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Human-Centered Approach For Resilience Assessment Of Healthcare Networks Subjected To Sequential Earthquakes, Emad Hassan, Hussam Mahmoud Nov 2024

Human-Centered Approach For Resilience Assessment Of Healthcare Networks Subjected To Sequential Earthquakes, Emad Hassan, Hussam Mahmoud

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Healthcare services are critical for community resilience and stability as their role after disastrous events is indispensable to reducing casualties and returning the community to normalcy. Sequential mainshock-aftershock events can damage hospital components, reduce utility availability, and cause multiple patient surges. No studies have been conducted to evaluate the impact of mainshock-aftershock events on healthcare resilience. Accordingly, here we investigate the impact of multiple earthquakes on the healthcare network in Shelby County, Tennessee, and determine the optimal resources needed to enhance its functionality. The functionality is estimated by combining functionality quantity and quality terms. The quantity is calculated based on …

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Circular Economy Integration In Leed: A Decade Of Materials And Resources Credit Achievement Patterns, Radwa Eissa, Islam H. El-Adaway Nov 2024

Circular Economy Integration In Leed: A Decade Of Materials And Resources Credit Achievement Patterns, Radwa Eissa, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Previous studies consistently label the Materials and Resources (MR) credit category of the Leadership in Energy and Environmental Design (LEED) as the least attainable, despite its critical role in transitioning to a circular economy (CE). To this end, a long-standing gap exists in understanding the MR credit achievement, especially in LEED v4, which has been in use for nearly over a decade. This paper evaluates the level of CE integration in LEED v4 across 971 US-based certified projects. The study comprehensively analyzed the projects achievement patterns of the five MR credits: Building Life Cycle Impact Reduction (C1), Environmental Product Declarations …

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Anti-Corrosion Performance Of Magnesium Potassium Phosphate Cement Coating On Steel Reinforcement: The Effect Of Boric Acid, Fan Zhang, Jihui Qin, Kangyi Cai, John J. Myers, Hongyan Ma Nov 2024

Anti-Corrosion Performance Of Magnesium Potassium Phosphate Cement Coating On Steel Reinforcement: The Effect Of Boric Acid, Fan Zhang, Jihui Qin, Kangyi Cai, John J. Myers, Hongyan Ma

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

It has recently been found that magnesium potassium phosphate cement (MKPC) paste coating applied on the surface of steel reinforcement can effectively retard the onset of corrosion and suppress corrosion reactions. However, the fast-setting nature of MKPC—which is a merit in repair—can be problematic in a practical engineering process of coating the steel reinforcement with MKPC paste. To address this problem, boric acid (H3BO3) was added as a retarder in an MKPC formulation to prolong the setting time. This work investigated the impact of boric acid (at 5% by weight of MgO) on the anti-corrosion performance …

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Temperature Effect On The Properties And Response Of Composite Materials And Plates, Victor Birman Nov 2024

Temperature Effect On The Properties And Response Of Composite Materials And Plates, Victor Birman

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The paper illustrates the effect of temperature on composite material properties and its influence on the response of composite plates. Two composites considered include laminae with uniaxially oriented and with in-plane randomly oriented fibers. Analytical solutions are presented for a uniformly heated large-aspect-ratio plate deforming into a cylindrical surface. The solutions are demonstrated for thermal buckling and natural frequencies for the cases of controlled loading and controlled displacements. Micromechanical residual and lifetime thermally induced stresses at the interface of fibers and matrix are assessed to predict a possible onset of local damage after the curing and during lifetime. The material …

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Biocargos: Capture And Release Gels For Room Temperature Cell Storage., Justin Jacobson Nov 2024

Biocargos: Capture And Release Gels For Room Temperature Cell Storage., Justin Jacobson

Electronic Theses and Dissertations

Currently, cryovials on dry ice or liquid nitrogen vapor transportation vessels are primary ways utilized to transport mammalian cells from one location to another. Due to the safety concerns of dry ice and liquid nitrogen, associated costly shipping charges, and limitations of proper packaging and labeling of materials, these conventional shipping techniques are unacceptable. It is urgent to develop a safe and environmentally friendly protocol to preserve and ship the biological samples from one place to another. In this research, a method was developed for an ecofriendly and safe protocol to preserve cancer cells. The cell viability of cell line …

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The Use Of Peracetic Acid And The Advanced Oxidation Process In Water Purification., Spencer Shipman Nov 2024

The Use Of Peracetic Acid And The Advanced Oxidation Process In Water Purification., Spencer Shipman

Electronic Theses and Dissertations

The Next Round Brewing project was a project that sought to use treated wastewater to make potable drinking water using peracetic acid (PAA) and the advanced oxidation process and break the stigma around reclaimed water. In experiments, PAA was an efficient biocide which reduced the level of pathogens to within EPA standards. When PAA was coupled with the advanced oxidation process all organic matter was also reduced to within acceptable levels, and no biocide was left over in the final product, meaning PAA properly dissociated into harmless byproducts. A series of experiments are presented that vary concentrations of PAA, effluent …

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The Effects Of Wildfires On The Mental And Physical Health Of School-Age Children In North America: A Scoping Review, Sarah Oerther, Sarah Manspeaker, Alison Wix, Daniel Oerther, Carmen Marsit Nov 2024

The Effects Of Wildfires On The Mental And Physical Health Of School-Age Children In North America: A Scoping Review, Sarah Oerther, Sarah Manspeaker, Alison Wix, Daniel Oerther, Carmen Marsit

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Background: Wildfires are occurring more often and with greater intensity, leading to longer and harsher fire seasons. As a result, children are more frequently exposed to wildfire smoke, which increases their risk of mental and physical health effects. Purpose: The purpose of our scoping review is to explore the current literature on what is known about the direct and indirect impacts of wildfires on the mental and physical health of school-age children in North America (5 to 18-year-olds). Methods: A health sciences librarian-assisted literature search, with input from the research team, was performed. Results: A total of 16 studies were …

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Causal Neuro-Symbolic Ai For Root Cause Analysis In Smart Manufacturing, Utkarshani Jaimini, Cory Henson, Amit Sheth Nov 2024

Causal Neuro-Symbolic Ai For Root Cause Analysis In Smart Manufacturing, Utkarshani Jaimini, Cory Henson, Amit Sheth

Publications

Root cause analysis is the process of investigating the cause of a failure and providing measures to prevent future failures. It is an active area of research due to the complexities in manufacturing production lines and the vast amount of data that requires manual inspection. We present a combined approach of causal neuro-symbolic AI for root cause analysis to identify failures in smart manufacturing production lines. We have used data from an industry-grade rocket assembly line and a simulation package to demonstrate the effectiveness and relevance of our approach.

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Ontology Design Metapattern For Relationtype Role Composition, Utkarshani Jaimini, Ruwan Wickramarachchi, Cory Henson, Amit Sheth Nov 2024

Ontology Design Metapattern For Relationtype Role Composition, Utkarshani Jaimini, Ruwan Wickramarachchi, Cory Henson, Amit Sheth

Publications

RelationType is a metapattern that specifies a property in a knowledge graph that directly links the head of a triple with the type of the tail. This metapattern is useful for knowledge graph link prediction tasks, specifically when one wants to predict the type of a linked entity rather than the entity instance itself. The RelationType metapattern serves as a template for future extensions of an ontology with more fine-grained domain information.

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Causal Knowledge Graph For Scene Understanding In Autonomous Driving, Utkarshani Jaimini, Cory Henson, Amit Sheth Nov 2024

Causal Knowledge Graph For Scene Understanding In Autonomous Driving, Utkarshani Jaimini, Cory Henson, Amit Sheth

Publications

The current approaches to autonomous driving focus on learning from observation or simulated data. These approaches are based on correlations rather than causation. For safety-critical applications, like autonomous driving, it’s important to represent causal dependencies among variables in addition to the domain knowledge expressed in a knowledge graph. This will allow for a better understanding of causation during scenarios that have not been observed, such as malfunctions or accidents. The causal knowledge graph, coupled with domain knowledge, demonstrates how autonomous driving scenes can be represented, learned, and explained using counterfactual and intervention reasoning to infer and understand the behavior of …

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Neutrosophic Logic-Based Crop Yield Prediction And Risk Assessment Using Least Squares Regression, M. Srikanth, R.N.V. Jagan Mohan, M. Chandra Naik Nov 2024

Neutrosophic Logic-Based Crop Yield Prediction And Risk Assessment Using Least Squares Regression, M. Srikanth, R.N.V. Jagan Mohan, M. Chandra Naik

Neutrosophic Systems with Applications

Agriculture faces significant challenges due to climate change and unpredictable environmental factors, which impact crop yields and threaten food security. This study proposes a novel approach to crop yield prediction and risk assessment using neutrosophic logic and least squares regression. By integrating these methods, we aim to improve accuracy in predicting crop losses under uncertain conditions. The model classifies crops based on profitability and environmental risks, utilizing the independence test to evaluate the relationships between crop attributes. Our approach leverages deep learning techniques, such as restricted Boltzmann machines (RBM), to enhance the analysis of crop data and provide farmers with …

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Establishing A Perinatal Medical-Legal Partnership To Address The Health-Harming Legal Needs Of Pregnant And Postpartum Birthing People, Loral Patchen, Roxana Richardson, Lisa Kessler, Deborah Perry, Kimberly Martinez, Vicki W. Girard Nov 2024

Establishing A Perinatal Medical-Legal Partnership To Address The Health-Harming Legal Needs Of Pregnant And Postpartum Birthing People, Loral Patchen, Roxana Richardson, Lisa Kessler, Deborah Perry, Kimberly Martinez, Vicki W. Girard

Georgetown Law Faculty Publications and Other Works

This Report from the Field chronicles the establishment of Georgetown University’s Perinatal Legal Assistance and Wellbeing Project, a medical-legal partnership in Washington, D.C. It describes foundational steps, implementation strategies, and lessons learned, and reflects on impacts of addressing the unmet legal needs of birthing individuals.

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Judges In Their Own Cases: Biblical Kings And Supreme Court Justices, Joshua Segev Nov 2024

Judges In Their Own Cases: Biblical Kings And Supreme Court Justices, Joshua Segev

Touro Law Review

Allegations that the justices of the United States Supreme Court are judges in their own cases and that they judge themselves leniently are common. These allegations are often accompanied by an association with kings, queens, and monarchies, accountable to no one but their own divine authority. This Article took this association seriously and used the biblical story of prophet Nathan's rebuke of King David for his sin towards Bathsheba and Uriah to explain the problems, tensions, and conflicting considerations of the contemporary recusal doctrine of the United States Supreme Court. This biblical judicial tale has two possible conclusions, depending on …

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The Danger Of Silence: The Negative Effect Of Supreme Court Hesitance To Establish A Bright-Line Rule For Determining Patent Subject Matter Eligibility, Amber N. Roibu Nov 2024

The Danger Of Silence: The Negative Effect Of Supreme Court Hesitance To Establish A Bright-Line Rule For Determining Patent Subject Matter Eligibility, Amber N. Roibu

Touro Law Review

Ambiguity surrounding the interpretation of 35 U.S.C. § 101 and the ultimate application of the Alice/Mayo standard for determining patent subject matter eligibility has long plagued the courts, practitioners, and USPTO examiners alike. Maintaining a standard that leads to sheer confusion and, as a result, inconsistent rulings severely muddles the ultimate goal of patent law, to promote innovation. The Supreme Court has been presented with ample opportunities to address these issues, with the Solicitor General consistently recommending that it hear cases that deal with patent-eligibility debates. Nonetheless, the Supreme Court's continued hesitancy to grant certiorari on these cases only further …

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Why The United States Should Change Its Standards For Food Additives, Sara Smith Nov 2024

Why The United States Should Change Its Standards For Food Additives, Sara Smith

Touro Law Review

Processed food products sold in the United States are vastly different than those in Europe, often containing unnecessary and potentially dangerous additives. Recently, food consumer advocacy groups and reporters are bringing attention to these differences, thereby raising awareness of the poor processed food quality in the United States. The United States should take a new and improved method to food safety that mirrors the European Union’s approach. This Note will compare the differences between food additives in the United States and Europe, and further, will propose solutions to increase regulation on food additives in the United States.

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Mitigating Operational Greenhouse Gas Emissions In Ageing Residential Buildings Using An Urban Digital Twin Dashboard, Pradeep Alva, Martín Mosteiro-Romero, Clayton Miller, Rudi Stouffs Nov 2024

Mitigating Operational Greenhouse Gas Emissions In Ageing Residential Buildings Using An Urban Digital Twin Dashboard, Pradeep Alva, Martín Mosteiro-Romero, Clayton Miller, Rudi Stouffs

Research Collection College of Integrative Studies

With the increasing stock of ageing infrastructure and resource constraints in Singapore, related risks and carbon emissions can be mitigated through long-term resilience planning, automated building inspection, and effective maintenance. Sustainable actions are needed to maintain Singapore's ageing infrastructure. Hence, a state-of-the-art control and management system is required in the form of smart city digital tools. We introduce an Urban Digital Twin (UDT)—GHG App for decision-makers in Singapore's operational building greenhouse gas (GHG) emission mitigation and decarbonisation initiatives. Based on multiple-criteria decision analysis (MCDA), a Potential for Intervention (PFI) map was created to rejuvenate the building system. Decision-makers can use …

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A Dynamic Urban Digital Twin Integrating Longitudinal Thermal Imagery For Microclimate Studies, Vasantha Ramani, Marcel Ignatius, Joie Lim, Filip Biljecki, Clayton Miller Nov 2024

A Dynamic Urban Digital Twin Integrating Longitudinal Thermal Imagery For Microclimate Studies, Vasantha Ramani, Marcel Ignatius, Joie Lim, Filip Biljecki, Clayton Miller

Research Collection College of Integrative Studies

Recently, the concept of a digital twin for the built environment has received significant attention due to its potential benefits to urban planners, engineers, and designers. The development of tools that aid in integrating real-world physical systems with digital capabilities is essential for advancing digital twin technology. In this work, we present one such digital twin tool that integrates the longitudinal thermal envelope data of buildings on the campus of the National University of Singapore with a virtual 3D model. Thermal images of the buildings were captured using a neighborhood-scale infrared observatory for a few months. The temperature profile of …

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From Personal Comfort To District Performance: Using Smartwatch And Wifi Data For Occupant-Driven Operation, Martín Mosteiro-Romero, Matias Quintana, Clayton Miller, Rudi Stouffs Nov 2024

From Personal Comfort To District Performance: Using Smartwatch And Wifi Data For Occupant-Driven Operation, Martín Mosteiro-Romero, Matias Quintana, Clayton Miller, Rudi Stouffs

Research Collection College of Integrative Studies

This work proposes the use of a data-driven, agent-based model of building occupants’ activities and thermal comfort in an urban university campus in order to assess how district operation strategies can be leveraged to support the transition to flexible work arrangements. The results show that when users are given the flexibility to pursue more comfortable workspaces, they are still comfortable only 58% of the time.

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Unlocking College Potential: The Role Of Student Expectations And Non-Cognitive Skills In College Success, Gema Zamarro, Malachi Nichols, Julie R. Trivitt, Rian Djita Nov 2024

Unlocking College Potential: The Role Of Student Expectations And Non-Cognitive Skills In College Success, Gema Zamarro, Malachi Nichols, Julie R. Trivitt, Rian Djita

Education Reform Faculty and Graduate Students Publications

Attending college is a significant human capital investment but only about 60% of those who start college will have a completed degree six years later. This makes identifying the skills associated with college success an important policy concern. We surveyed over 1,100 entering college freshmen, majoring in business and engineering at a public university in the US, and combined this information with administrative data to create a comprehensive data set that, in addition to the usual academic performance data, cognitive ability measures, and demographics, also included measures of non-cognitive skills, personality traits, student expectations about college success and performance at …

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Enhancedbert: A Python Software Tailored For Arabic Word Sense Disambiguation, Sanaa Kaddoura, Reem Nassar Nov 2024

Enhancedbert: A Python Software Tailored For Arabic Word Sense Disambiguation, Sanaa Kaddoura, Reem Nassar

All Works

EnhancedBERT is a software framework designed to disambiguate Arabic polysemous terms using advanced natural language processing techniques. It integrates transformer architectures with ensemble methods to achieve high performance in understanding and processing Arabic text. The framework provides a flexible pipeline that can be directly utilized or fine-tuned according to specific needs. EnhancedBERT stands out for its ease of use, leveraging transformer-based models combined with ensemble strategies to provide superior contextual understanding. This contextual awareness makes it an invaluable tool for researchers and practitioners tackling complexities in Arabic language processing.

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The Role Of Scribble In Activating The Sonic Hedgehog (Shh) Pathway And Its Role In The Progression Of Shh-Medulloblastoma, Jingwen Zhu Nov 2024

The Role Of Scribble In Activating The Sonic Hedgehog (Shh) Pathway And Its Role In The Progression Of Shh-Medulloblastoma, Jingwen Zhu

Alternative Theses and Dissertations (AETDs)

Our current knowledge of regulators in vertebrates’ Hedgehog (HH) pathway is incomplete. Gaining a better understanding of HH pathway components is appealing due to the key role of the Sonic Hedgehog (SHH) pathway in modulating the developmental proliferation of granule neuron progenitors (GNPs) in the cerebellum. Aberrant activation of SHH pathway in GNPs promotes the formation of SHH-Medulloblastoma (SHH-MB), a common pediatric brain tumor. Though SHH-MB is genetically understood, current therapies are ineffective. Recently, we identified a scaffold protein, Scribble (Scrib), as a novel interactor of our previously identified SHH pathway regulator—Abcc4. Scrib’s reported expression in the brain also suggested …

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Uncovering Merchants’ Willingness To Wait In On-Demand Food Delivery Markets, Jian Liang, Ya Zhao, Hai Wang, Zuopeng Xiao, Jintao Ke Nov 2024

Uncovering Merchants’ Willingness To Wait In On-Demand Food Delivery Markets, Jian Liang, Ya Zhao, Hai Wang, Zuopeng Xiao, Jintao Ke

Research Collection School Of Computing and Information Systems

While traditional on-demand food delivery services help restaurants reach more customers and enable doorstep deliveries, they also come with drawbacks, such as high commission fees and limited control over the delivery process. White-label food delivery services have emerged as an alternative, ready-to-use platform for restaurants to arrange delivery for customer orders received through their applications or websites, without the constraints imposed by traditional on-demand food delivery platforms or the need to develop an in-house delivery operation. Although several studies have investigated consumer behavior when using traditional on-demand food delivery services, there is limited research on merchants’ behavior when adopting white-label …

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Badfl: Backdoor Attack Defense In Federated Learning From Local Model Perspective, Haiyan Zhang, Xinghua Li, Mengfan Xu, Ximeng Liu, Tong Wu, Jian Weng, Robert H. Deng Nov 2024

Badfl: Backdoor Attack Defense In Federated Learning From Local Model Perspective, Haiyan Zhang, Xinghua Li, Mengfan Xu, Ximeng Liu, Tong Wu, Jian Weng, Robert H. Deng

Research Collection School Of Computing and Information Systems

There is substantial attention to federated learning with its ability to train a powerful global model collaboratively while protecting data privacy. Despite its many advantages, federated learning is vulnerable to backdoor attacks, where an adversary injects malicious weights into the global model, making the global model's targeted predictions incorrect. Existing defenses based on identifying and eliminating malicious weights ignore the similarity variation of the local weights during iterations in the malicious model detection and the presence of benign weights in the malicious model during the malicious local weight elimination, resulting in a poor defense and a degradation of global model …

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Don’T Just Say “I Don’T Know”! Self-Aligning Large Language Models For Responding To Unknown Questions With Explanations, Yang Deng, Yong Zhao, Moxin Li, See-Kiong Ng, Tat-Seng Chua Nov 2024

Don’T Just Say “I Don’T Know”! Self-Aligning Large Language Models For Responding To Unknown Questions With Explanations, Yang Deng, Yong Zhao, Moxin Li, See-Kiong Ng, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Despite the remarkable abilities of Large Language Models (LLMs) to answer questions, they often display a considerable level of overconfidence even when the question does not have a definitive answer. To avoid providing hallucinated answers to these unknown questions, existing studies typically investigate approaches to refusing to answer these questions. In this work, we propose a novel and scalable self-alignment method to utilize the LLM itself to enhance its response-ability to different types of unknown questions, being capable of not only refusing to answer but also providing explanation to the unanswerability of unknown questions. Specifically, the Self-Align method first employ …

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A Survey Of Ontology Expansion For Conversational Understanding, Jinggui Liang, Yuxia Wu, Yuan Fang, Hao Fei, Lizi Liao Nov 2024

A Survey Of Ontology Expansion For Conversational Understanding, Jinggui Liang, Yuxia Wu, Yuan Fang, Hao Fei, Lizi Liao

Research Collection School Of Computing and Information Systems

In the rapidly evolving field of conversational AI, Ontology Expansion (OnExp) is crucial for enhancing the adaptability and robustness of conversational agents. Traditional models rely on static, predefined ontologies, limiting their ability to handle new and unforeseen user needs. This survey paper provides a comprehensive review of the state-of-the-art techniques in OnExp for conversational understanding. It categorizes the existing literature into three main areas: (1) New Intent Discovery, (2) New Slot-Value Discovery, and (3) Joint OnExp. By examining the methodologies, benchmarks, and challenges associated with these areas, we highlight several emerging frontiers in OnExp to improve agent performance in real-world …

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Navigating Weight Prediction With Diet Diary, Yinxuan Gui, Bin Zhu, Jingjing Chen, Chong-Wah Ngo, Yu-Gang Jiang Nov 2024

Navigating Weight Prediction With Diet Diary, Yinxuan Gui, Bin Zhu, Jingjing Chen, Chong-Wah Ngo, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Current research in food analysis primarily concentrates on tasks such as food recognition, recipe retrieval and nutrition estimation from a single image. Nevertheless, there is a significant gap in exploring the impact of food intake on physiological indicators (e.g., weight) over time. This paper addresses this gap by introducing the DietDiary dataset, which encompasses daily dietary diaries and corresponding weight measurements of real users. Furthermore, we propose a novel task of weight prediction with a dietary diary that aims to leverage historical food intake and weight to predict future weights. To tackle this task, we propose a model-agnostic time series …

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Irl For Restless Multi-Armed Bandits With Applications In Maternal And Child Health, Gauri Jain, Pradeep Varakantham, Haifeng Xu, Aparna Taneja, Prashant Doshi, Milind Tambe Nov 2024

Irl For Restless Multi-Armed Bandits With Applications In Maternal And Child Health, Gauri Jain, Pradeep Varakantham, Haifeng Xu, Aparna Taneja, Prashant Doshi, Milind Tambe

Research Collection School Of Computing and Information Systems

Public health practitioners often have the goal of monitoring patients and maximizing patients’ time spent in “favorable” or healthy states while being constrained to using limited resources. Restless multi-armed bandits (RMAB) are an effective model to solve this problem as they are helpful to allocate limited resources among many agents under resource constraints, where patients behave differently depending on whether they are intervened on or not. However, RMABs assume the reward function is known. This is unrealistic in many public health settings because patients face unique challenges and it is impossible for a human to know who is most deserving …

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Defending Large Language Models Against Jailbreak Attacks Via Layer-Specific Editing, Wei Zhao, Zhe Li, Yige Li, Jun Sun, Jun Sun Nov 2024

Defending Large Language Models Against Jailbreak Attacks Via Layer-Specific Editing, Wei Zhao, Zhe Li, Yige Li, Jun Sun, Jun Sun

Research Collection School Of Computing and Information Systems

Large language models (LLMs) are increasingly being adopted in a wide range of realworld applications. Despite their impressive performance, recent studies have shown that LLMs are vulnerable to deliberately crafted adversarial prompts even when aligned via Reinforcement Learning from Human Feedback or supervised fine-tuning. While existing defense methods focus on either detecting harmful prompts or reducing the likelihood of harmful responses through various means, defending LLMs against jailbreak attacks based on the inner mechanisms of LLMs remains largely unexplored. In this work, we investigate how LLMs respond to harmful prompts and propose a novel defense method termed Layer-specific Editing (LED) …

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Adversarial Learning For Coordinate Regression Through K-Layer Penetrating Representation, Mengxi Jiang, Yulei Sui, Yunqi Lei, Xiaofei Xie, Cuihua Li, Yang Liu, Ivor W. Tsang Nov 2024

Adversarial Learning For Coordinate Regression Through K-Layer Penetrating Representation, Mengxi Jiang, Yulei Sui, Yunqi Lei, Xiaofei Xie, Cuihua Li, Yang Liu, Ivor W. Tsang

Research Collection School Of Computing and Information Systems

Adversarial attack is a crucial step when evaluating the reliability and robustness of deep neural networks (DNNs) models. Most existing attack approaches apply an end-to-end gradient update strategy to generate adversarial examples for a classification or regression problem. However, few of them consider the non-differentiable DNN models (e.g., coordinate regression model) that prevent end-to-end backpropagation resulting in the failure of gradient calculation. In this paper, we present a new adversarial example generation approach for both untargeted and targeted attacks on coordinate regression models with non-differentiable operations. The novelty of our approach lies in a k-layer penetrating representation, on which we …

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Mechanisms Of Extracellular Vesicle Uptake And Implications For The Design Of Cancer Therapeutics, Stephanie R. Jackson Cullison, Joseph P. Flemming, Kubra Karagoz, Peter J. Wermuth, Mỹ G. Mahoney Nov 2024

Mechanisms Of Extracellular Vesicle Uptake And Implications For The Design Of Cancer Therapeutics, Stephanie R. Jackson Cullison, Joseph P. Flemming, Kubra Karagoz, Peter J. Wermuth, Mỹ G. Mahoney

Department of Pharmacology, Physiology, and Cancer Biology Faculty Papers

The translation of pre-clinical anti-cancer therapies to regulatory approval has been promising, but slower than hoped. While innovative and effective treatments continue to achieve or seek approval, setbacks are often attributed to a lack of efficacy, failure to achieve clinical endpoints, and dose-limiting toxicities. Successful efforts have been characterized by the development of therapeutics designed to specifically deliver optimal and effective dosing to tumour cells while minimizing off-target toxicity. Much effort has been devoted to the rational design and application of synthetic nanoparticles to serve as targeted therapeutic delivery vehicles. Several challenges to the successful application of this modality as …

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