Digital Commons Network^™

Qura: Reinforcement Learning Based Routing For Quantum Networks, Tasdiqul Islam, Engin Arslan, Md Arifuzzaman

Computer Science Faculty Research & Creative Works

Quantum routing deals with identifying a set of quantum repeaters to use to create entanglement between distant endpoints. Previous approaches proposed shortest-path and linear programming methods to find a solution to this problem. While the shortest path approach results in suboptimal performance, linear programming takes too long to find a solution as the network size and constraints increase. In this paper, we apply Deep Q-Reinforcement Learning (DQRL) to optimize routing in quantum networks both in terms of execution time and performance. The proposed Quantum Routing Algorithm (QuRA) first chooses which request to schedule among all requests. It then determines which …

Nature-Based Solutions For Urban Resilience And Environmental Justice In Underserved Coastal Communities: A Case Study On Oakleaf Forest In Norfolk, Va, Farzaneh Soflaei, Mujde Erten-Unal, Carol L. Considine, Faeghe Borhani

Civil & Environmental Engineering Faculty Publications

Climate change and sea-level change (SLC) are intensifying flooding in U.S. coastal communities, with disproportionate impacts on Black and minority neighborhoods that face displacement, economic hardship, and heightened health risks. In Norfolk, Virginia, sea levels are projected to rise by at least 0.91 m (3 ft) by 2100, placing underserved neighborhoods such as Oakleaf Forest at particular risk. This study investigates the compounded impacts of flooding at both the building and urban scales, situating the work within the framework of the UN Sustainable Development Goals (UN SDGs). A mixed-method, community-based approach was employed, integrating literature review, field observations, and community …

Characterizing The Unique Chemical Imprint Of On-Axis, Lower-Temperature Hydrothermal Flow To The Deep Ocean (Southern East Pacific Rise, 16.5°-18.0°S), Laura E. Moore, Randelle M. Bundy, Joseph A. Resing, Scott White, Tamara Baumberger, Peter N. Sedwick, Nathaniel J. Buck, Anson M. Antriasian, Isaac Keohane, Bettina M. Sohst, Sharon L. Walker, Christopher R. German

OES Faculty Publications

In addition to high-temperature vents, lower-temperature flow (LTF) (< 300°C) is abundant along mid-ocean ridges and contributes globally-important fluxes of heat and water along with largely-unconstrained geochemical influences on the ocean. We examined the impact of on-axis LTF on the chemical composition of the overlying water column (< 40 m above seafloor) along the 16.5°-18.0°S sector of the ultrafast-spreading southern East Pacific Rise using autonomous underwater vehicle Sentry surveys and conductivity-temperature-depth rosette casts. LTF sites were typically spatially isolated from high-temperature systems and imparted unique chemical signatures to the overlying ocean. Water column samples impacted by LTF exhibited low particulate iron:sulfur ratios and high methane: total-dissolvable manganese ratios, whereas samples influenced by high-temperature venting exhibited opposite trends. We confirmed that LTF imparts a distinct and measurable chemical signature to the water column, independent from high-temperature vents. Isolated, on-axis LTF will be important to consider when assessing hydrothermal circulation impacts upon ocean biogeochemistry.

Aquatic Macrophytes As Nature-Based Solutions: Challenges And Opportunities Across Inland And Coastal Waters, Morgan Botrel, Roxane Maranger, Lindsay L. Trottier, Mathieu Cusson, Lars L. Iverson, Fanny Noisette, Christian Nozais, Katrine Turgeon, Andrea Bertolo, Thibaud André-Alphonse, Simon Bélanger, Arthur De Grandpré, Jean-Olivier Goyette, Sabine Hilt, Ladd Johnson, Valérie Langlois, Martin Laporte, Félix Lauzon, Brigitte Légaré, Anne Ola, Marie-Pomme Presne-Poissant, Matthieu Prugne, Caroline Susini, Richard Zimmerman

OES Faculty Publications

Macrophytes are foundation species whose use as nature-based solution (NbS) in aquatic ecosystems can help reduce climate change impacts while mitigating biodiversity loss. The discrepancy in research and application of macrophytes as NbS across inland and marine coastal ecosystems is an opportunity to expand the concept and learn from different approaches. We report on an initiative uniting marine and freshwater scientists that compared knowledge on macrophytes as NbS across realms, identified advances and gaps in their use, and synthesized challenges and opportunities for application. We conducted a bibliometric analysis and an expert participatory exercise around recent review papers. We reveal …

Revisiting The Life Cycle Of Margalefidinium Polykrikoides Group Iii, Eduardo Pérez-Vega, Kenneth N. Mertens, Pjotr Meyvisch, Margaret R. Mulholland

OES Faculty Publications

Dinoflagellates produce cysts as a strategy to withstand environmental stressors, with nutrient depletion generally considered a key trigger for cyst production. Resting cysts are thick-walled, typically composed of one to several layers, and characterized by a prolonged dormancy period. In contrast, pellicle cysts possess a thin, single wall and exhibit no dormancy or a markedly shorter dormancy than resting cysts of the same species. Margalefidinium polykrikoides produces pellicle and resting cysts, whereas its congener, M. fulvescens, has been shown to produce pumpkin-like structures. Using phase-contrast microscopy, time-lapse microscopy, FlowCam, and attenuated total reflection Fourier transform infrared microspectroscopy (ATR μ-FTIR), …

The Effects Of A Microplate On Plume-Ridge Interactions: Constraints From Comparing Easter And Juan Fernandez Microplates In The Eastern Pacific Ocean, Katherine Ames, Jennifer Georgen

OES Faculty Publications

This study investigates the nature of plume-ridge interactions near a tectonic microplate using mantle Bouguer anomaly (MBA) gravity calculations. The focus of this investigation is a comparison of the Easter and Juan Fernandez microplates, which are located in the eastern Pacific Ocean along the Pacific, Nazca, and Antarctic plate boundaries. The microplates have several similar characteristics, including general size, time of formation, and clockwise rotation within the larger bounding mid-ocean ridge systems. Unlike the Juan Fernandez microplate, however, the Easter microplate is located near a mantle plume (Easter/Salas y Gomez). Previously published geochemical data suggest that material from this plume …

The Lawyer Of The Future: Ethics And Identity In The Age Of Ai, David Yosifon, Michael Santoro, Isaac Nikssarian

American University Law Review

The dawn of artificial intelligence (AI) poses a fundamental challenge to the legal profession’s practical function and social identity. We argue that this challenge should be met as an opportunity to reclaim the profession’s core ethical intentions. We approach the emergence of AI as an occasion to define and safeguard what is irreducibly human in legal work. We ground our approach in the ethical imperatives set out in the American Bar Association’s Model Rules of Professional Conduct, while extending them into an invigorated framework for the AI era.

We survey the uses and ethical challenges associated with cutting-edge deployment of …

2024 Annual Operations And Maintenance Report 2024 Bres Annual Summary Report For Work Completed In Quadrant 4, Butte-Silver Bow Department Of Reclamation And Environmental Services

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Optical Nonlinearity Of A Cold Atomic Ensemble Driven By A Strong Coherent Field In A Saturation Regime, A. S. Usoltsev, L. V. Gerasimov, A. D. Manukhova, S. P. Kulik, D. V. Kupriyanov

Physics Faculty Publications

We present a microscopic analysis and evaluation of the dielectric susceptibility of a dielectric medium consisting of vector-type two-energy-level atoms, responding to a weak probe mode, when the atoms are driven by a strong coherent field. Each atom, in an environment of others, exists as a quasiparticle, further structuring the bulk medium. In a limit of dilute atomic gas, the dynamics of each atom follows the Mollow-type nonlinear excitation regime, and the medium susceptibility collectivizes the individual atomic responses to the probe mode. We outline how the collective dynamics can be interpolated up to a dense medium, and we argue …

Real-Time Isolated Asl Recognition: Evaluating Spatial-Temporal Networks And Multimodal Llms, Raga Mouni Batchu

West Chester University Graduate Theses, Dissertations, and Final Projects

This thesis investigates the deployment of high-accuracy Isolated ASL Recognition (ISLR) in resource-constrained edge environments. We train a lightweight Spatio-Temporal Attention Network (SSTAN,∼2.7 M parameters,∼10 MB) on the WLASL-100 benchmark, achieving 75.25% Top-1 and 88.24% Top-5 accuracy with 139 ms CPU-only inference. A systematic comparison against frontier multimodal LLMs (Gemini 3 Flash, Gemini 3.1 Pro, Qwen 3 VL) shows SSTAN outperforms the best LLM baseline by∼1.85×in accuracy while being 22–230×faster and up to 40×cheaper annually. The LLMs’ core limitation is a lack of fine-grained temporal perception; they impose English-language semantic priors rather than learning the articulatory distinctions that define ASL …

Investigation Of Fine-Grain Cu And Cu Alloys For Low-Temperature Hybrid Bonding Applications, Sarabjot Singh

Electronic Theses & Dissertations (2024 - present)

Hybrid bonding has emerged as a key enabler for next-generation three-dimensional (3D) integration, offering fine-pitch interconnects and improved electrical performance. However, conventional Cu–Cu hybrid bonding typically requires elevated temperatures to achieve sufficient diffusion and interface quality, posing challenges for temperature-sensitive device integration and process compatibility. This work investigates materials engineering approaches to enable low-temperature Cu–Cu bonding through both microstructure design and alloying strategies.

This work begins by examining grain refinement in Cu as a pathway to enhance diffusion through increased grain boundary density, providing efficient atomic transport without introducing additional elements. Three Cu-based systems Cu–Co, Cu–Ag, and Cu–Al were systematically …

Entropic Dynamics Approach To The Classical Limit Of Quantum Mechanics: Decoupling Of The Center Of Mass Motion For A Mesoscopic Particle, Fatimah Judayba

Electronic Theses & Dissertations (2024 - present)

In the Entropic Dynamics (ED) approach, quantum mechanics is derived from the principles of entropic inference and information geometry. The ED approach differs from other interpretations by making a clear commitment to distinguishing which variables are ontic (real) and which are epistemic. The classical limit for the center of mass (CM) coordinate is achieved for a large number of particles, M →∞, while Planck’s constant ℏ remains finite. Typically, the emergence of the classical limit requires decoherence through interactions with the external environment. In this work, we investigate whether the classical behavior of the CM coordinate in a mesoscopic system …

Reaching The Intrinsic Performance Limits Of Superconducting Nanowire Single-Photon Detectors Up To 0.1 Mm Wide, Kristen M. Parzuchowski, Eli Mueller, Bakhrom G. Oripov, Benedikt Hampel, Ravin A. Chowdhury, Sahil R. Patel, Daniel Kuznesof, Emma K. Batson, Ryan Morgenstern, Robert H. Hadfield, Varun B. Verma, Matthew D. Shaw, Jason P. Allmaras, Martina J. Stevens, Alex Gurevich, Adam N. Mccaughan

Physics Faculty Publications

Superconducting nanowire single-photon detectors combine high detection efficiency, low noise, and excellent timing resolution, making them a leading platform for photon-counting applications. However, despite decades of materials and fabrication research, detector performance has never been shown to match theoretical performance expectations. Here, we demonstrate in situ tuning of a detector from its typical, suboptimal operation, to a regime limited only by material quality, allowing the device to reach its intrinsic performance limit. Our approach is based on current-biased superconducting “rails” placed on either side of the detector that redistribute current across its width to achieve peak performance. This technique reduces …

Development Of Photolabile Coumarin Linker For Rna Synthesis And Crisprcas9 Applications, Ian Mcclain

Electronic Theses & Dissertations (2024 - present)

The scope of RNA-based therapeutics continues to expand as more siRNA, mRNA, and CRISPR-based treatments are approved for various medical applications. Purification of synthetic RNA drugs is inherently challenging and requires considerable time and resources. New cost-effective and efficient purification strategies will expedite drug development process and will lower the drug costs. In this thesis I describe two generations of photolabile linkers for the non-chromatographic purification of therapeutic RNAs. In addition, the photolabile linker was utilized for regulation CRISPR-Cas9 gene editing. In the first part of the thesis, I describe the first generation of the photolabile coumarin-based linker for non-chromatographic …

Drivers Of Extreme Streamflow During A Snowmelt-Enhanced Heavy Rainfall And Atmospheric River Event In The Catskill Mountains Of New York, Christopher A. Gilberti

Electronic Theses & Dissertations (2024 - present)

This study uses atmospheric reanalysis, precipitation and snow water equivalent (SWE) analyses, mesonet observations, and streamflow records to examine the impact of an atmospheric river storm that produced heavy rainfall and snowpack ablation across the Catskill Mountains of New York on 24–25 December 2020. Earlier in December, an antecedent storm produced SWE values in the Catskills above the 90^th percentile for that point in the season. The atmospheric river event followed with strong southerly warm-air advection ahead of an anomalously deep trough, temperatures and dewpoints that exceeded 10°C, and heavy orographically enhanced rainfall and rapid snowmelt. Sensible heat fluxes …

Weather-Related Road Condition Detection Using Co-Developed Machine Learning Methods, Carly Sutter

Electronic Theses & Dissertations (2024 - present)

Transportation agencies make critical operational decisions during hazardous weather events, including assessment of road conditions and resource allocation. In this study, machine learning models are developed to provide additional support for the New York State Department of Transportation (NYSDOT) by automatically classifying road conditions across the state. Convolutional neural networks and random forests are trained on NYSDOT roadside camera images and weather data to predict road surface conditions. This task draws critically on a labeled dataset of 22,000 camera images containing six road surface conditions (severe snow, snow, wet, dry, poor visibility, and obstructed) generated from an iterative hand-labeling process …

ℵ-Ipomdp: Mitigating Deception In A Cognitive Hierarchy With Off-Policy Counterfactual Anomaly Detection, Nitay Alon, Joseph M. Barnby, Stefan Sarkadi, Lion Schulz, Jeffrey S. Rosenschein, Peter Dayan

Research outputs 2022 to 2026

Social agents with finitely nested opponent models are vulnerable to manipulation by agents with deeper recursive capabilities. This imbalance, rooted in logic and the theory of recursive modelling frameworks, cannot be solved directly. We propose a computational framework called ℵ-IPOMDP, which augments the Bayesian inference of model-based RL agents with an anomaly detection algorithm and an out-of-belief policy. Our mechanism allows agents to realize that they are being deceived, even if they cannot understand how, and to deter opponents via a credible threat. We test this framework in both a mixed-motive and a zero-sum game. Our results demonstrate the ℵ-mechanism’s …

Stakeholder Co-Design Of Sustainable Urban Pest Management Strategies, Elizabeth C. Lowe, Nathan J. Butterworth, Alexander Austin, Cameron Webb, Tanya Latty

Research outputs 2022 to 2026

The high levels of broad-spectrum insecticides used to manage invertebrates in many cities around the world has significant environmental and health impacts. Integrated pest management (IPM) is a framework for sustainable pest control practice, but uptake of IPM remains low in most cities. We used participatory action research with pest management industry stakeholders (practitioners, industry representatives, researchers and government employees) to identify key issues in urban pest management in Australia, set priorities for change and discuss collaborative solutions. Via an online survey and a face-to-face workshop, the participants identified the key themes of education and training, public awareness, environmental impacts …

Evolution Of A Managed Flood-Tide Delta And Barrier-Beach System, Charlestown, Rhode Island, Zachary Justin Levitan

Open Access Master's Theses

Barrier-beach and estuarine areas are important ecologically and economically, and the inlets connecting them are critical for ocean exchange and greatly dynamic. Man-made jetties are often installed to maintain the connection between ocean and estuary for navigation and water quality benefits. With storms and sea-level rise, coastal systems are changing over days to decades, affecting communities in New England and around the globe. This study utilized remotely sensed data (i.e., aerial imagery, lidar, and sonar) to examine the dynamics of the Charlestown Breachway and its flood-tide delta in southern Rhode Island, USA over varying times scales. The specific research objectives …

A Unified Framework For Evaluating Training Efficiency In Deep (Bayesian) Neural Networks: Metrics, Overtraining, Stopping Criteria, And Grokking Computer Science, Eduardo Cueto Mendoza

Doctoral

Measuring training efficiency for artificial neural networks is an open research problem, current literature reports several attempts to define measures or create reporting frameworks. Current methods lack generality as they require measurements of the hardware or software thus, comparing efficiency between different systems can be difficult. Similarly, current metrics or frameworks generally do not propose the use of the metrics to directly improve training efficiency. This thesis presents three main contributions: (1) a novel framework that quantifies the training efficiency of a neural architecture on a learning task as the average ratio of model accuracy to total energy consumption during …

Motivation System Evoked By High Performance Work System In Chinese Universities And Colleges - An Examination Of The Relationship Between Human Resource Practices, Basic Psychological Needs, And Job Performance, Juan Chen

Doctoral

High Performance Work Systems (HPWS) are strategic, integrated Human Resource Practices (HRPS) designed to enhance employee abilities, motivation, and opportunities for participation, driving sustained organisational performance. While early research emphasized commitment HRPS, recent studies recognise that control and commitment HRPS are complementary rather than mutually exclusive, with neither holding an absolute advantage. Their success depends on contextual factors such as country, industry,organisation, economic environment, and workforce. In Chinese higher education institutions, transitioning from a high-commitment “iron rice bowl” system to a more control-oriented HR model has created tensions between efficiency and academic freedom. Based on the resource-based view, social exchange …

Generation Of Wave Turbulence In Dipolar Gases Driven Across Their Phase Transitions, Georgios A. Bougas, Koushik Mukherjee, Simeon Mistakidis

Physics Faculty Research & Creative Works

Ultracold quantum gases with long-range anisotropic interactions host novel exotic phases of matter, such as super solids, exhibiting both rigid and superfluid characteristics. The impact of this interplay on the out-of-equilibrium dynamics of dipolar gases, and in particular its connection with universal turbulent behavior, remains highly unexplored. Here, upon considering a dipolar Bose-Einstein condensate of dysprosium atoms being dynamically driven across the super solid-superfluid phase transition and vice versa, we unveil the emergence of a robust nonequilibrium quasi-steady state. This state displays self-similar momentum distributions exhibiting algebraic decay at large momenta, with scaling exponents supporting the existence of wave turbulence. …

Decentralized Linear Solvers: Communication Cost And Privacy, Nelson G. Brasil, Vinay A. Vaishampayan

Publications and Research

We consider the problem of multiple parties iteratively solving a system of linear equations in a decentralized manner. Specifically, we solve for $\negr{x} \in \R^n$, the $n \times n$ system of linear equations $M\negr{x} = \negr{b}$ when each party only knows their row of the matrix $M$ and a single component of $\negr{b} \in \R^n$. Our objective is to determine the tradeoff between the accuracy of the solution and the total communication cost measured in bits. A fully connected, reliable mesh network is assumed to connect the different parties. We develop a general formulation that applies to a large class …

Large Language Model-Assisted Research Question Development In Public Health: A Case Study In The Special Supplemental Nutrition Program For Women, Infants, And Children (Wic), Qi Zhang, Bidusha Neupane, Priyanka Patel, Futun N. Alkhalifah, Yi He, Leslie Hodges

Health Behavior, Policy & Management Faculty Publications

Objective:

To assess the feasibility of using large language models (LLMs) to develop research questions about changes to the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) food packages.

Design:

We conducted a controlled experiment using ChatGPT-4 and its plugin, MixerBox Scholarly, to generate research questions based on a section of the USDA summary of the final public comments on the WIC revision. Five questions weekly for three weeks were generated using LLMs under two conditions: fed with or without relevant literature. The experiment generated 90 questions, which were evaluated using the FINER criteria (Feasibility, Innovation, Novelty, Ethics, …

A Critical Perspective On The Society Of Environmental Toxicology And Chemistry's Adherence To Founding Principles— Opportunities For The Future, Barnett A. Rattner, Annegaaike Leopold, Carys L. Mitchelmore, Glenn W. Suter, Mark S. Johnson, Adriana C. Bejarano, Lawrence A. Kapustka, Niranjana Krishnan, Derek C. G. Muir, Beatrice O. Opeolu, Martha Georgina Orozco-Medina, April Reed, Bruce W. Vigon, Adam R. Wronski

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

The Society of Environmental Toxicology and Chemistry (SETAC) is a global organization whose mission is the advancement of environmental science and management through collaboration, leadership, communication and education. On SETAC's 45th anniversary, the following question was raised: Are the 1979 founding principles of SETAC, multidisciplinary approaches to solving environmental problems, multisector engagement and scientific objectivity, still useful, adequate and effective in fulfilling its mission? In a special session held at the 45th Annual Meeting in Fort Worth, Texas, United States, a critical evaluation of the founding principles was initiated by reviewing SETAC's history and ongoing activities, and recommendations were made …

The Crucial Role Of Machine Learning Models In Predicting Current Childhood Asthma: Model Comparison, Calibration, And Shap-Based Interpretation, Aditya Chakraborty, A. K.M. Raquibul Bashar

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Background: Asthma is one of the most prominent chronic diseases in children and one of the most challenging ailments to diagnose in infants and preschoolers in the United States. Predictive models can be instrumental in improving early diagnosis, personalized treatment strategies, and disease progression. By utilizing nationalized data, this study focuses on building and comparing high-performing analytical predictive models based on the relevant risk factors and identifying the most influential predictors.

Methods: We analyzed cross-sectional BRFSS Asthma Call-Back Survey data (2011-2020; N = 9,813) and randomly split participants into training and testing sets. An XGBoost model (hyperparameters tuned via grid …

Fleet: A Federated Learning Emulation And Evaluation Testbed For Holistic Research, Osama Abu Hamdan, Hao Che, Engin Arslan, Md Arifuzzaman

Computer Science Faculty Research & Creative Works

Federated Learning (FL) presents a robust paradigm for privacy-preserving, decentralized machine learning. However, a significant gap persists between the theoretical design of FL algorithms and their practical performance, largely because existing evaluation tools often fail to model realistic operational conditions. Many testbeds oversimplify the critical dynamics among algorithmic efficiency, client-level heterogeneity, and continuously evolving network infrastructure. To address this challenge, we introduce the Federated Learning Emulation and Evaluation Testbed (FLEET). This comprehensive platform provides a scalable and configurable environment by integrating a versatile, framework-agnostic learning component with a high-fidelity network emulator. FLEET supports diverse machine learning frameworks, customizable real-world network …

Explaining The Unseen: Multimodal Vision-Language Reasoning For Situational Awareness In Underground Mining Disasters, Mizanur Rahman Jewel, Mohamed Elmahallawy, Sanjay Kumar Madria, Samuel Frimpong

Computer Science Faculty Research & Creative Works

Underground mining disasters produce pervasive darkness, dust, and collapses that obscure vision and make situational awareness difficult for humans and conventional systems. To address this, we propose MDSE, Multimodal Disaster Situation Explainer, a novel vision-language framework that automatically generates detailed textual explanations of post-disaster underground scenes. MDSE has three-fold innovations: (i) Context-Aware Cross-Attention for robust alignment of visual and textual features even under severe degradation; (ii) Segmentation-aware dual pathway visual encoding that fuses global and region-specific embeddings; and (iii) Resource-Efficient Transformer-Based Language Model for expressive caption generation with minimal compute cost. To support this task, we present the Underground Mine …

Changepoint Analyses Confirms Global Tropical Cyclone Frequency Decline, Michael Wehner, Thomas Fisher, Norou Diawara, Robert Lund

Mathematics & Statistics Faculty Publications

Changes in tropical cyclone frequencies as the climate warms is a topic of significant current debate [1, 2]. There is no accepted theory of how tropical cyclogenesis might respond to a warmer ocean-atmosphere system as multiple controlling factors exist [3–7]. Anthropogenic warming of surface ocean temperatures due to increased greenhouse gas concentrations [8] increases the potential for tropical cyclogenesis [9–11]; however, realized cyclogenesis also requires an initial local disturbance [12–16] to develop. Most multi-decadal tropical cyclone permitting climate models (i.e. resolutions of 15-50km) exhibit frequency decreases in warmer climates, despite the increase in tropical cyclogenesis potential [17–25]. In this paper, …

Mapping Multiclass-Targeted Hate Speech In Online Discourse: An Open Dataset, Sanaa Kaddoura, Sumaia Al-Kohlani

All Works

Online social networks have become central spaces for public discourse, where hostile and discriminatory language toward social groups can cause psychological and social consequences for marginalized communities. Although multiple public hate speech datasets are available, many rely on binary categorization practices that obscure linguistic, cultural, and contextual variation across targeted groups. As a result, minority and less visible forms of hate speech remain insufficiently documented and analyzed. This discussion paper examines methodological limitations in existing hate speech annotation schemes and presents a re-annotation framework applied to the HatEval2019 dataset. The proposed framework introduces target-specific multiclass labels that distinguish subcategories of …