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2025

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Articles 1141 - 1170 of 3497

Full-Text Articles in Computer Sciences

Adaptive Backstepping Control With Real-Time Fuzzy Logic Parameter Selection Of A Field- Oriented Control-Based Permanent Magnet Synchronous Motor Driver, Fati̇h Bayir, Erkan Zergeroğlu Jul 2025

Adaptive Backstepping Control With Real-Time Fuzzy Logic Parameter Selection Of A Field- Oriented Control-Based Permanent Magnet Synchronous Motor Driver, Fati̇h Bayir, Erkan Zergeroğlu

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes an adaptive backstepping control approach integrated with a real-time fuzzy logic parameter selection algorithm to enhance the robustness and stability of a permanent magnet synchronous motor (PMSM) controller under parametric uncertainties and external disturbances. Although backstepping control performs well under varying disturbances, it must be supported by an adaptive control algorithm to effectively handle both variable disturbances and parameter uncertainties. Moreover, because the fixed parameters of the adaptive backstepping controller limit the dynamic performance of the velocity tracking loop, this study incorporates fuzzy logic control—a soft computing algorithm capable of real-time parameter adjustment—to achieve more robust outcomes. …

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Excitation Of Synchronous Machine By Contactless Power Transfer - Review From The Perspective Of Electric Vehicles, Erhan Tuncel, Emi̇n Yildiriz Jul 2025

Excitation Of Synchronous Machine By Contactless Power Transfer - Review From The Perspective Of Electric Vehicles, Erhan Tuncel, Emi̇n Yildiriz

Turkish Journal of Electrical Engineering and Computer Sciences

Electrically excited synchronous machines (EESMs) are one of the best choices for propulsion motor appli cation in electric vehicles (EVs) due to their wide torque-speed characteristics. Moreover, the air gap flux density can be easily controlled by varying the excitation current. Despite these advantages, it is difficult to transfer the current required by the rotating excitation winding into the motor under conventional methods, so it is not widely used in EVs. In this study, the emerging literature on contactless power transfer methods is reviewed for applicability to an EESM that can operate as an EV propulsion motor. Design criteria such …

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Optimization And Model Averaging Of Histogram-Based Place Cell Firing Rate Maps Using The Point Process Framework, Murat Okatan Jul 2025

Optimization And Model Averaging Of Histogram-Based Place Cell Firing Rate Maps Using The Point Process Framework, Murat Okatan

Turkish Journal of Electrical Engineering and Computer Sciences

The firing rate of hippocampal place cells depends on the spatial position of the organism in an environment. This position dependence is often quantified by constructing spike-in-location and time-in-location histograms, the ratio of which yields a firing rate map. The purpose of this study is to present a new method for optimizing the spatial resolution of histogram-based firing rate maps. It is pointed out that histogram-based firing rate maps are conditional intensity functions of inhomogeneous Poisson process models of neural spike trains, and, as such, they can be optimized through model selection within the point process framework. The point process …

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Rescon: Residual Consistency For Real-World Super-Resolution, Erdi̇ Saritaş, Hazim Kemal Ekenel Jul 2025

Rescon: Residual Consistency For Real-World Super-Resolution, Erdi̇ Saritaş, Hazim Kemal Ekenel

Turkish Journal of Electrical Engineering and Computer Sciences

Real-world super-resolution is a highly challenging problem in the field of computer vision. Besides enhancing image resolution and improving visual details, information loss due to complex real-world degradations is desired to be restored. One of the primary hardness of this problem is finding sufficiently large paired datasets for training. Researchers have developed techniques that generate synthetic low-resolution pairs using high-resolution images with a generative adversarial network-based degradation generator to address this issue. In these approaches, the degradation generator is trained by utilizing real-world low-resolution images as the target domain, generating a degraded low-resolution counterpart of the high-resolution input. However, in …

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Combination Of Irreversible Electroporation And Clostridium Novyi-Nt Bacterial Therapy For Colorectal Liver Metastasis, Zigeng Zhang, Guangbo Yu, Qiaoming Hou, Farideh Amirrad, Sha Webster, Surya M. Nauli, Jianhua Yu, Vahid Yaghmai, Aydin Eresen, Zhuoli Zhang Jul 2025

Combination Of Irreversible Electroporation And Clostridium Novyi-Nt Bacterial Therapy For Colorectal Liver Metastasis, Zigeng Zhang, Guangbo Yu, Qiaoming Hou, Farideh Amirrad, Sha Webster, Surya M. Nauli, Jianhua Yu, Vahid Yaghmai, Aydin Eresen, Zhuoli Zhang

Pharmacy Faculty Articles and Research

Colorectal liver metastasis (CRLM) poses a significant challenge in oncology due to its high incidence and poor prognosis in unresectable cases. Current treatments, including surgical resection, systemic chemotherapy, and liver-directed therapies, often fail to effectively target hypoxic tumor regions, which are inherently more resistant to these interventions. This review examines the potential of a novel therapeutic strategy combining irreversible electroporation (IRE) ablation and Clostridium novyi-nontoxic (C. novyi-NT) bacterial therapy. IRE is a non-thermal tumor ablation technique that uses high-voltage electric pulses to create permanent nanopores in cell membranes, leading to cell death while preserving surrounding structures, and …

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Multilingual Cyber Threat Intelligence Feeds Preprocessing For Threat Intelligence Event Extraction: A Systematic Literature Review, Jamal H. Al-Yasiri, Mohamad Fadli Bin Zolkipli, Nik Fatinah N. Mohd Farid Jul 2025

Multilingual Cyber Threat Intelligence Feeds Preprocessing For Threat Intelligence Event Extraction: A Systematic Literature Review, Jamal H. Al-Yasiri, Mohamad Fadli Bin Zolkipli, Nik Fatinah N. Mohd Farid

Karbala International Journal of Modern Science

In cyber threat intelligence (CTI), information security specialists face overwhelming data flows from multiple sources, including hacker forums, dark web markets, and social media. These diverse and multilingual information streams require extensive analysis and processing. However, the current state of CTI faces several challenges, such as reliance on manual annotation and evaluation, as well as limited support for non-English languages, which hinders advanced threat detection and comprehensive analysis. This systematic literature review proposes a conceptual framework designed to overcome existing state-of-the-art limitations. It evaluates recent advancements in CTI methodologies by following PRISMA guidelines and analyzing selected studies from reputable sources, …

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More Everything Forever: Ai Overlords, Space Empires, And Silicon Valley’S Crusade To Control The Fate Of Humanity, Joseph Kirby Jul 2025

More Everything Forever: Ai Overlords, Space Empires, And Silicon Valley’S Crusade To Control The Fate Of Humanity, Joseph Kirby

Consensus

Becker, A. (2025). More everything forever : AI overlords, space empires, and Silicon Valley’s crusade to control the fate of humanity. Basic Books. ISBN: 9781541619593

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Improving Large Language Models’ Summarization Accuracy By Adding Highlights To Discharge Notes: Comparative Evaluation, Mahshad Koohi Habibi Dehkordi, Yehoshua Perl, Fadi P. Deek, Zhe He, Vipina K. Keloth, Hao Liu, Gai Elhanan, Andrew J. Einstein Jul 2025

Improving Large Language Models’ Summarization Accuracy By Adding Highlights To Discharge Notes: Comparative Evaluation, Mahshad Koohi Habibi Dehkordi, Yehoshua Perl, Fadi P. Deek, Zhe He, Vipina K. Keloth, Hao Liu, Gai Elhanan, Andrew J. Einstein

School of Computing Faculty Scholarship and Creative Works

Background: The American Medical Association recommends that electronic health record (EHR) notes, often dense and written in nuanced language, be made readable for patients and laypeople, a practice we refer to as the simplification of discharge notes. Our approach to achieving the simplification of discharge notes involves a process of incremental simplification steps to achieve the ideal note. In this paper, we present the first step of this process. Large language models (LLMs) have demonstrated considerable success in text summarization. Such LLM summaries represent the content of EHR notes in an easier-to-read language. However, LLM summaries can also introduce inaccuracies. …

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Coli@Fire2024: Findings Of Word-Level Code-Mixed Language Identification In Dravidian Languages, Asha Hegde, Fazlourrahman Balouchzahi, Sabur Butt, Sharal Coelho, Kavya G, Harshitha S. Kumar, Sonith D, Shashirekha H. L., Ameeta Agrawal Jul 2025

Coli@Fire2024: Findings Of Word-Level Code-Mixed Language Identification In Dravidian Languages, Asha Hegde, Fazlourrahman Balouchzahi, Sabur Butt, Sharal Coelho, Kavya G, Harshitha S. Kumar, Sonith D, Shashirekha H. L., Ameeta Agrawal

Computer Science Faculty Publications and Presentations

Code-mixing, a linguistic phenomenon where multiple languages are blended within a single text, has become increasingly prevalent in multilingual societies, particularly in digital communication. The CoLI-Dravidian shared task, organized as part of Forum for Information Retrieval and Evaluation (FIRE) 2024, aimed to address these challenges by inviting researchers to develop models capable of classifying words in code-mixed texts involving Dravidian languages — Tamil, Kannada, Malayalam, and Tulu - interwoven with English. The task presents significant challenges due to the complexity of linguistic structures, mixed-language tokens, and dialectal variations, especially in low-resource languages like those in the Dravidian family. The participating …

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Assessing The Adversarial Robustness Of Multimodal Medical Ai Systems: Insights Into Vulnerabilities And Modality Interactions, Ekaterina Mozhegova, Asad Masood Khattak, Adil Khan, Roman Garaev, Bader Rasheed, Muhammad Shahid Anwar Jul 2025

Assessing The Adversarial Robustness Of Multimodal Medical Ai Systems: Insights Into Vulnerabilities And Modality Interactions, Ekaterina Mozhegova, Asad Masood Khattak, Adil Khan, Roman Garaev, Bader Rasheed, Muhammad Shahid Anwar

All Works

The emergence of both task-specific single-modality models and general-purpose multimodal large models presents new opportunities, but also introduces challenges, particularly regarding adversarial attacks. In high-stakes domains like healthcare, these attacks can severely undermine model reliability and their applicability in real-world scenarios, highlighting the critical need for research focused on adversarial robustness. This study investigates the behavior of multimodal models under various adversarial attack scenarios. We conducted experiments involving two modalities: images and texts. Our findings indicate that multimodal models exhibit enhanced resilience against adversarial attacks compared to their single-modality counterparts. This supports our hypothesis that the integration of multiple modalities …

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Antibacterial Potential Of Tapanuli Orangutan (Pongo Tapanuliensis) Food In Batang Toru Forest Against Escherichia Coli And Salmonella Typhi, Herna Febrianty Sianipar, Wahyu Widoretno, Luchman Hakim, Rezi Rahmi Amolia, Fatchiyah Fatchiyah Jul 2025

Antibacterial Potential Of Tapanuli Orangutan (Pongo Tapanuliensis) Food In Batang Toru Forest Against Escherichia Coli And Salmonella Typhi, Herna Febrianty Sianipar, Wahyu Widoretno, Luchman Hakim, Rezi Rahmi Amolia, Fatchiyah Fatchiyah

Karbala International Journal of Modern Science

Diarrhea is a common disease affecting orangutans, primarily caused by Escherichia coli and Salmonella typhi bacteria. To treat this disease, antibacterial food sources are essential as therapeutic agents for orangutans. The fruits consumed by Tapanuli orangutans include Campnosperma auriculatum, Agathis borneensis, Artocarpus heterophyllus, Castanopsis argantea, and Aglaia tomentosa. This study aims to examine the amino acid and phytochemical components with potential antibacterial properties in these five fruit species and their inhibitory effects on E. coli and S. typhi growth through cell lysis, observed using a Scanning Electron Microscope (SEM). The samples were tested for amino acids, phytochemicals, vitamin C content, …

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Investigating The Impact Of Agent Openness On Planning In Multi-Agent Systems, Bala Subramanyam Duggirala Jul 2025

Investigating The Impact Of Agent Openness On Planning In Multi-Agent Systems, Bala Subramanyam Duggirala

School of Computing: Dissertations, Theses, and Student Research

Multi-agent systems (MAS) possess significant potential for modeling real-world scenarios requiring coordinated actions (like wildfire fighting or ridesharing) among autonomous entities or agents (e.g., wildfire fighting agents) in complex, dynamic environments. Effective decision-theoretic planning (where each agent must carefully consider both the immediate and the future situations or states, and coordinate with the other agents (neighbors) to evaluate what needs to be done at present) within MAS, especially multiagent planning, where the planning agent directly models its neighbors in order to estimate their optimal actions, is critical, yet challenged by factors like partial observability, openness, and diverse agent types with …

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Zero Trust Architecture For Electric Transportation Systems: A Systematic Survey And Deep Learning Framework For Replay Attack Detection, Grace Muriithi, Behnaz Papari, Ali Arsalan, Laxman Timilsina, Alex Muriithi, Elutunji Buraimoh, Asif Khan, Gokhan Ozkan, Christopher Edrington, Akram Papari Jul 2025

Zero Trust Architecture For Electric Transportation Systems: A Systematic Survey And Deep Learning Framework For Replay Attack Detection, Grace Muriithi, Behnaz Papari, Ali Arsalan, Laxman Timilsina, Alex Muriithi, Elutunji Buraimoh, Asif Khan, Gokhan Ozkan, Christopher Edrington, Akram Papari

Montclair State University Scholarship & Creative Works

Modern and autonomous hybrid electric vehicles (HEVs), as complex cyber-physical systems, represent a key innovation in the future of transportation. However, the increasing interconnectivity and reliance on digital components expose these vehicles to significant cybersecurity risks. To address these challenges, Zero Trust Architecture (ZTA) has emerged as a promising security framework. Operating on the principle of ‘never trust, always verify,’ ZTA offers a comprehensive approach to ensuring continuous trust verification in HEV systems. Despite its potential, the application of ZTA within cyber-physical vehicular systems remains underexplored, and its practical benefits and limitations are not yet fully understood by the engineering …

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Multiscale Modeling And Dynamic Mutational Profiling Of Binding Energetics And Immune Escape For Class I Antibodies With Sars-Cov-2 Spike Protein: Dissecting Mechanisms Of High Resistance To Viral Escape Against Emerging Variants, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker Jul 2025

Multiscale Modeling And Dynamic Mutational Profiling Of Binding Energetics And Immune Escape For Class I Antibodies With Sars-Cov-2 Spike Protein: Dissecting Mechanisms Of High Resistance To Viral Escape Against Emerging Variants, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

The rapid evolution of SARS-CoV-2 has underscored the need for a detailed understanding of antibody binding mechanisms to combat immune evasion by emerging variants. In this study, we investigated the interactions between Class I neutralizing antibodies—BD55-1205, BD-604, OMI-42, P5S-1H1, and P5S-2B10—and the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein using multiscale modeling, which combined molecular simulations with the ensemble-based mutational scanning of the binding interfaces and binding free energy computations. A central theme emerging from this work is that the unique binding strength and resilience to immune escape of the BD55-1205 antibody are determined by leveraging a broad epitope …

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Effects Of Plasma-Activated Water On Wheat: Germination And Seedling Development, Wafaa Abdulrazzaq Abdullah, Hadeel O. Ismael, Duaa A. Uamran, Hammad R. Humud Jul 2025

Effects Of Plasma-Activated Water On Wheat: Germination And Seedling Development, Wafaa Abdulrazzaq Abdullah, Hadeel O. Ismael, Duaa A. Uamran, Hammad R. Humud

Karbala International Journal of Modern Science

The food sector must contend with issues such as pathogen resistance to some of the available chemical agents, environmental pollution, and climate change to provide healthy food for livestock and people. The application of atmospheric pressure plasma jets (APPJs) is one potential solution for such problems. Plasma is appropriate for effective surface decontamination regarding food products and seeds, surface decontamination, and achieving improved agricultural production yields. The impact of plasma-activated water (PAW) produced by plasma jet discharge (PJD) system on in vitro-cultivated wheat seeds is examined in this work. For this aim, a plasma jet system was constructed with a …

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Teaching Ai Ethics And Skepticism: The Impact Of Instruction On Ethical Usage On Students’ Perceptions, Jenna D. Justin Jul 2025

Teaching Ai Ethics And Skepticism: The Impact Of Instruction On Ethical Usage On Students’ Perceptions, Jenna D. Justin

Journal of Practitioner Research

This study investigates the ethical implications of artificial intelligence (AI) in K-12 education, focusing on how explicit instruction influences students' perceptions of AI tools like ChatGPT. Conducted with 80 sixth-grade students at A.D. Henderson University School and FAU High School, the research tracks changes in student understanding and skepticism of AI following a World History unit. Pre- and post-instruction surveys revealed a decline in comfort with AI as students became more aware of its ethical concerns, including plagiarism, bias, and misinformation. The findings suggest integrating AI ethics into the middle school curriculum to foster responsible AI usage among students.

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Policy-Based Redactable Set Signatures, Zachary A. Kissel Jul 2025

Policy-Based Redactable Set Signatures, Zachary A. Kissel

Computer and Data Science Faculty Publications

A redactable set signature scheme is a signature scheme that allows a redactor, without possessing the signing key, to convert a signature on set S to a signature on set S' if S' ⊂ S. This paper introduces a new form of redactable set signature scheme called a policy-based redactable set signature scheme. These redactable set signatures allow for a signer to provide a redaction policy at signing time that limits the possible redactions that can be made by a redactor. In particular, a signature on set S can only be redacted to a signature on if S' ⊂ …

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Digital Identity Management As A Critical Criminal Justice And Homeland Security Legal Issue: A Qualitative Analysis Of The Reasonable Person Factors Involved In Court Decisions, William H. Nicholson Jul 2025

Digital Identity Management As A Critical Criminal Justice And Homeland Security Legal Issue: A Qualitative Analysis Of The Reasonable Person Factors Involved In Court Decisions, William H. Nicholson

Doctoral Dissertations and Projects

The purpose of this descriptive qualitative applied study is to define and explain through analysis the reasonable person standard as it relates to prosecution and sentencing computer crime cases involving digital identities while addressing the problem of digital anonymity. This has been done by analyzing computer crime cases with the advent of current and planned technologies, and surveying potential jurors to understand the current state of knowledge of digital attribution. This descriptive qualitative research method analyzed the problem through the use of criminological theories of control and social learning theory to better understand the reasonable person standard in computer crime …

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Alignment Of Perceptual Similarity Metrics With Human Perception, Abhijay Ghildyal Jul 2025

Alignment Of Perceptual Similarity Metrics With Human Perception, Abhijay Ghildyal

Dissertations and Theses

Perceptual similarity metrics are used for quantitatively evaluating the similarity between two images as it would appear to human perception. These metrics aim to mimic the human visual system, providing a more accurate assessment of visual similarity. Such visual assessments are considered to be more advanced than simple pixel-wise comparisons such as ℓp norm distances. Thus, a human-like assessment of visual similarity, makes the metrics valuable for applications in image compression, restoration, and enhancement, where evaluating perceptual quality is crucial. Perceptual similarity metrics have progressively become more correlated with human judgments on perceptual similarity; however, despite recent advances, the …

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Securing Ai-Generated Code, Andreas E. Nelson Jul 2025

Securing Ai-Generated Code, Andreas E. Nelson

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

The increasing use of AI for code generation presents significant security challenges, as these tools often lack inherent security awareness and can produce vulnerable code. This paper investigates these security risks, outlining common types of vulnerabilities (such as injection flaws and improper resource handling) found in AI-generated code. It further explores and evaluates mitigation techniques aimed at im-proving code security, including model fine-tuning and adversarial strategies like Security Verifier Enhanced Neural Steering (SVEN). Findings indicate that while current methods offer promising ways to reduce vulnerabilities, ongoing research and development are crucial for the secure and responsible deployment of AI in …

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Relightable Neural Radiance Fields For Novel View Synthesis, Malena I. Mahoney Jul 2025

Relightable Neural Radiance Fields For Novel View Synthesis, Malena I. Mahoney

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

This paper describes relighting neural radiance fields for novel view synthesis. View synthesis is the problem of using input images with corresponding camera angles to produce a photorealistic 3D model of an environment and its objects. Neural radiance fields (NeRFs) were created as a solution to view synthesis. Neural radiance field models work well for generating realistic 3D models from 2D image inputs; how-ever, they do not support changing the lighting or placing the objects from the input images into different environments. The problem comes from the fact that NeRFs rely on a neural network that is essentially overfitted to …

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A Longitudinal Analysis Of Morphological Shape Variation Of Spleen In Patients With Fontan Surgery, Varatharajan Nainamalai, Håvard Bjørke Jenssen, Mostafa Rezaeitaleshmahalleh, Djinaud Prophete, Jordan Gosnell, Sarah Khan, Marcus Haw, Jingfeng Jiang, Joseph Vettukattil Jul 2025

A Longitudinal Analysis Of Morphological Shape Variation Of Spleen In Patients With Fontan Surgery, Varatharajan Nainamalai, Håvard Bjørke Jenssen, Mostafa Rezaeitaleshmahalleh, Djinaud Prophete, Jordan Gosnell, Sarah Khan, Marcus Haw, Jingfeng Jiang, Joseph Vettukattil

Michigan Tech Publications

Background: Splenic size serves as a surrogate biomarker for predicting portal vein hyper-tension and liver abnormalities in subjects with Fontan Associated Liver Disease (FALD). We analyze the long-term shape variation of the spleen in FALD subjects using morphological shape features of radiomic features. Methods: We used 154 (84 from computed tomography and 70 from magnetic resonance) image volumes obtained from 36 individuals who underwent stage 3 Fontan procedure and 145 computed tomography images from controls to assess splenomegaly. To understand the splenomegaly, thirteen shape features of the spleen over three 10-year intervals, and variations between controls and FALD subjects were …

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Towards Sustainable Community-Designed Ai Systems In The Public Sector, Victoria Chui, Kelly Mcconvey, Erina Seh-Young Moon, Maya Ghai, Shion Guha Jul 2025

Towards Sustainable Community-Designed Ai Systems In The Public Sector, Victoria Chui, Kelly Mcconvey, Erina Seh-Young Moon, Maya Ghai, Shion Guha

Health Services and Informatics Research

Advancements in data-driven modeling and artificial intelligence applications in public sector settings can lead to increased ten sions between stakeholder needs and tangible model capabilities from developers. Engaging multiple stakeholder groups in model development through the gleaning of sociotechnical, theoretical in sights using qualitative methods can contribute to more impactful, beneficial model solutions. Qualitative methods can complement quantitative model development, emphasizing stakeholder priori ties, informing model design choices, and promoting sustainable connections and model longevity. We are excited to discuss human centered qualitative methods, sustainable modeling practices, and community engagement in this workshop, engaging with scholars on system-level modeling strategies.

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A Comprehensive Deep Learning System With Mgrf Modeling For Predicting Breast Cancer Response To Neoadjuvant Chemotherapy, Ahmed Sharafeldeen, Fatma Taher, Norah Saleh Alghamdi, Eman Alnaghy, Reham Alghandour, Khadiga M. Ali, Sameh Shamaa, Abdelrahman Gamal, Mohammed Ghazal, Sohail Contractor, Ayman El-Baz Jul 2025

A Comprehensive Deep Learning System With Mgrf Modeling For Predicting Breast Cancer Response To Neoadjuvant Chemotherapy, Ahmed Sharafeldeen, Fatma Taher, Norah Saleh Alghamdi, Eman Alnaghy, Reham Alghandour, Khadiga M. Ali, Sameh Shamaa, Abdelrahman Gamal, Mohammed Ghazal, Sohail Contractor, Ayman El-Baz

All Works

Accurate prediction of breast cancer (BC) response to neoadjuvant chemotherapy (NAC) is critical for tailoring treatment strategies and improving patient outcomes. This study introduces a novel deep learning-based framework that integrates multi-parametric magnetic resonance imaging (MRI) (i.e., T1, T2, STIR, and DWI), along with clinical and molecular subtype markers, to classify tumor response into pathological complete response (pCR), partial response (PR), and stable disease (SD). First, tumor regions are delineated across MRI modalities and then modeled using a translation-invariant Markov-Gibbs random field (MGRF) with analytical parameter estimation to capture modality-specific spatial appearance patterns correlated with NAC response. Subsequently, diffusion-weighted MRI …

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Zeus: Zero-Shot Llm Instruction For Union Segmentation In Multimodal Medical Imaging, Siyuan Dai, Kai Ye, Guodong Liu, Haoteng Tang, Liang Zhan Jul 2025

Zeus: Zero-Shot Llm Instruction For Union Segmentation In Multimodal Medical Imaging, Siyuan Dai, Kai Ye, Guodong Liu, Haoteng Tang, Liang Zhan

Computer Science Faculty Publications

Medical image segmentation has achieved remarkable success through the continuous advancement of UNet-based and Transformer-based foundation backbones. However, clinical diagnosis in the real world often requires integrating domain knowledge, especially textual information. Conducting multimodal learning involves visual and text modalities shown as a solution, but collecting paired vision-language datasets is expensive and time-consuming, posing significant challenges. Inspired by the superior ability in numerous cross-modal tasks for Large Language Models (LLMs), we proposed a novel Vision-LLM union framework to address the issues. Specifically, we introduce frozen LLMs for zero-shot instruction generation based on corresponding medical images, imitating the radiology scanning and …

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Strengthening Scientific Integrity: Digital Forensics For Biomedical Research Imaging, João Phillipe Cardenuto, Daniel Moreira, Anderson Rocha Jul 2025

Strengthening Scientific Integrity: Digital Forensics For Biomedical Research Imaging, João Phillipe Cardenuto, Daniel Moreira, Anderson Rocha

Computer Science: Faculty Publications and Other Works

To fight against the increasing misconduct cases in science, this Ph. D. research confronted the challenge of scientific integrity with a pioneering investigation into digital forensic analysis specifically tailored for biomedical images. This work conducted extensive research into key manipulation types–copy-move forgery, image reuse, and AI-generated content–developing novel, fully explainable, and auditable computational detection methods for each. In a commitment to transparency and to promote research to the area, these techniques are provided as open-source resources. Besides the isolated techniques for each type of image forged, a central contribution is the development of an end-to-end system, created through collaboration with …

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Research On Policy Representation In Deep Reinforcement Learning, Zhen Chen, Zhuoyi Wu, Lin Zhang Jul 2025

Research On Policy Representation In Deep Reinforcement Learning, Zhen Chen, Zhuoyi Wu, Lin Zhang

Journal of System Simulation

Abstract: Deep reinforcement learning (DRL) has achieved remarkable success in various domains. Nevertheless, existing policy networks in DRL still face significant challenges in areas such as generalizability, multi-task adaptability, and sample efficiency. Policy representation, as a crucial research direction for enhancing DRL capabilities, aims to improve an agent's adaptability to environmental changes and novel tasks by constructing more efficient and generalizable forms of policy expression. This paper provided a concise overview of key research advances in the field of policy representation. It introduced diverse policy architectures, ranging from traditional multi-layer perceptron (MLP) -based policies to those based on pointer networks, …

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Ai Project Facilitation Guidance For Research Computing And Data (Rcd) Professionals, Anna Alber, Laura Briggs, Paul Brunk, Manasvita Joshi, Atish P. Kamble, Amira Kefi, Timothy Middelkoop, Semir Sarajlic, Ana Maria Sokovic, Jeffrey N. Valdez, Ying Zhang Jul 2025

Ai Project Facilitation Guidance For Research Computing And Data (Rcd) Professionals, Anna Alber, Laura Briggs, Paul Brunk, Manasvita Joshi, Atish P. Kamble, Amira Kefi, Timothy Middelkoop, Semir Sarajlic, Ana Maria Sokovic, Jeffrey N. Valdez, Ying Zhang

Administration and Staff Articles and Research

The role of Artificial Intelligence (AI) in research and education continues to rapidly grow, resulting in increased collaboration between researchers in AI and Research Computing and Data (RCD) professionals to meet the research and teaching demands. RCD professionals bridge the gap between research and technology by guiding and collaborating with researchers and educators through the process of selecting the hardware, software, and services best suited for executing their AI projects. This includes ensuring compliance with funding and regulatory requirements across the entire lifecycle of the project. In this paper, we present an overview of the AI project lifecycle and how …

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A Web Application For Generating Argument Maps For Essays Using Llms, Alexis R. Chalmers Jul 2025

A Web Application For Generating Argument Maps For Essays Using Llms, Alexis R. Chalmers

Theses

Argumentative writing is a critical skill that strengthens students’ reasoning, communication, and analytical abilities. However, maintaining a clear and organized argument structure while writing can be challenging. Argument maps — visual diagrams which explicitly show an argument’s structure — have been shown to improve students’ writing, but are rarely used outside of the planning stage of an essay due to the time and effort required to create them. Automatically generating argument maps from student essays helps students to evaluate the structure of their argument as they write and makes identifying unsupported claims visible. To evaluate whether large language models (LLMs) …

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Thinking On Simulation Science And Engineering In The Era Of Artificial Intelligence, Wenhui Fan, Yuan Jiang Jul 2025

Thinking On Simulation Science And Engineering In The Era Of Artificial Intelligence, Wenhui Fan, Yuan Jiang

Journal of System Simulation

Abstract: With the rapid advancement of artificial intelligence and computing technologies, simulation technologies have leapfrogged, propelling the discipline of simulation toward greater maturity. Research progress in computer simulation technologies both in China and abroad was reviewed, and the definition and connotation of simulation were clarified. It was proposed that the Chinese terms "仿真" "仿效"and " 模拟" be unified under a single term " 仿真" with corresponding "Simulation" "Emulation" and "Analog" in English translated uniformly as "Simulation". Simulation science and engineering discipline was delineated, which was grounded in three core theoretical foundations: analogical theory,computational theory, and model validation theory. The first-level …

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