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Articles 841 - 870 of 294494
Full-Text Articles in Physical Sciences and Mathematics
Towards More Inclusive Ai Systems In Cities, Siew Ying Shee, Orlando Woods
Towards More Inclusive Ai Systems In Cities, Siew Ying Shee, Orlando Woods
Research Collection School of Social Sciences
Artificial Intelligence (AI) is increasingly embedded in urban infrastructures and governance, shaping how people, spaces, and futures are classified, prioritised, and managed. Yet, most AI systems are developed within a narrow set of linguistic and geopolitical contexts and exported globally, embedding particular epistemic assumptions into diverse urban environments. Even where formal inclusion metrics are met, such asymmetries can render certain populations and realities less legible within algorithmic systems. Prevailing approaches in digital inclusion—centred on fairness metrics, representation, or access—presume technologies as politically inert and bounded. Yet, the adaptive and probabilistic behaviour of contemporary AI disrupts this premise, challenging the idea …
Catalytic Synthesis Of Protoberberine Alkaloids And Their Evaluation As Selective Dopamine Receptor Ligands, Ashok Reddy Gudipally
Catalytic Synthesis Of Protoberberine Alkaloids And Their Evaluation As Selective Dopamine Receptor Ligands, Ashok Reddy Gudipally
Dissertations, Theses, and Capstone Projects
Dopamine regulates motor control, cognition, reward, motivation, and neuroendocrine signaling. Disruption of dopaminergic neurotransmission is closely linked to central nervous system disorders, including Parkinson’s disease, schizophrenia, addiction, and related neuropsychiatric conditions. Because these functions are mediated by multiple dopamine receptor subtypes with distinct roles in physiology and disease, the discovery of subtype-selective ligands remains an important goal in neuropharmacology. Within this context, protoberberine alkaloids, particularly tetrahydroprotoberberines (THPBs), are attractive molecular frameworks because they combine structural complexity with broad biological relevance, including measurable activity in CNS-related diseases. Prior work from our laboratory and others established (–)-stepholidine (1.60) as an important lead …
Bridging Data Gaps In Retinal Imaging: From Structural Domain Adaptation To Topology-Aware Synthesis, Gözde Merve Demirci
Bridging Data Gaps In Retinal Imaging: From Structural Domain Adaptation To Topology-Aware Synthesis, Gözde Merve Demirci
Dissertations, Theses, and Capstone Projects
Comprehensive visualization of the retina is essential for diagnosing and monitoring blinding diseases such as Diabetic Retinopathy and Retinopathy of Prematurity (ROP), where pathological changes often extend beyond a single field of view. Despite significant advances in automated retinal image analysis, clinical deployment remains limited by two fundamental data gaps: a structural learning gap, arising from scarce expert annotations and poor generalization across imaging domains, and a spatial coverage gap, caused by the difficulty of acquiring multi-view retinal images in fragile populations. Although these challenges are often addressed independently, this dissertation argues that they are tightly coupled: accurate, …
Potential Energy Landscape Formalism For Quantum Liquids, Yang Zhou
Potential Energy Landscape Formalism For Quantum Liquids, Yang Zhou
Dissertations, Theses, and Capstone Projects
Atomic delocalization due to nuclear quantum effects (NQE) remains poorly understood in low-temperature liquids near the glass state and during vitrification. Many liquids can be described accurately by treating their nuclei as classical particles, but this approximation fails for light elements such as He and H₂, small hydrogen-containing molecules such as water, and systems in which zero-point motion or isotope-substitution effects are important. Developing a general thermodynamic and statistical-mechanical description of such liquids has been challenging. This dissertation extends the potential energy landscape (PEL) formalism, originally developed for classical liquids and glasses, to liquids that obey quantum mechanics and exhibit …
Mapping The Water Quality Of Jamaica Bay, New York (1996-2024): Principal Component Analysis And K-Means Clustering, Sneha Srivastava
Mapping The Water Quality Of Jamaica Bay, New York (1996-2024): Principal Component Analysis And K-Means Clustering, Sneha Srivastava
Dissertations, Theses, and Capstone Projects
Jamaica Bay, located along the southeastern coast of New York City, acts as a biodiverse estuary of wetlands, meadows, and salt marsh islands. The purpose of this study is to analyze the water quality conditions of the region over time, comparing locations around the bay to identify hyperlocal features that influence larger trends in the hydrological system. Ten variables were used as water quality indicators, including total Kjeldahl nitrogen, salinity, pH, Secchi disk depth, and total phosphorus, among others, across five stations in the bay, between 1994 and 2024. After data cleaning and standardization methods were applied, principal component analysis …
Rethinking Road Racing Standards: Comparing New York Road Runners Race Results To Running Industry Standards, Jennie Coughlin
Rethinking Road Racing Standards: Comparing New York Road Runners Race Results To Running Industry Standards, Jennie Coughlin
Dissertations, Theses, and Capstone Projects
Running has undergone a third boom in participation since 2020, driven largely by people seeking fitness options that were outside and socially distanced during the COVID-19 pandemic. Social media has also allowed runners from groups that did not traditionally participate to find community. As the road racing population has expanded to include more people, some road racing industry standards have not kept up. This project assesses what the road racing community looks like and measures industry standards against the community of participants to see what changes in those standards would be needed to make them inclusive for all participants.
To …
Self-Organized Criticality In Biased Activated Random Walk, Joshua Meisel
Self-Organized Criticality In Biased Activated Random Walk, Joshua Meisel
Dissertations, Theses, and Capstone Projects
We demonstrate many of the conjectured universality and self-organized criticality (SOC) properties of the interacting particle system Activated Random Walk (ARW) in the setting of one-dimensional biased walks, as formulated for instance in Levine and Silvestri’s 2024 survey. Namely, there exists the same limiting critical state for two finite ARW models, as well as for the infinite model as the density approaches its critical value from below. Many of the desired properties hold, including heavy-tailed avalanches, but spatial correlations decay exponentially fast, a deviation from the SOC paradigm. Nonetheless, the obtained decay rate vanishes with the bias. Since the critical …
Applications Of Entanglement In Quantum Information, Nada Ali
Applications Of Entanglement In Quantum Information, Nada Ali
Dissertations, Theses, and Capstone Projects
Entanglement is the resource that most sharply distinguishes quantum information processing from its classical counterpart, and this thesis examines it from two complementary directions: how it can be detected and quantified, and how it, together with the broader machinery of quantum correlations, interference, and measurement, can be put to use. We first study two simple, measurable conditions that detect bipartite entanglement, and show that the extent to which either is violated yields a lower bound on the negativity of a state. The bound is established for two qubits, extended to systems of arbitrary finite dimension, and sharpened when partial knowledge …
Behind The Score: The Influence Of Neighborhood Policy Contexts On New York Regents Exam Performance Across New York City Public High Schools, Philip J. Kovacevic
Behind The Score: The Influence Of Neighborhood Policy Contexts On New York Regents Exam Performance Across New York City Public High Schools, Philip J. Kovacevic
Dissertations, Theses, and Capstone Projects
This study used a two-level hierarchical linear model (HLM) to test whether New York City neighborhood zoning and land-use characteristics independently predict school-level performance on the New York State Regents Examinations, after controlling for school demographic and organizational characteristics, and Regents mean scores, both drawn from the NYC DOE's Regents Exam Results file (NYC Public Schools InfoHub, 2024). Using NYC Primary Land Use Tax Lot Output (PLUTO) 2025 data, a Neighborhood Educational Quality (NEQ) index was built for each of the city’s 42 community districts by combining the commercial floor area ratio (CommFAR) and the proportion of lots zoned residential …
Cavity Optomechanics Via Mechanically Induced Coupling Of Optical Modes, Satyam S. Jha
Cavity Optomechanics Via Mechanically Induced Coupling Of Optical Modes, Satyam S. Jha
Dissertations, Theses, and Capstone Projects
This thesis introduces a transverse, symmetry-breaking mode of optomechanical coupling that departs from the conventional dispersive and dissipative interactions, taking its motivating platform from whispering-gallery-mode (WGM) resonators, where a mechanical displacement lifts the near-degeneracy of azimuthal mode pairs and couples them. After reviewing the standard optomechanical model and the sideband-cooling phenomenology it underlies, we derive the Hamiltonian for the transverse-coupling system and first study its Hamiltonian dynamics, without drive or dissipation. Recast in terms of Schwinger pseudospin operators, the model exhibits a Hamiltonian Hopf bifurcation separating stable and unstable dynamical regimes. In the stable regime, the mechanical nonlinearity permits controlled …
Quaternionic Analogues Of Zagier’S Sums Of Binary Quadratic Forms, Ajmain A. Yamin
Quaternionic Analogues Of Zagier’S Sums Of Binary Quadratic Forms, Ajmain A. Yamin
Dissertations, Theses, and Capstone Projects
Let K be the real numbers R, complex numbers C or quaternions H. Let O ⊂ K be a full rank discrete Euclidean subring of K. We investigate certain functions F_{k,Δ,O} : K → R indexed by positive integers k, Δ with k odd. When K = R or C, these functions recover Zagier’s sums of binary quadratic forms and Karabulut’s sums of binary Hermitian forms respectively. When K = H, the F_{k,Δ,O} functions are new quaternionic analogues of Zagier's sums whose definition involves sums of binary Hamiltonian forms as defined by Parkkonen-Paulin.
We prove that for fixed "weight" k …
Editorial For The Special Issue “Advances And Applications Of Polymer Gels For Subsurface Energy And Storage”, Baojun Bai, Jingyang Pu
Editorial For The Special Issue “Advances And Applications Of Polymer Gels For Subsurface Energy And Storage”, Baojun Bai, Jingyang Pu
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
Polymer gels are essential functional materials for subsurface energy operations, playing a critical role in conformance control, fluid diversion, hydraulic fracturing, and leakage mitigation. As reservoirs become increasingly complex and the demand for sustainable energy grows, continued innovation in gel technologies is crucial. This editorial introduces a Special Issue titled "Advances and Applications of Polymer Gels for Subsurface Energy and Storage," which compiles seven original research articles exploring recent developments in gel synthesis, characterization, and applications. The featured studies highlight the versatility of polymer gels, including nanoparticle-reinforced composites, foam–gel hybrids, recrosslinkable preformed particle gels, and advanced fracturing fluids. The contributions …
Collecting Holistic Evidence On Agroecology Performance To Accelerate Sustainable Food System Transitions, Sarah K. Jones, Andrea Cecilia Sánchez, Chris Dickens, Matthias S. Geck, Chaturangi Wickramaratne, Veronique Alary, Peter Bolo, Dennis Junior Choruma, Somphasith Douangsavanh, Modou Gueye Fall, Gatien Falconnier, Shweta Gupta, Chris Kettle, Smitha Krishnan, Sylvia Nyawira, Guillermo Orjuela-Ramirez, Boko Michel Orounladji, Piedad Pareja, Telma Sibanda, Christine Lamanna
Collecting Holistic Evidence On Agroecology Performance To Accelerate Sustainable Food System Transitions, Sarah K. Jones, Andrea Cecilia Sánchez, Chris Dickens, Matthias S. Geck, Chaturangi Wickramaratne, Veronique Alary, Peter Bolo, Dennis Junior Choruma, Somphasith Douangsavanh, Modou Gueye Fall, Gatien Falconnier, Shweta Gupta, Chris Kettle, Smitha Krishnan, Sylvia Nyawira, Guillermo Orjuela-Ramirez, Boko Michel Orounladji, Piedad Pareja, Telma Sibanda, Christine Lamanna
All Peer-Reviewed Publications
A growing body of research shows the potential of agroecology for enabling a shift to planet-friendly and socially just agrifood systems through context-specific transition pathways. We conduct a scoping review to identify and evaluate the potential of 42 existing agroecology adherence and/or agricultural performance assessment tools to generate credible, legitimate, salient and transferable evidence to inform these transitions. Results show that while multiple relevant tools exist, each of them can be strengthened in at least one area. While most tools are transferable (low time and resource requirements) and have legitimacy (open access with transparent methods), tools have variable saliency (holistic …
Machine Learning-Enabled Chemical Ecology For Integrated Pest Management: From Volatiles To Field Applications, Steve B.S. Baleba, Victor O. Omondi, Pascal Aigbedion-Atalor, Emmanuel Peter, Souleymane Diallo, Komi Mensah Agboka
Machine Learning-Enabled Chemical Ecology For Integrated Pest Management: From Volatiles To Field Applications, Steve B.S. Baleba, Victor O. Omondi, Pascal Aigbedion-Atalor, Emmanuel Peter, Souleymane Diallo, Komi Mensah Agboka
All Peer-Reviewed Publications
Machine learning is transforming chemical ecology by accelerating the discovery and deployment of semiochemical-based tools for precision pest management. These advances are particularly important in the face of climate change, pesticide resistance, and the growing need for sustainable agricultural intensification. This review synthesizes how machine learning can be applied across the semiochemical discovery and implementation pipeline, from chemical signal detection to field deployment and decision support for integrated pest management. We review major machine learning approaches and demonstrate how they extract biologically relevant information from high-dimensional chemical, electrophysiological, behavioral, sensor, and field datasets. These methods accelerate semiochemical discovery, prioritize candidate …
Pseudo-Traveling Waves And Bumps In Quantum And Classical Hierarchical Cellular Neural Networks, Wilson A. Zuniga-Galindo, B. A. Zambrano-Luna, Chayapuntika Indoung
Pseudo-Traveling Waves And Bumps In Quantum And Classical Hierarchical Cellular Neural Networks, Wilson A. Zuniga-Galindo, B. A. Zambrano-Luna, Chayapuntika Indoung
School of Mathematical & Statistical Sciences Faculty Publications
We study the existence of pseudo-traveling waves and bump solutions for two classes of hierarchical cellular neural networks (CNNs) defined over the ring of p-adic integers Zp. The first type is a p-adic CNN described by a reaction-diffusion equation, while the second type is its quantum analog obtained via Wick rotation. The p-adic CNNs are hierarchical versions of the classical Chua-Yang CNNs; these networks have a tree-like hierarchical architecture with infinitely many cells and hidden layers. The states are governed by integro-differential equations on Zp. The p-adic traveling waves behave fundamentally differently from their Archimedean counterparts. A traveling wave restricted …
Soil Organic Carbon Stocks And Sequestration Rates In Western Australia’S Mangroves, Enric Gomis, Cristian Salinas, Madison Williams-Hoffman, Nicole E. Said, Marta Sánchez Alarcón, Connor Gorham, Axel Werner, Paul S. Lavery, Karina Inostroza, Tegan Davies, Pauline F. Grierson, Sharyn Hickey, Ben Radford, Enrique Ballesteros, Jeffrey J. Kelleway, Pere Masqué, Eduard Serrano, Peter I. Macreadie, Catherine E. Lovelock, Anna Lafratta, Micheli Duarte De Paula Costa, Ruth Reef, Vladimir Levchenko, Fiona Doessel, Matthew A. Hayes, Stacey M. Trevathan-Tackett, I. Noyan Yilmaz, Pawel Waryszak, Rory Crofts, Oscar Serrano
Soil Organic Carbon Stocks And Sequestration Rates In Western Australia’S Mangroves, Enric Gomis, Cristian Salinas, Madison Williams-Hoffman, Nicole E. Said, Marta Sánchez Alarcón, Connor Gorham, Axel Werner, Paul S. Lavery, Karina Inostroza, Tegan Davies, Pauline F. Grierson, Sharyn Hickey, Ben Radford, Enrique Ballesteros, Jeffrey J. Kelleway, Pere Masqué, Eduard Serrano, Peter I. Macreadie, Catherine E. Lovelock, Anna Lafratta, Micheli Duarte De Paula Costa, Ruth Reef, Vladimir Levchenko, Fiona Doessel, Matthew A. Hayes, Stacey M. Trevathan-Tackett, I. Noyan Yilmaz, Pawel Waryszak, Rory Crofts, Oscar Serrano
Research outputs 2022 to 2026
Mangroves are widely recognized for their contribution to climate change mitigation. This study provides the first comprehensive assessment of top 1-m and 30-cm soil organic carbon (OC) stocks and accumulation rates across Western Australia’s mangroves, spanning multiple bioregions, geomorphological settings, and intertidal positions. The results revealed (mean ± SE) 236 ± 13 Mg and 83 ± 4 Mg OC ha−1 in top 1-m and 30-cm soils, respectively, accumulated at 443 ± 83 and 215 ± 22 kg OC ha−1 yr−1 over the past 100 and 500 years, respectively. Mangroves across Western Australia exhibited up to 3-fold differences in top 1-m …
Allochthonous Particulate Organic Carbon In Blue Carbon Ecosystems: Implications For Accounting, Stability, And Policy, Anirban Akhand, Inés Mazarrasa, Stacey M. Trevathan-Tackett, K. M.G. Mostofa, Abhra Chanda, Hongbin Liu, Hiroshi Sakugawa, Si Liang Li, Cong Qiang Liu, Catherine E. Lovelock, Paul Lavery, Hilary Kennedy, Peter I. Macreadie
Allochthonous Particulate Organic Carbon In Blue Carbon Ecosystems: Implications For Accounting, Stability, And Policy, Anirban Akhand, Inés Mazarrasa, Stacey M. Trevathan-Tackett, K. M.G. Mostofa, Abhra Chanda, Hongbin Liu, Hiroshi Sakugawa, Si Liang Li, Cong Qiang Liu, Catherine E. Lovelock, Paul Lavery, Hilary Kennedy, Peter I. Macreadie
Research outputs 2022 to 2026
Blue carbon ecosystems (BCEs) store a significant amount of organic carbon (OC) in their soils, including OC sequestered by other ecosystems and transported into these ecosystems, referred to as allochthonous OC. This study reviews the state-of-the-art knowledge on the abundance and sources (including still unexplored ones) of allochthonous particulate organic carbon (POC) and reviews the ways allochthonous POC is managed under the current blue carbon policy frameworks for carbon benefits accounting in blue carbon restoration and conservation projects. Based on a review of 102 studies, we find that 56 ± 25% of the soil organic carbon (SOC) deposits in BCEs …
Generalizations Of The Dirichlet Problem For Bianalytic Functions, William L. Blair
Generalizations Of The Dirichlet Problem For Bianalytic Functions, William L. Blair
Math Faculty Publications and Presentations
We prove the Dirichlet problem for second-order iterated Vekua equations, a natural generalization of the Bitsadze equation, is well-posed when the boundary condition is defined as a product of an exponential function and a polynomial on a non-degenerate conic that is not a circumference. Also, we extend this result, as well as other related results for the Dirichlet problem for polyanalytic and generalized analytic functions from the literature, to their analogues for bicomplex differential equations.
Investigating The Impact Of Outreach Programmes On Second Level Students In Formal And Informal Computer Science Education In Ireland, Karen Nolan
Doctoral
Computer Science (CS) education at second-level in Ireland has undergone significant development, including the introduction of the Leaving Certificate Computer Science (LCCS). However, the existing literature examined demonstrated that access to and participation in CS education is uneven, resulting in many students having limited exposure CS at second-level before making educational choices. At the same time, students who elect to study LCCS require appropriate support as they engage with programming and other aspects of a relatively new formal curriculum. This thesis investigates the function of school-based CS outreach in helping students at these various phases of their second-level CS education …
Toward Equitable Energy Futures: The Influence Of Digital Government And Financial Development On Clean Energy Justice, Martin Spraggon, Muhammad Hafeez, Sana Ullah, Chanyanan Somthawinpongsai, Zurul Aisya Osman, Sidra Sohail
Toward Equitable Energy Futures: The Influence Of Digital Government And Financial Development On Clean Energy Justice, Martin Spraggon, Muhammad Hafeez, Sana Ullah, Chanyanan Somthawinpongsai, Zurul Aisya Osman, Sidra Sohail
All Works
Fossil fuel energy is the largest source of carbon emissions and the main driver of climate change and global warming. Therefore, the world is switching towards clean and green energy sources as an alternative to fossil fuel-based energy sources. Nevertheless, the equitable distribution of clean energy resources in urban and rural areas among every segment of society has become a concern for policymakers. Thus, urban-rural clean energy justice is an investigation topic that needs our attention. In this analysis, our main focus is on investigating the influence of financial development and digital government on clean energy justice using an advanced …
Sea-Level Rise And Regional Economic Adjustment On The U.S. Gulf Coast, Md A M Hasif, Juhee Lee, Robin A. Choudhury
Sea-Level Rise And Regional Economic Adjustment On The U.S. Gulf Coast, Md A M Hasif, Juhee Lee, Robin A. Choudhury
School of Earth, Environmental, & Marine Sciences Faculty Publications
Sea-level rise (SLR) poses escalating risks to the U.S. Gulf Coast, where critical industries, infrastructure, and populations are concentrated in low-lying areas. This study estimates the short- and long-run economic effects of SLR using a panel autoregressive distributed lag-pooled mean group framework applied to county-level data from 26 coastal counties across five Gulf Coast states from 2005 to 2021. Over this period, mean sea level increased by approximately 11 cm on average across counties, with cumulative changes ranging from about 4 cm to over 24 cm and substantial cross-county variation, providing a meaningful empirical setting for identifying economic adjustment. We …
Re: Butte Priority Soils Operable Unit (Bpsou) Final Bpsou Unreclaimed Sites Anderson Shaft Remedial Action Work Plan (Rawp) Request For Change Ur-2026-Ra-01, Mike Mcanulty
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Revised Draft Final Quarterly Operations And Maintenance Report: Butte Treatment Lagoon System – First Quarter 2026, Pioneer Technical Services, Inc.
Revised Draft Final Quarterly Operations And Maintenance Report: Butte Treatment Lagoon System – First Quarter 2026, Pioneer Technical Services, Inc.
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Butte Priority Soils Operable Unit (Bpsou) Final Bpsou Unreclaimed Sites Anderson Shaft Remedial Action Work Plan (Rawp) Request For Change Ur-2026-Ra-01, Mike Mcanulty
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Remote Sensing Integrated Modeling Of Fall Armyworm Parasitoid Interactions In Africa Using Fractional Differential Equations, Marian Adan, Steeven Belvinos Affognon, Henri E.Z. Tonnang, Klaus Greve, Christian Borgemeister, Georg Goergen
Remote Sensing Integrated Modeling Of Fall Armyworm Parasitoid Interactions In Africa Using Fractional Differential Equations, Marian Adan, Steeven Belvinos Affognon, Henri E.Z. Tonnang, Klaus Greve, Christian Borgemeister, Georg Goergen
All Peer-Reviewed Publications
The invasion of fall armyworm (Spodoptera frugiperda; FAW) into Africa poses a major threat to agricultural systems, particularly maize production, necessitating effective biological control strategies. This study presents an ecological modelling framework that integrates temperature data with fractional differential equations (FDEs) to investigate interactions between FAW and its parasitoid natural enemies. By incorporating temperature-driven effects on life-history traits and ecological memory dynamics, the model captures key features of host–parasitoid interactions under variable environmental conditions. Equilibrium states corresponding to FAW extinction, parasitoid extinction, and coexistence were analytically derived, and sensitivity analysis of the FAW reproduction number highlighted its central role in …
Constrained Multiview Contrastive Learning For Jointly Supervised Representation Learning, Siyuan Dai, Kai Ye, Kun Zhao, Yang Du, Haoteng Tang, Liang Zhan
Constrained Multiview Contrastive Learning For Jointly Supervised Representation Learning, Siyuan Dai, Kai Ye, Kun Zhao, Yang Du, Haoteng Tang, Liang Zhan
Computer Science Faculty Publications
Purpose
To develop a mutual information (MI)–based mechanism for quantifying representation distance, and to introduce a constrained multiview learning paradigm that dynamically re-ranks and selects sample views, thereby improving contrastive representation learning for lung lesion segmentation on CT images—addressing the difficulty of measuring distances in high-dimensional feature spaces and the impracticality of constructing large positive–negative sample banks in the medical domain.Materials and Methods
The proposed framework, termed MIMIC (Mutual Information-based constrained Multi-view Contrastive learning), generates multiple frequency-domain views of CT images and performs a dynamic MI-based representation re-ranking and selection process to improve the quality of positive and negative …Ecu-Malnett V2, Matthew G. Gaber, Mohiuddin Ahmed, Michael N. Johnstone
Ecu-Malnett V2, Matthew G. Gaber, Mohiuddin Ahmed, Michael N. Johnstone
Research Datasets
ECU-MALNETT (ECU MALware NETwork Traffic) is a real world, reproducible dataset of labeled benign and malicious network flows built from the Peekaboo execution corpus. Peekaboo runs evasive malware with dynamic binary instrumentation and records raw host-level PCAPs while granting full Internet access, yielding noisy, real-world captures with background OS activity and concurrent processes. To derive trustworthy labels from these traces, we apply Construct, a baseline aware, zero-trust labeling framework. Construct first ingests a baseline capture to establish reference sets (DNS qnames, HTTP hosts, TLS SNIs, and socket endpoints) and grows a conservative benign IP pool only via whitelisted DNS resolutions. …
From Green Presence To Perceived Greenery: Everyday Mobility And Perceptual Availability In Singapore, Ziheng Zeng, Sonny Rosenthal, Orlando Woods
From Green Presence To Perceived Greenery: Everyday Mobility And Perceptual Availability In Singapore, Ziheng Zeng, Sonny Rosenthal, Orlando Woods
Research Collection College of Integrative Studies
Urban greenery may be abundant in transit-oriented cities, yet green presence does not necessarily become perceptually available to people moving through it. This paper distinguishes green supply, perceived greenery, and green experience, and examines the step at which greenery enters awareness during travel. The study combined 21 days of ecological momentary assessment from 68 participants in Singapore, yielding 6,794 in-trip moments, and 25 route-reconstruction interviews. A satellite normalized difference vegetation index (NDVI) provided a top-down baseline of green supply, and a street-level green view index (GVI) from Google Street View (GSV), matched to 5,824 moments, provided a co-located eye-level baseline. …
The Application Of Machine Learning And Deep Learning On Demand Forecasting Across Time-Critical Industries: A Systematic Review, Asmaa Seyam, Sujith Samuel Mathew, May El Barachi, Cheng Zhang, Jun Shen
The Application Of Machine Learning And Deep Learning On Demand Forecasting Across Time-Critical Industries: A Systematic Review, Asmaa Seyam, Sujith Samuel Mathew, May El Barachi, Cheng Zhang, Jun Shen
All Works
The applications of machine learning and deep learning in demand forecasting have attracted increasing attention, as they offer remarkable predictive capabilities that help automate forecasting processes and achieve higher accuracy. While numerous review studies have examined solutions within specific industries, there is a lack of comprehensive literature review investigating these solutions across different sectors. Therefore, this study overviews machine learning and deep learning applications in demand forecasting across time-critical industries, including power, tourism, water, transportation, and food. A two-tier classification framework is proposed to categorize demand forecasting studies by both application industry and methodological architecture. In addition, the most popular …
Model-Theoretic Arguments In Philosophy, Peter Susanszky
Model-Theoretic Arguments In Philosophy, Peter Susanszky
Dissertations, Theses, and Capstone Projects
This dissertation is on model-theoretic arguments in philosophy, especially those of Quine, Davidson, and Putnam. In the first part, to ground the debate, I give a rigorous introduction to the salient parts of first-order model theory. I start the second part by giving an introduction to Quine's philosophy, and how the model-theoretic arguments fit into it. After considering how Donald Davidson adopted the Quinean lesson, I move on to Putnam's model-theoretic arguments. Putnam's spin on these model-theoretic considerations significantly departs from Quine and Davidson, while retaining many of the core ideas. Most importantly, I argue that the target of Putnam's …