E. Siirila-Woodburn, S. M. Skiles, J. N. Smith, R. C. Sullivan, A. Theisen, M. Tuftedal, A. C. Varble, A. Wiedlea, S. Wielandt, K. Williams, Z. Xu Dec 2023

The Surface Atmosphere Integrated Field Laboratory (Sail) Campaign, D. R. Feldman, A. C. Aiken, W. R. Boos, R. W. H. Carroll, V. Chandrasekar, S. Collis, J. M. Creamean, G. De Boer, J. Deems, P. J. Demott, J. Fan, A. N. Flores, D. Gochis, M. Grover, T. C. J. Hill, A. Hodshire, E. Hulm, C. C. Hume, R. Jackson, F. Junyent, A. Kennedy, M. Kumjian, E. J. T. Levin, J. D. Lundquist, J. O'Brien, M. S. Raleigh, J. Reithel, A. Rhoades, K. Rittger, W. Rudisill, Z. Sherman, E. Siirila-Woodburn, S. M. Skiles, J. N. Smith, R. C. Sullivan, A. Theisen, M. Tuftedal, A. C. Varble, A. Wiedlea, S. Wielandt, K. Williams, Z. Xu

Geosciences Faculty Publications and Presentations

The science of mountainous hydrology spans the atmosphere through the bedrock and inherently crosses physical and disciplinary boundaries: land–atmosphere interactions in complex terrain enhance clouds and precipitation, while watersheds retain and release water over a large range of spatial and temporal scales. Limited observations in complex terrain challenge efforts to improve predictive models of the hydrology in the face of rapid changes. The Upper Colorado River exemplifies these challenges, especially with ongoing mismatches between precipitation, snowpack, and discharge. Consequently, the U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) user facility has deployed an observatory to the East River Watershed …

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The Influence Of Subhaloes On Host Halo Properties, Lorena Mezini, Catherine E. Fielder, Andrew R. Zentner, Yao-Yuan Mao, Kuan Wang, Hao-Yi Wu Dec 2023

The Influence Of Subhaloes On Host Halo Properties, Lorena Mezini, Catherine E. Fielder, Andrew R. Zentner, Yao-Yuan Mao, Kuan Wang, Hao-Yi Wu

Physics Faculty Publications and Presentations

Within the ΛCDM cosmology, dark matter haloes are composed of both a smooth component and a population of smaller gravitationally bound subhaloes. These components are often treated as a single halo when properties, such as density profiles, are extracted from simulations. Recent work has shown that density profiles change substantially when subhalo mass is excluded. In this paper, we expand on this result by analysing three specific host halo properties – concentration (cNFW), spin (λB), and shape (c/a) – when calculated only from the smooth component of the halo. This analysis …

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Stress-Sensing In Flexible Epoxy Adhesives, Christine Rukeyser Dec 2023

Stress-Sensing In Flexible Epoxy Adhesives, Christine Rukeyser

Honors Theses

In mechanochemistry, mechanical force causes a chemical change using small molecules, called mechanophores, by covalently connecting them into polymer materials. Stress-sensing mechanophores give a visual signal of mechanical force on the molecular level within a material. To our knowledge, stress-sensing mechanophores have never been incorporated into a commercially available epoxy kit. In this work, the characterization of two 3MTM Scotch-Weld TM Epoxy Adhesive kits: DP100 Plus Clear and DP190 Translucent have been completed through FT-IR Spectroscopy. The addition of the mechanophore spiropyran to the 3M kits will be discussed; as well as preparation and characterization of three dimerized anthracene derivatives. …

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Kape: Knn-Based Performance Testing For Deep Code Search, Yuejun Guo, Qiang Hu, Xiaofei Xie, Cordy Maxime, Mike Papadakis, Yves Le Traon Dec 2023

Kape: Knn-Based Performance Testing For Deep Code Search, Yuejun Guo, Qiang Hu, Xiaofei Xie, Cordy Maxime, Mike Papadakis, Yves Le Traon

Research Collection School Of Computing and Information Systems

Code search is a common yet important activity of software developers. An efficient code search model can largely facilitate the development process and improve the programming quality. Given the superb performance of learning the contextual representations, deep learning models, especially pre-trained language models, have been widely explored for the code search task. However, studies mainly focus on proposing new architectures for ever-better performance on designed test sets but ignore the performance on unseen test data where only natural language queries are available. The same problem in other domains, e.g., CV and NLP, is usually solved by test input selection that …

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Estimating Propensity For Causality-Based Recommendation Without Exposure Data, Zhongzhou Liu, Yuan Fang, Min Wu Dec 2023

Estimating Propensity For Causality-Based Recommendation Without Exposure Data, Zhongzhou Liu, Yuan Fang, Min Wu

Research Collection School Of Computing and Information Systems

Causality-based recommendation systems focus on the causal effects of user-item interactions resulting from item exposure (i.e., which items are recommended or exposed to the user), as opposed to conventional correlation-based recommendation. They are gaining popularity due to their multi-sided benefits to users, sellers and platforms alike. However, existing causality-based recommendation methods require additional input in the form of exposure data and/or propensity scores (i.e., the probability of exposure) for training. Such data, crucial for modeling causality in recommendation, are often not available in real-world situations due to technical or privacy constraints. In this paper, we bridge the gap by proposing …

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Monocular Depth Estimation For Glass Walls With Context: A New Dataset And Method, Yuan Liang, Bailin Deng, Wenxi Liu, Jing Qin, Shengfeng He Dec 2023

Monocular Depth Estimation For Glass Walls With Context: A New Dataset And Method, Yuan Liang, Bailin Deng, Wenxi Liu, Jing Qin, Shengfeng He

Research Collection School Of Computing and Information Systems

Traditional monocular depth estimation assumes that all objects are reliably visible in the RGB color domain. However, this is not always the case as more and more buildings are decorated with transparent glass walls. This problem has not been explored due to the difficulties in annotating the depth levels of glass walls, as commercial depth sensors cannot provide correct feedbacks on transparent objects. Furthermore, estimating depths from transparent glass walls requires the aids of surrounding context, which has not been considered in prior works. To cope with this problem, we introduce the first Glass Walls Depth Dataset (GW-Depth dataset). We …

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Robust Test Selection For Deep Neural Networks, Weifeng Sun, Meng Yan, Zhongxin Liu, David Lo Dec 2023

Robust Test Selection For Deep Neural Networks, Weifeng Sun, Meng Yan, Zhongxin Liu, David Lo

Research Collection School Of Computing and Information Systems

Deep Neural Networks (DNNs) have been widely used in various domains, such as computer vision and software engineering. Although many DNNs have been deployed to assist various tasks in the real world, similar to traditional software, they also suffer from defects that may lead to severe outcomes. DNN testing is one of the most widely used methods to ensure the quality of DNNs. Such method needs rich test inputs with oracle information (expected output) to reveal the incorrect behaviors of a DNN model. However, manually labeling all the collected test inputs is a labor-intensive task, which delays the quality assurance …

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Benchmarking Foundation Models With Language-Model-As-An-Examiner, Yushi Bai, Jiahao Ying, Yixin Cao, Xin Lv, Yuze He, Xiaozhi Wang, Jifan Yu, Kaisheng Zeng, Yijia Xiao, Haozhe Lyu, Jiayin Zhang, Juanzi Li, Lei Hou Dec 2023

Benchmarking Foundation Models With Language-Model-As-An-Examiner, Yushi Bai, Jiahao Ying, Yixin Cao, Xin Lv, Yuze He, Xiaozhi Wang, Jifan Yu, Kaisheng Zeng, Yijia Xiao, Haozhe Lyu, Jiayin Zhang, Juanzi Li, Lei Hou

Research Collection School Of Computing and Information Systems

Numerous benchmarks have been established to assess the performance of foundation models on open-ended question answering, which serves as a comprehensive test of a model’s ability to understand and generate language in a manner similar to humans. Most of these works focus on proposing new datasets, however, we see two main issues within previous benchmarking pipelines, namely testing leakage and evaluation automation. In this paper, we propose a novel benchmarking framework, Language-Model-as-an-Examiner, where the LM serves as a knowledgeable examiner that formulates questions based on its knowledge and evaluates responses in a reference-free manner. Our framework allows for effortless extensibility …

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Efficient Meta Neural Heuristic For Multi-Objective Combinatorial Optimization, Jinbiao Chen, Zizhen Zhang, Te Ye, Zhiguang Cao, Siyuan Chen, Jiahai Wang Dec 2023

Efficient Meta Neural Heuristic For Multi-Objective Combinatorial Optimization, Jinbiao Chen, Zizhen Zhang, Te Ye, Zhiguang Cao, Siyuan Chen, Jiahai Wang

Research Collection School Of Computing and Information Systems

Recently, neural heuristics based on deep reinforcement learning have exhibited promise in solving multi-objective combinatorial optimization problems (MOCOPs). However, they are still struggling to achieve high learning efficiency and solution quality. To tackle this issue, we propose an efficient meta neural heuristic (EMNH), in which a meta model is first trained and then fine-tuned with a few steps to solve corresponding single-objective subproblems. Specifically, for the training process, a (partial) architecture-shared multi-task model is leveraged to achieve parallel learning for the meta model, so as to speed up the training; meanwhile, a scaled symmetric sampling method with respect to the …

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Truncated Affinity Maximization: One-Class Homophily Modeling For Graph Anomaly Detection, Hezhe Qiao, Guansong Pang Dec 2023

Truncated Affinity Maximization: One-Class Homophily Modeling For Graph Anomaly Detection, Hezhe Qiao, Guansong Pang

Research Collection School Of Computing and Information Systems

We reveal a one-class homophily phenomenon, which is one prevalent property we find empirically in real-world graph anomaly detection (GAD) datasets, i.e., normal nodes tend to have strong connection/affinity with each other, while the homophily in abnormal nodes is significantly weaker than normal nodes. However, this anomaly-discriminative property is ignored by existing GAD methods that are typically built using a conventional anomaly detection objective, such as data reconstruction. In this work, we explore this property to introduce a novel unsupervised anomaly scoring measure for GAD – local node affinity – that assigns a larger anomaly score to nodes that are …

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A Closer Look At The Security Risks In The Rust Ecosystem, Xiaoye Zheng, Zhiyuan Wan, Yun Zhang, Rui Chang, David Lo Dec 2023

A Closer Look At The Security Risks In The Rust Ecosystem, Xiaoye Zheng, Zhiyuan Wan, Yun Zhang, Rui Chang, David Lo

Research Collection School Of Computing and Information Systems

Rust is an emerging programming language designed for the development of systems software. To facilitate the reuse of Rust code, crates.io, as a central package registry of the Rust ecosystem, hosts thousands of third-party Rust packages. The openness of crates.io enables the growth of the Rust ecosystem but comes with security risks by severe security advisories. Although Rust guarantees a software program to be safe via programming language features and strict compile-time checking, the unsafe keyword in Rust allows developers to bypass compiler safety checks for certain regions of code. Prior studies empirically investigate the memory safety and concurrency bugs …

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Extending The Horizon By Empowering Government Customer Service Officers With Acqar For Enhanced Citizen Service Delivery, Hui Shan Lee, Shankararaman, Venky, Eng Lieh Ouh Dec 2023

Extending The Horizon By Empowering Government Customer Service Officers With Acqar For Enhanced Citizen Service Delivery, Hui Shan Lee, Shankararaman, Venky, Eng Lieh Ouh

Research Collection School Of Computing and Information Systems

A previous study on the use of the Empath library in the prediction of Service Level Agreements (SLA) reveals the quality levels required for meaningful interaction between government customer service officers and citizens. On the other hand, past implementation of the Citizen Question-Answer system (CQAS), a type of Question-Answer model, suggests that such models if put in place can empower government customer service officers to reply faster and better with recommended answers. This study builds upon the research outcomes from both arenas of studies and introduces an innovative system design that allows the officers to incorporate the outputs from Empath …

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Assessing The Effectiveness Of A Chatbot Workshop As Experiential Teaching And Learning Tool To Engage Undergraduate Students, Kyong Jin Shim, Thomas Menkhoff, Ying Qian Teo, Clement Shi Qi Ong Dec 2023

Assessing The Effectiveness Of A Chatbot Workshop As Experiential Teaching And Learning Tool To Engage Undergraduate Students, Kyong Jin Shim, Thomas Menkhoff, Ying Qian Teo, Clement Shi Qi Ong

Research Collection School Of Computing and Information Systems

In this paper, we empirically examine and assess the effectiveness of a chatbot workshop as experiential teaching and learning tool to engage undergraduate students enrolled in an elective course “Doing Business with A.I.” in the Lee Kong Chian School of Business (LKCSB) at Singapore Management University. The chatbot workshop provides non-STEM students with an opportunity to acquire basic skills to build a chatbot prototype using the ‘Dialogflow’ program. The workshop and the experiential learning activity are designed to impart conversation and user-centric design know how and know why to students. A key didactical aspect which informs the design and flow …

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