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Articles 34081 - 34110 of 291657

Full-Text Articles in Physical Sciences and Mathematics

Computation-Assisted Molecular Discovery For Biomedical Applications: Seeking Small Molecules And Dna Sequences With High Affinity Target Binding, Payam Kelich Dec 2023

Computation-Assisted Molecular Discovery For Biomedical Applications: Seeking Small Molecules And Dna Sequences With High Affinity Target Binding, Payam Kelich

Open Access Theses & Dissertations

Binding affinity between two molecules is an essential property in drug and sensor discovery. Several computational and experimental methods exist to find molecules with high binding affinities to desired target molecules. These methods are often complementary, where fast computational methods can be used for the initial screening of molecules, and experimental methods can then screen and determine the molecules of interest and sometimes define the structures of bound complexes. After these steps, computational methods, like molecular dynamics (MD) simulations, can provide detailed insights into atomic interactions and binding, and machine learning approaches can analyze experiment-derived data to discern patterns and …

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Southern Rio Grande Rift Kinematics And Geochronology, Big Bend Fold Geometry, And The Use Of Real Data In Geoscience Education: Contributions To The Understanding Of Big Bend Geology And To Public Geoscientific Literacy, Jessica Kelsch Dec 2023

Southern Rio Grande Rift Kinematics And Geochronology, Big Bend Fold Geometry, And The Use Of Real Data In Geoscience Education: Contributions To The Understanding Of Big Bend Geology And To Public Geoscientific Literacy, Jessica Kelsch

Open Access Theses & Dissertations

The Big Bend region of Trans-Pecos Texas preserves a rich record of Rio Grande rifting and Laramide-age contraction that provide intrigue to national and state park visitors and field trips for undergraduate geology students. Despite its well-exposed geologic record, the Big Bend region remains an underutilized natural laboratory for studying these two tectonic events. This dissertation combines structural studies of Rio Grande rift and Laramide structures with public outreach and geoscience education studies focused on the Big Bend region. In Chapter 2, existing extensional-kinematic studies from parts of this region are compiled with new fault kinematic and U-Pb geochronologic data …

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Leveraging Agile Software Methodologies Within Software Development To Introduce A Novel Educational Software Methodology, Montserrat Guadalupe Molina Dec 2023

Leveraging Agile Software Methodologies Within Software Development To Introduce A Novel Educational Software Methodology, Montserrat Guadalupe Molina

Open Access Theses & Dissertations

Agile Software Development has been growing increasingly popular in the software engineering industry as a way to produce working software in a quick and people-centered manner. Agile methodologies require practitioners to have strong technical and non-technical skills, such as teamwork, project management, and communication skills. Students graduating from the software engineering discipline have been found to be lacking in these areas, leading to many difficulties faced by recent graduates as they begin their professional careers. Given that Agile Software Development is the most popular software development lifecycle currently used by practitioners in industry, it is important to expose students to …

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Sterically Encumbering Ligands For The Synthesis And Stabilization Of Iron Nitride And Iron Oxo Compounds, Asiel Mena Dec 2023

Sterically Encumbering Ligands For The Synthesis And Stabilization Of Iron Nitride And Iron Oxo Compounds, Asiel Mena

Open Access Theses & Dissertations

The study of iron-nitrides has been found to be very attractive due to their potential role in processes like Haber-Bosch and nitrogen fixation by nitrogenase. The role of iron-nitrides in these processes is yet not well understood, and the fact that only handful of terminal iron-nitrides have been isolated or spectroscopically detected motivates us to study this type of systems, since much remains to be learned about the electronic and structural factors that affect the chemistry of the Feâ?¡N bond. Recently in our group, by using a super-bulky guanidinate ligand (LAr*), the obtention of an iron-nitride ([LAr*]FeN(py) (LAr* = (Ar*N)2C(NCtBu2), …

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Co2-Dependent Nanoscale Organization In Bulk And Interfacial Carbon Dioxide Capture Liquids Elucidated Using X-Ray Scattering, Daniel Eduardo Moran Dec 2023

Co2-Dependent Nanoscale Organization In Bulk And Interfacial Carbon Dioxide Capture Liquids Elucidated Using X-Ray Scattering, Daniel Eduardo Moran

Open Access Theses & Dissertations

The pressing need to control carbon dioxide emissions has propelled extensive research efforts employing a variety of approaches across the globe. In flue-gas recovery of CO2, the water-lean amine-based solvent N-(2-ethoxyethyl)-3-morpholinopropan-1-amine (2-EEMPA), has shown exceptional performance. Recent studies show that 2-EEMPA exhibits intermediate-range order (IRO), beyond the first nearest neighbor length scale, consisting of tetrameric clusters. In view of the need to find solutions for direct air capture (DAC) of CO2, this system may represent a critical linkage in a DAC strategy, yet structural insights on EEMPA's behavior at solid surfaces are still lacking. To this end, we applied the …

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Enhancing Our Understanding Of Ancient Oceans Through The Investigation Of Molybdenum Behavior Under Sulfidic Conditions, Rachel Faye Phillips Dec 2023

Enhancing Our Understanding Of Ancient Oceans Through The Investigation Of Molybdenum Behavior Under Sulfidic Conditions, Rachel Faye Phillips

Open Access Theses & Dissertations

The most abundant trace metal in the ocean today, molybdenum (Mo), exhibits distinct behavior in oxygenated water, where it remains predominantly dissolved, compared to euxinic (i.e., oxygen-free and sulfidic) water, in which it is sequestered into the sediment. This dissimilar behavior allows us to use Mo concentrations and isotopic compositions in sediment to reconstruct marine oxygenation conditions throughout geologic history. However, Mo sequestration mechanisms under euxinic conditions remain unresolved, which limits the accuracy and precision of reconstructions made using Mo signatures in the rock record. For my doctoral research, I experimentally investigated abiotic and biotic Mo sequestration mechanisms under various …

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Metrics For Comparison Of Complex Networks, Clarissa Reyes Dec 2023

Metrics For Comparison Of Complex Networks, Clarissa Reyes

Open Access Theses & Dissertations

Heuristic network statistics are used as a preliminary approach to identify change across networks. In networks where there is known node correspondence (KNC), conventional network comparison methods include taking a norm of the difference matrix, or calculating dissimilarity measures like DeltaCon and cut distance. Since different KNC measures provide varying insight to the network comparison problem, we propose employing Rank Score Characteristic Functions (RSCFs) and the rank-score process as a method for reaching a consensus when ranking quantified change across multiple pairs of networks â?? which is particularly useful for ranking change across subpopulations or subgraphs. Additionally, we propose a …

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Alteration And Mineralization Of The Deep Extension Of The Giant Chuquicamata Porphyry Copper Deposit, Northern Chile, Claudio Andres Araya Torres Dec 2023

Alteration And Mineralization Of The Deep Extension Of The Giant Chuquicamata Porphyry Copper Deposit, Northern Chile, Claudio Andres Araya Torres

Open Access Theses & Dissertations

Porphyry copper deposits are the major source of copper and molybdenum in the world. The deposits consist of large volumes of rock altered by hydrothermal fluids released by shallow, intermediate composition magma chambers, with metallic mineralization present in veins, breccias, and disseminations; ore grades are typically 0.3-1.0 wt.% Cu. The subject of this study, the Chuquicamata porphyry copper deposit in northern Chile, is one of the most productive such deposits in the world, with over 45 million tons of Cu produced since large scale, open pit mining started early in the XXth century. Current production at Chuquicamata is from an …

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Viability Of Magnetic Nanoparticles For Magnetic Hyperthermia Cancer Therapy, Marcos Adrian Garcia Dec 2023

Viability Of Magnetic Nanoparticles For Magnetic Hyperthermia Cancer Therapy, Marcos Adrian Garcia

Open Access Theses & Dissertations

Over the last few decades magnetic nanoparticles have gained an extraordinary amount of attention in the science community. Their versatile use in many different research areas such as medicine, engineering and technology and many other areas has made them a popular subject. In this thesis, the synthesis of different systems of magnetic nanoparticles will be explored along with the potential use of the MNP's as viable candidates for Magnetic Hyperthermia Cancer Therapy. With values of over 200 emu/g for Iron-Silver magnetic nanoparticles with particle sizes ranging from 30-70nm and their heating properties under an AC magnetic field. As well of …

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Synthesis And Characterization Of Acetaminophen-Derived Nanoparticles: A Novel Approach To Inhibit Fibril Formation, Hannia Elena Mendoza-Dickey Dec 2023

Synthesis And Characterization Of Acetaminophen-Derived Nanoparticles: A Novel Approach To Inhibit Fibril Formation, Hannia Elena Mendoza-Dickey

Open Access Theses & Dissertations

In the realm of nanotechnology, nanoparticles (NPs), have garnered significant notoriety in recent scientific research due to their unique physical and chemical properties, such as fluorescence emissions, nanoscale dimensions (typically <1000 nm), ease of surface modification, and biocompatibility. Nanoparticles have shown their potential across a variety of areas, including advanced industrial applications and cutting-edge biomedical research. Considering their cost-effective synthesis, they have shown promise as therapeutic agents for a variety of bioimaging and biomedical applications. This thesis describes the synthesis and detailed analysis of acetaminophen-derived nanoparticles. Techniques such as Dynamic Light Scattering (DLS), Thioflavin T (THT) assay, Attenuated Total Reflectance Infrared Spectroscopy (ATR-IR), 1H NMR spectroscopy, and Ultraviolet-Visible Spectroscopy (UV-VIS) were utilized for structural and functional assessments. Acetaminophen derived nanoparticles (ANPs) exhibit potential to hinder the amyloidogenic conversion of soluble amyloid-forming proteins into their toxic form. The novelty of this research focuses on the utilization of chemical structures capable of traversing the Blood Brain Barrier (BBB) to mitigate xenotoxicant-induced neuronal damage, a notable contributor to neurodegenerative disorders. This thesis describes the synthesis and characterization of acetaminophen derived-nanoparticles (ANPs). Our nanoparticles possess anti-amyloidogenic properties as evidenced by their ability to disrupt in the soluble-to-toxic trajectory of HEWL. The prevalence and evolution of amyloid fibrils are consistent features in the pathology of neurodegenerative diseases such as Parkinson's disease (PD), Alzheimerâ??s Disease (AD), and Huntingtonâ??s Disease (HD), as well as metabolic disorders like Type 2 diabetes (T2D). The relationship between amyloidogenic pathways and these disorders highlights the imperative for enhanced understanding and the formulation of specific therapeutic interventions.

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Study Of Human Circadian Protein (Hrory) And Lipid-Protein Interaction In Giant Virus (Pbcv-1), Laila Noor Dec 2023

Study Of Human Circadian Protein (Hrory) And Lipid-Protein Interaction In Giant Virus (Pbcv-1), Laila Noor

Open Access Theses & Dissertations

Project 1: Circadian rhythm is a 24-hour cycle that regulates physical and behavioral changes such as sleep-wake patterns in humans, tailoring the daily light and dark changes. Long-term disruption in circadian rhythms can cause sleep disorders such as sleep apnea, insomnia, et al. Limited research has been done on potential drugs to treat against circadian related sleep disorders. Inside the cell at molecular level, the circadian rhythm is regulated by interlocked time-delayed feedback loops, which involve positive and negative transcriptional regulators. Experimental results showed transcriptional factors Retinoic Acid Receptor-Related Orphan Receptors (RORs) improve the stability and functionality of the circadian …

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Towards Explaining Neural Networks: Tools For Visualizing Activations And Parameters, Juan Puebla Dec 2023

Towards Explaining Neural Networks: Tools For Visualizing Activations And Parameters, Juan Puebla

Open Access Theses & Dissertations

There is a growing number of applications using neural networks for making decisions. However, there is a general lack of understanding of how neural networks work. Neural networks have even been described as black boxes which has led to a lack of trust in artificially intelligent programs. To remedy this, explainable artificial intelligence has risen as a means to validate the decision-making processes and the results of computer programs that use artificial intelligence. The work in this masterâ??s thesis is our contribution to explainable artificial intelligence, focusing on neural networks with the goal of helping users make more sense of …

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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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Customer Cybersecurity And Supplier Cost Management Strategy, Xu Yang, Peng Liang, Nan Hu, Fujing Xue Dec 2023

Customer Cybersecurity And Supplier Cost Management Strategy, Xu Yang, Peng Liang, Nan Hu, Fujing Xue

Research Collection School Of Computing and Information Systems

In this paper, we explore the spillover effect of customer firms’ data breaches on their upstream supplier firms’ cost management strategies, proxied by cost stickiness. Our primary analyses suggest that data breaches suffered by customer firms are associated with a decrease in cost stickiness among supplier firms. Furthermore, the reductions in supplier cost stickiness are stronger if suppliers are managed by CEOs from national cultural groups with high uncertainty avoidance, low long-term orientations, and/or low individualism. In sum, the findings contribute to both Information Systems (IS) and Operations Management (OM) disciplines in terms of data breach, cost management strategy, and …

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Software Composition Analysis For Vulnerability Detection: An Empirical Study On Java Projects, Lida Zhao, Sen Chen, Zhengzi Xu, Lyuye Zhang, Jiahui Wu, Jun Sun, Yang Liu Dec 2023

Software Composition Analysis For Vulnerability Detection: An Empirical Study On Java Projects, Lida Zhao, Sen Chen, Zhengzi Xu, Lyuye Zhang, Jiahui Wu, Jun Sun, Yang Liu

Research Collection School Of Computing and Information Systems

Software composition analysis (SCA) tools are proposed to detect potential vulnerabilities introduced by open-source software (OSS) imported as third-party libraries (TPL). With the increasing complexity of software functionality, SCA tools may encounter various scenarios during the dependency resolution process, such as diverse formats of artifacts, diverse dependency imports, and diverse dependency specifications. However, there still lacks a comprehensive evaluation of SCA tools for Java that takes into account the above scenarios. This could lead to a confined interpretation of comparisons, improper use of tools, and hinder further improvements of the tools. To fill this gap, we proposed an Evaluation Model …

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Generalized Logit Adjustment: Calibrating Fine-Tuned Models By Removing Label Bias In Foundation Models, Beier Zhu, Kaihua Tang, Qianru Sun, Hanwang Zhang Dec 2023

Generalized Logit Adjustment: Calibrating Fine-Tuned Models By Removing Label Bias In Foundation Models, Beier Zhu, Kaihua Tang, Qianru Sun, Hanwang Zhang

Research Collection School Of Computing and Information Systems

Foundation models like CLIP allow zero-shot transfer on various tasks without additional training data. Yet, the zero-shot performance is less competitive than a fully supervised one. Thus, to enhance the performance, fine-tuning and ensembling are also commonly adopted to better fit the downstream tasks. However, we argue that such prior work has overlooked the inherent biases in foundation models. Due to the highly imbalanced Web-scale training set, these foundation models are inevitably skewed toward frequent semantics, and thus the subsequent fine-tuning or ensembling is still biased. In this study, we systematically examine the biases in foundation models and demonstrate the …

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Mrim: Lightweight Saliency-Based Mixed-Resolution Imaging For Low-Power Pervasive Vision, Jiyan Wu, Vithurson Subasharan, Minh Anh Tuan Tran, Kasun Pramuditha Gamlath, Archan Misra Dec 2023

Mrim: Lightweight Saliency-Based Mixed-Resolution Imaging For Low-Power Pervasive Vision, Jiyan Wu, Vithurson Subasharan, Minh Anh Tuan Tran, Kasun Pramuditha Gamlath, Archan Misra

Research Collection School Of Computing and Information Systems

While many pervasive computing applications increasingly utilize real-time context extracted from a vision sensing infrastructure, the high energy overhead of DNN-based vision sensing pipelines remains a challenge for sustainable in-the-wild deployment. One common approach to reducing such energy overheads is the capture and transmission of lower-resolution images to an edge node (where the DNN inferencing task is executed), but this results in an accuracy-vs-energy tradeoff, as the DNN inference accuracy typically degrades with a drop in resolution. In this work, we introduce MRIM, a simple but effective framework to tackle this tradeoff. Under MRIM, the vision sensor platform first executes …

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M2-Cnn: A Macro-Micro Model For Taxi Demand Prediction, Shih-Fen Cheng, Prabod Manuranga Rathnayaka Mudiyanselage Dec 2023

M2-Cnn: A Macro-Micro Model For Taxi Demand Prediction, Shih-Fen Cheng, Prabod Manuranga Rathnayaka Mudiyanselage

Research Collection School Of Computing and Information Systems

In this paper, we introduce a macro-micro model for predicting taxi demands. Our model is a composite deep learning model that integrates multiple views. Our network design specifically incorporates the spatial and temporal dependency of taxi or ride-hailing demand, unlike previous papers that also utilize deep learning models. In addition, we propose a hybrid of Long Short-Term Memory Networks and Temporal Convolutional Networks that incorporates real world time series with long sequences. Finally, we introduce a microscopic component that attempts to extract insights revealed by roaming vacant taxis. In our study, we demonstrate that our approach is competitive against a …

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Designing Large-Scale Intelligent Collaborative Platform For Freight Forwarders, Pang Jin Tan, Shih-Fen Cheng, Richard Chen Dec 2023

Designing Large-Scale Intelligent Collaborative Platform For Freight Forwarders, Pang Jin Tan, Shih-Fen Cheng, Richard Chen

Research Collection School Of Computing and Information Systems

In this paper, we propose to design a large-scale intelligent collaborative platform for freight forwarders. This platform is based on a mathematical programming formulation and an efficient solution approach. Forwarders are middlemen who procure container capacities from carriers and sell them to shippers to serve their transport requests. However, due to demand uncertainty, they often either over-procure or under-procure capacities. We address this with our proposed platform where forwarders can collaborate and share capacities, allowing one's transport requests to be potentially shipped on another forwarder's container. The result is lower total costs for all participating forwarders. The collaboration can be …

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On The Usage Of Continual Learning For Out-Of-Distribution Generalization In Pre-Trained Language Models Of Code, Martin Weyssow, Xin Zhou, Kisub Kim, David Lo, Houari A. Sahraoui Dec 2023

On The Usage Of Continual Learning For Out-Of-Distribution Generalization In Pre-Trained Language Models Of Code, Martin Weyssow, Xin Zhou, Kisub Kim, David Lo, Houari A. Sahraoui

Research Collection School Of Computing and Information Systems

Pre-trained language models (PLMs) have become a prevalent technique in deep learning for code, utilizing a two-stage pre-training and fine-tuning procedure to acquire general knowledge about code and specialize in a variety of downstream tasks. However, the dynamic nature of software codebases poses a challenge to the effectiveness and robustness of PLMs. In particular, world-realistic scenarios potentially lead to significant differences between the distribution of the pre-training and test data, i.e., distribution shift, resulting in a degradation of the PLM's performance on downstream tasks. In this paper, we stress the need for adapting PLMs of code to software data whose …

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Clusterprompt: Cluster Semantic Enhanced Prompt Learning For New Intent Discovery, Jinggui Liang, Lizi Liao Dec 2023

Clusterprompt: Cluster Semantic Enhanced Prompt Learning For New Intent Discovery, Jinggui Liang, Lizi Liao

Research Collection School Of Computing and Information Systems

The discovery of new intent categories from user utterances is a crucial task in expanding agent skills. The key lies in how to efficiently solicit semantic evidence from utterances and properly transfer knowledge from existing intents to new intents. However, previous methods laid too much emphasis on relations among utterances or clusters for transfer learning, while paying less attention to the usage of semantics. As a result, these methods suffer from in-domain over-fitting and often generate meaningless new intent clusters due to data distortion. In this paper, we present a novel approach called Cluster Semantic Enhanced Prompt Learning (CsePL) for …

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A Reliable And Secure Mobile Cyber-Physical Digital Microfluidic Biochip For Intelligent Healthcare, Yinan Yao, Decheng Qiu, Huangda Liu, Zhongliao Yang, Ximeng Liu, Yang Yang, Chen Dong Dec 2023

A Reliable And Secure Mobile Cyber-Physical Digital Microfluidic Biochip For Intelligent Healthcare, Yinan Yao, Decheng Qiu, Huangda Liu, Zhongliao Yang, Ximeng Liu, Yang Yang, Chen Dong

Research Collection School Of Computing and Information Systems

Digital microfluidic, as an emerging and potential technology, diversifies the biochemical applications platform, such as protein dilution sewage detection. At present, a vast majority of universal cyberphysical digital microfluidic biochips (DMFBs) transmit data through wires via personal computers and microcontrollers (like Arduino), consequently, susceptible to various security threats and with the popularity of wireless devices, losing competitiveness gradually. On the premise that security be ensured first and foremost, calls for wireless portable, safe, and economical DMFBs are imperative to expand their application fields, engage more users, and cater to the trend of future wireless communication. To this end, a new …

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A Big Data Approach To Augmenting The Huff Model With Road Network And Mobility Data For Store Footfall Prediction, Ming Hui Tan, Kar Way Tan, Hoong Chuin Lau Dec 2023

A Big Data Approach To Augmenting The Huff Model With Road Network And Mobility Data For Store Footfall Prediction, Ming Hui Tan, Kar Way Tan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Conventional methodologies for new retail store catchment area and footfall estimation rely on ground surveys which are costly and time-consuming. This study augments existing research in footfall estimation through the innovative integration of mobility data and road network to create population-weighted centroids and delineate residential neighbourhoods via a community detection algorithm. Our findings are then used to enhance Huff Model which is commonly used in site selection and footfall estimation. Our approach demonstrated the vast potential residing within big data where we harness the power of mobility data and road network information, offering a cost-effective and scalable alternative. It obviates …

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How Helpful Do Novice Programmers Find The Feedback Of An Automated Repair Tool?, Oka Kurniawan, Christopher M. Poskitt, Ismam Al Hoque, Norman Tiong Seng Lee, Cyrille Jégourel, Nachamma Sockalingam Dec 2023

How Helpful Do Novice Programmers Find The Feedback Of An Automated Repair Tool?, Oka Kurniawan, Christopher M. Poskitt, Ismam Al Hoque, Norman Tiong Seng Lee, Cyrille Jégourel, Nachamma Sockalingam

Research Collection School Of Computing and Information Systems

Immediate feedback has been shown to improve student learning. In programming courses, immediate, automated feedback is typically provided in the form of pre-defined test cases run by a submission platform. While these are excellent for highlighting the presence of logical errors, they do not provide novice programmers enough scaffolding to help them identify where an error is or how to fix it. To address this, several tools have been developed that provide richer feedback in the form of program repairs. Studies of such tools, however, tend to focus more on whether correct repairs can be generated, rather than how novices …

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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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Sustainability Projects With A Community Partner: A Social Norm Nudging Effort, Benjamin Gan, Thomas Menkhoff, Eng Lieh Ouh Dec 2023

Sustainability Projects With A Community Partner: A Social Norm Nudging Effort, Benjamin Gan, Thomas Menkhoff, Eng Lieh Ouh

Research Collection School Of Computing and Information Systems

Singapore students from two inter-disciplinary courses worked with stakeholders of a local business association community partner on a series of sustainability topics to learn about climate change, its effects, and actions to mitigate them. They empathized with the association stakeholders, proposed a digital technology solution, tested their prototypes, and presented the final action plans. After the projects were completed, we found climate proficient (83%), motivated (83%), engaged (97%), and satisfied (70%) students; and two influencing predictors: interest/enjoyment and emotional engagement. The study results suggest that getting students interested and emotionally engaged in sustainability projects is an important first step towards …

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Vision Paper: Advancing Of Ai Explainability For The Use Of Chatgpt In Government Agencies: Proposal Of A 4-Step Framework, Hui Shan Lee, Shankararaman, Venky, Eng Lieh Ouh Dec 2023

Vision Paper: Advancing Of Ai Explainability For The Use Of Chatgpt In Government Agencies: Proposal Of A 4-Step Framework, Hui Shan Lee, Shankararaman, Venky, Eng Lieh Ouh

Research Collection School Of Computing and Information Systems

This paper explores ChatGPT’s potential in aiding government agencies, drawing from a case study based on a government agency in Singapore. While ChatGPT’s text generation abilities offer promise, it brings inherent challenges, including data opacity, potential misinformation, and occasional errors. These issues are especially critical in government decision-making.Public administration’s core values of transparency and accountability magnify these concerns. Ensuring AI alignment with these principles is imperative, given the potential repercussions on policy outcomes and citizen trust.AI explainability plays a central role in ChatGPT’s adoption within government agencies. To address these concerns, we propose strategies like prompt engineering, data governance, and …

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Prompting And Evaluating Large Language Models For Proactive Dialogues: Clarification, Target-Guided, And Non-Collaboration, Yang Deng, Lizi Liao, Liang Chen, Hongru Wang, Wenqiang Lei, Tat-Seng Chua Dec 2023

Prompting And Evaluating Large Language Models For Proactive Dialogues: Clarification, Target-Guided, And Non-Collaboration, Yang Deng, Lizi Liao, Liang Chen, Hongru Wang, Wenqiang Lei, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Conversational systems based on Large Language Models (LLMs), such as ChatGPT, show exceptional proficiency in context understanding and response generation. However, they still possess limitations, such as failing to ask clarifying questions to ambiguous queries or refuse users' unreasonable requests, both of which are considered as key aspects of a conversational agent's proactivity. This raises the question of whether LLM-based conversational systems are equipped to handle proactive dialogue problems. In this work, we conduct a comprehensive analysis of LLM-based conversational systems, specifically focusing on three key aspects of proactive dialogues: clarification, target-guided, and non-collaborative dialogues. To trigger the proactivity of …

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Beyond Factuality: A Comprehensive Evaluation Of Large Language Models As Knowledge Generators, Liang Chen, Yang Deng, Yatao Bian, Zeyu Qin, Bingzhe Wu, Tat-Seng Chua, Kam-Fai Wong Dec 2023

Beyond Factuality: A Comprehensive Evaluation Of Large Language Models As Knowledge Generators, Liang Chen, Yang Deng, Yatao Bian, Zeyu Qin, Bingzhe Wu, Tat-Seng Chua, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Large language models (LLMs) outperform information retrieval techniques for downstream knowledge-intensive tasks when being prompted to generate world knowledge. Yet, community concerns abound regarding the factuality and potential implications of using this uncensored knowledge. In light of this, we introduce CONNER, a COmpreheNsive kNowledge Evaluation fRamework, designed to systematically and automatically evaluate generated knowledge from six important perspectives - Factuality, Relevance, Coherence, Informativeness, Helpfulness and Validity. We conduct an extensive empirical analysis of the generated knowledge from three different types of LLMs on two widely-studied knowledge-intensive tasks, i.e., open-domain question answering and knowledge-grounded dialogue. Surprisingly, our study reveals that the …

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Neural Airport Ground Handling, Yaoxin Wu, Jianan Zhou, Yunwen Xia, Xianli Zhang, Zhiguang Cao, Jie Zhang Dec 2023

Neural Airport Ground Handling, Yaoxin Wu, Jianan Zhou, Yunwen Xia, Xianli Zhang, Zhiguang Cao, Jie Zhang

Research Collection School Of Computing and Information Systems

Airport ground handling (AGH) offers necessary operations to flights during their turnarounds and is of great importance to the efficiency of airport management and the economics of aviation. Such a problem involves the interplay among the operations that leads to NP-hard problems with complex constraints. Hence, existing methods for AGH are usually designed with massive domain knowledge but still fail to yield high-quality solutions efficiently. In this paper, we aim to enhance the solution quality and computation efficiency for solving AGH. Particularly, we first model AGH as a multiple-fleet vehicle routing problem (VRP) with miscellaneous constraints including precedence, time windows, …

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