Tootfinder

San Diego-based Clearspeed, which offers AI-driven voice-based risk assessment tech for 60 languages, raised a $60M Series D, taking its total funding to $110M (Duncan Riley/SiliconANGLE)
https://siliconangle.com/2025/06/26/cl

Clearspeed raises $60M to expand voice-based risk assessment platform - SiliconANGLE
Clearspeed raises $60M to expand voice-based risk assessment platform - SiliconANGLE

National Climate Report Website Goes Dark (Rebecca Dzombak/New York Times)
https://www.nytimes.com/2025/07/01/climate/national-climate-assessment.html
http://www.memeorandum.com/250701/p88#a250701p88

The Impact of AI on Educational Assessment: A Framework for Constructive Alignment
Patrick Stokkink
https://arxiv.org/abs/2506.23815 https://

The Impact of AI on Educational Assessment: A Framework for Constructive Alignment
The influence of Artificial Intelligence (AI), and specifically Large Language Models (LLM), on education is continuously increasing. These models are frequently used by students, giving rise to the question whether current forms of assessment are still a valid way to evaluate student performance and comprehension. The theoretical framework developed in this paper is grounded in Constructive Alignment (CA) theory and Bloom's taxonomy for defining learning objectives. We argue that AI influences…

FPF and OneTrust launch updated Conformity Assessment under the EU AI Act: guide and infographic
https://fpf.org/blog/fpf-and-onetrust-launch-updated-conformity-assessment-under-the-eu-ai-act-guide-and-infographi…

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks
Lushun Fan, Yuqin Xia, Jun Li, Karl Jenkins
https://arxiv.org/abs/2506.22662

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks
This study explores the possibilities of automating the loading, classification and assessment of Computational Fluid Dynamics (CFD) mesh data by Convolutional Neural Networks (CNNs). The research aim is finding a feasible way to quickly make classification and assessment on airfoil mesh data. For this purpose, this study designed a new framework named CFD-based airfoil Classification and Assessment Network (AirCANS) for CFD mesh data which including the data loader and improved the CNN structu…

Bad moon rising…
("releasing" hundreds)
https://www.nytimes.com/2025/04/28/climate/national-climate-assessment-authors-dismissed.html?unlocked_article_cod…

On the polemic assessment of what Bell did
Justo Pastor Lambare
https://arxiv.org/abs/2506.22915 https://arxiv.org/pdf/2506.22915

On the polemic assessment of what Bell did
Despite their Nobel Prize-winning empirical falsification, the interpretation of the Bell inequality remains a subject of controversy. This article discusses and attempts to clarify the reasons John S. Bell and A. Einstein claimed that quantum entanglement implies puzzling nonlocal correlations that Einstein famously termed ``spooky action at a distance.'' The issue remains highly controversial and has roughly divided the scientific community into localists and nonlocalists. Without taking a st…

A Practical Guide for Supporting Formative Assessment and Feedback Using Generative AI
Sapolnach Prompiengchai, Charith Narreddy, Steve Joordens
https://arxiv.org/abs/2505.23405

A Practical Guide for Supporting Formative Assessment and Feedback Using Generative AI
Formative assessment is a cornerstone of effective teaching and learning, providing students with feedback to guide their learning. While there has been an exponential growth in the application of generative AI in scaling various aspects of formative assessment, ranging from automatic question generation to intelligent tutoring systems and personalized feedback, few have directly addressed the core pedagogical principles of formative assessment. Here, we critically examined how generative AI, e…

"Inside a plan to use AI to amplify doubts about the dangers of pollutants"
#AI #ArtificialIntelligence #Climate

Literature-Grounded Novelty Assessment of Scientific Ideas
Simra Shahid, Marissa Radensky, Raymond Fok, Pao Siangliulue, Daniel S. Weld, Tom Hope
https://arxiv.org/abs/2506.22026 …

Literature-Grounded Novelty Assessment of Scientific Ideas
Automated scientific idea generation systems have made remarkable progress, yet the automatic evaluation of idea novelty remains a critical and underexplored challenge. Manual evaluation of novelty through literature review is labor-intensive, prone to error due to subjectivity, and impractical at scale. To address these issues, we propose the Idea Novelty Checker, an LLM-based retrieval-augmented generation (RAG) framework that leverages a two-stage retrieve-then-rerank approach. The Idea Nove…

Adaptable Non-parametric Approach for Speech-based Symptom Assessment: Isolating Private Medical Data in a Retrieval Datastore
Yu-Wen Chen, Julia Hirschberg
https://arxiv.org/abs/2506.22972

Adaptable Non-parametric Approach for Speech-based Symptom Assessment: Isolating Private Medical Data in a Retrieval Datastore
The automatic assessment of health-related acoustic cues has the potential to improve healthcare accessibility and affordability. Although parametric models are promising, they face challenges in privacy and adaptability. To address these, we propose a NoN-Parametric framework for Speech-based symptom Assessment (NoNPSA). By isolating medical data in a retrieval datastore, NoNPSA avoids encoding private information in model parameters and enables efficient data updates. A self-supervised learni…

High Resolution Isotropic 3D Cine imaging with Automated Segmentation using Concatenated 2D Real-time Imaging and Deep Learning
Mark Wrobel (UCL Centre for Translational Cardiovascular Imaging, University College London), Michele Pascale (UCL Centre for Translational Cardiovascular Imaging, University College London), Tina Yao (UCL Centre for Translational Cardiovascular Imaging, University College London), Ruaraidh Campbell (UCL Centre for Translational Cardiovascular Imaging, Univers…

High Resolution Isotropic 3D Cine imaging with Automated Segmentation using Concatenated 2D Real-time Imaging and Deep Learning
Background: Conventional cardiovascular magnetic resonance (CMR) in paediatric and congenital heart disease uses 2D, breath-hold, balanced steady state free precession (bSSFP) cine imaging for assessment of function and cardiac-gated, respiratory-navigated, static 3D bSSFP whole-heart imaging for anatomical assessment. Our aim is to concatenate a stack 2D free-breathing real-time cines and use Deep Learning (DL) to create an isotropic a fully segmented 3D cine dataset from these images. Methods…

Met mijn hart gaat het goed.
Maar het gat in mijn lies(slagader) is vanmorgen gaan bloeden en opnieuw verbonden met een modern drukpleistersysteem (https://www.merit.com/product/safeguard-pressure-assisted-device/)
Nu mag ik zes uur stil op mijn ru…

SafeGuard® Pressure Assisted Device
Safeguard pressure assisted device maintains consistent pressure on the access site and facilitates site assessment through the clear window.

Metric formalism for precision assessment in non-Hermitian systems
Javid Naikoo, Ravindra W. Chhajlany, Jan Ko{\l}ody\'nski, Adam Miranowicz
https://arxiv.org/abs/2506.22571

Metric formalism for precision assessment in non-Hermitian systems
Enhancing measurement precision in quantum systems is vital for advancing technologies like quantum sensing and communication. Traditionally, quantum Fisher information (QFI) has been the key tool in determining precision limits within Hermitian quantum systems. However, recent research has expanded to non-Hermitian systems exhibiting real spectra. This study investigates various interpretations of non-Hermitian quantum dynamics such as the normalization and metric approaches. We demonstrate th…

Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach
Xue Wen Tan, Stanley Kok
https://arxiv.org/abs/2506.23767

Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach
Every publicly traded U.S. company files an annual 10-K report containing critical insights into financial health and risk. We propose Tiny eXplainable Risk Assessor (TinyXRA), a lightweight and explainable transformer-based model that automatically assesses company risk from these reports. Unlike prior work that relies solely on the standard deviation of excess returns (adjusted for the Fama-French model), which indiscriminately penalizes both upside and downside risk, TinyXRA incorporates ske…

Our urban #MobilityAnalytics project EMERALDS hosts its next webinar tomorrow:
🗓️ 27 June | ⏰ 14:30 CEST | 📍Online
How The Hague is using data to manage urban risks.
Register 👉

MMReason: An Open-Ended Multi-Modal Multi-Step Reasoning Benchmark for MLLMs Toward AGI
Huanjin Yao, Jiaxing Huang, Yawen Qiu, Michael K. Chen, Wenzheng Liu, Wei Zhang, Wenjie Zeng, Xikun Zhang, Jingyi Zhang, Yuxin Song, Wenhao Wu, Dacheng Tao
https://arxiv.org/abs/2506.23563

MMReason: An Open-Ended Multi-Modal Multi-Step Reasoning Benchmark for MLLMs Toward AGI
Reasoning plays a crucial role in advancing Multimodal Large Language Models (MLLMs) toward Artificial General Intelligence. However, existing MLLM benchmarks often fall short in precisely and comprehensively evaluating long-chain reasoning abilities from three key aspects: (1) lack of difficulty and diversity, (2) susceptibility to guessability and memorization, (3) inadequate assessment of intermediate reasoning steps. To fill this gap, we introduce MMReason, a new benchmark designed to preci…

Impact of Pre-Assessment and Post-Assessment in an Introductory Real Analysis Course
Chamila Malagoda Gamage
https://arxiv.org/abs/2505.22479 https://

Impact of Pre-Assessment and Post-Assessment in an Introductory Real Analysis Course
This study explores how pre- and post-assessments shape learning outcomes in an Introductory Real Analysis course. Pre-assessments act as learning roadmaps, highlighting prior knowledge and guiding student focus, while post-assessments measure growth and conceptual mastery. By analyzing student performance and feedback, we assess their impact on engagement, self-efficacy, and deeper mathematical understanding. The findings offer valuable insights for enhancing instructional strategies and foste…

And now they talk like a Donald 😲 Donald talk ->
"The White House said the "flat-out wrong" assessment was leaked by "a low-level loser in the intelligence community"."
US strikes did not destroy Iran nuclear programme, says intelligence assessment
https://www.bbc.co…

Quality assessment of 3D human animation: Subjective and objective evaluation
Rim Rekik, Stefanie Wuhrer, Ludovic Hoyet, Katja Zibrek, Anne-H\'el\`ene Olivier
https://arxiv.org/abs/2505.23301

Quality assessment of 3D human animation: Subjective and objective evaluation
Virtual human animations have a wide range of applications in virtual and augmented reality. While automatic generation methods of animated virtual humans have been developed, assessing their quality remains challenging. Recently, approaches introducing task-oriented evaluation metrics have been proposed, leveraging neural network training. However, quality assessment measures for animated virtual humans that are not generated with parametric body models have yet to be developed. In this contex…

Predictive Risk Analysis and Safe Trajectory Planning for Intelligent and Connected Vehicles
Zeyu Han, Mengchi Cai, Chaoyi Chen, Qingwen Meng, Guangwei Wang, Ying Liu, Qing Xu, Jianqiang Wang, Keqiang Li
https://arxiv.org/abs/2506.23999

Predictive Risk Analysis and Safe Trajectory Planning for Intelligent and Connected Vehicles
The safe trajectory planning of intelligent and connected vehicles is a key component in autonomous driving technology. Modeling the environment risk information by field is a promising and effective approach for safe trajectory planning. However, existing risk assessment theories only analyze the risk by current information, ignoring future prediction. This paper proposes a predictive risk analysis and safe trajectory planning framework for intelligent and connected vehicles. This framework fi…

An ontological lens on attack trees: Toward adequacy and interoperability
\'Italo Oliveira, Stefano M. Nicoletti, Gal Engelberg, Mattia Fumagalli, Dan Klein, Giancarlo Guizzardi
https://arxiv.org/abs/2506.23841

An ontological lens on attack trees: Toward adequacy and interoperability
Attack Trees (AT) are a popular formalism for security analysis. They are meant to display an attacker's goal decomposed into attack steps needed to achieve it and compute certain security metrics (e.g., attack cost, probability, and damage). ATs offer three important services: (a) conceptual modeling capabilities for representing security risk management scenarios, (b) a qualitative assessment to find root causes and minimal conditions of successful attacks, and (c) quantitative analyses via s…

Not All Water Consumption Is Equal: A Water Stress Weighted Metric for Sustainable Computing
Yanran Wu, Inez Hua, Yi Ding
https://arxiv.org/abs/2506.22773 …

Not All Water Consumption Is Equal: A Water Stress Weighted Metric for Sustainable Computing
Water consumption is an increasingly critical dimension of computing sustainability, especially as AI workloads rapidly scale. However, current water impact assessment often overlooks where and when water stress is more severe. To fill in this gap, we present SCARF, the first general framework that evaluates water impact of computing by factoring in both spatial and temporal variations in water stress. SCARF calculates an Adjusted Water Impact (AWI) metric that considers both consumption volume…

Early Assessment of Artificial Lower Extremity Sensory Response Times and Proprioceptive Acuity via Sensory Cortex Electrical Stimulation
Won Joon Sohn, Jeffrey Lim, Po T. Wang, Susan J. Shaw, Michelle Armacost, Hui Gong, Brian Lee, Darrin Lee, Payam Heydari, Richard A. Andersen, Charles Y. Liu, Zoran Nenadic, An H. Do
https://a…

Early Assessment of Artificial Lower Extremity Sensory Response Times and Proprioceptive Acuity via Sensory Cortex Electrical Stimulation
Bi-directional brain computer interfaces (BD-BCIs) may restore brain-controlled walking and artificial leg sensation after spinal cord injury. Current BD-BCIs provide only simplistic "tingling" feedback, which lacks proprioceptive information to perceive critical gait events (leg swing, double support). This information must also be perceived adequately fast to facilitate timely motor responses. Here, we investigated utilizing primary sensory cortex (S1) direct cortical electrical stimulation (…

CBF-AFA: Chunk-Based Multi-SSL Fusion for Automatic Fluency Assessment
Papa S\'ega Wade, Mihai Andries, Ioannis Kanellos, Thierry Moudenc
https://arxiv.org/abs/2506.20243

CBF-AFA: Chunk-Based Multi-SSL Fusion for Automatic Fluency Assessment
Automatic fluency assessment (AFA) remains challenging, particularly in capturing speech rhythm, pauses, and disfluencies in non-native speakers. We introduce a chunk-based approach integrating self-supervised learning (SSL) models (Wav2Vec2, HuBERT, and WavLM) selected for their complementary strengths in phonetic, prosodic, and noisy speech modeling, with a hierarchical CNN-BiLSTM framework. Speech is segmented into breath-group chunks using Silero voice activity detection (Silero-VAD), enabl…

Impact of magnetic field-driven anisotropies on the equation of state probed in neutron star mergers
Elias R. Most, Jeffrey Peterson, Luigi Scurto, Helena Pais, Veronica Dexheimer
https://arxiv.org/abs/2506.21696

Impact of magnetic field-driven anisotropies on the equation of state probed in neutron star mergers
Binary neutron star mergers can produce extreme magnetic fields, some of which can lead to strong magnetar-like remnants. While strong magnetic fields have been shown to affect the dynamics of outflows and angular momentum transport in the remnant, they can also crucially alter the properties of nuclear matter probed in the merger. In this work, we provide a first assessment of the latter, determining the strength of the pressure anisotropy caused by Landau level quantization and the anomalous …

Importance of the numerical schemes in the CFD of the human nose
Andrea Schillaci, Maurizio Quadrio
https://arxiv.org/abs/2506.23163 https://

Importance of the numerical schemes in the CFD of the human nose
Computational fluid dynamics of the air flow in the human nasal cavities, starting from patient-specific Computer Tomography (CT) scans, is an important tool for diagnostics and surgery planning. However, a complete and systematic assessment of the influence of the main modeling assumptions is still lacking. In designing such simulations, choosing the discretization scheme, which is the main subject of the present work, is an often overlooked decision of primary importance. We use a comparison …

Counterfactual Voting Adjustment for Quality Assessment and Fairer Voting in Online Platforms with Helpfulness Evaluation
Chang Liu, Yixin Wang, Moontae Lee
https://arxiv.org/abs/2506.21362

Counterfactual Voting Adjustment for Quality Assessment and Fairer Voting in Online Platforms with Helpfulness Evaluation
Efficient access to high-quality information is vital for online platforms. To promote more useful information, users not only create new content but also evaluate existing content, often through helpfulness voting. Although aggregated votes help service providers rank their user content, these votes are often biased by disparate accessibility per position and the cascaded influence of prior votes. For a fairer assessment of information quality, we propose the Counterfactual Voting Adjustment (…

Active View Selector: Fast and Accurate Active View Selection with Cross Reference Image Quality Assessment
Zirui Wang, Yash Bhalgat, Ruining Li, Victor Adrian Prisacariu
https://arxiv.org/abs/2506.19844

Active View Selector: Fast and Accurate Active View Selection with Cross Reference Image Quality Assessment
We tackle active view selection in novel view synthesis and 3D reconstruction. Existing methods like FisheRF and ActiveNeRF select the next best view by minimizing uncertainty or maximizing information gain in 3D, but they require specialized designs for different 3D representations and involve complex modelling in 3D space. Instead, we reframe this as a 2D image quality assessment (IQA) task, selecting views where current renderings have the lowest quality. Since ground-truth images for candid…

Human Empathy as Encoder: AI-Assisted Depression Assessment in Special Education
Boning Zhao
https://arxiv.org/abs/2505.23631 https://

Human Empathy as Encoder: AI-Assisted Depression Assessment in Special Education
Assessing student depression in sensitive environments like special education is challenging. Standardized questionnaires may not fully reflect students' true situations. Furthermore, automated methods often falter with rich student narratives, lacking the crucial, individualized insights stemming from teachers' empathetic connections with students. Existing methods often fail to address this ambiguity or effectively integrate educator understanding. To address these limitations by fostering a …

This https://arxiv.org/abs/2504.16979 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qbi…

Automating tumor-infiltrating lymphocyte assessment in breast cancer histopathology images using QuPath: a transparent and accessible machine learning pipeline
In this study, we built an end-to-end tumor-infiltrating lymphocytes (TILs) assessment pipeline within QuPath, demonstrating the potential of easily accessible tools to perform complex tasks in a fully automatic fashion. First, we trained a pixel classifier to segment tumor, tumor-associated stroma, and other tissue compartments in breast cancer H&E-stained whole-slide images (WSI) to isolate tumor-associated stroma for subsequent analysis. Next, we applied a pre-trained StarDist deep learning …

HighRateMOS: Sampling-Rate Aware Modeling for Speech Quality Assessment
Wenze Ren, Yi-Cheng Lin, Wen-Chin Huang, Ryandhimas E. Zezario, Szu-Wei Fu, Sung-Feng Huang, Erica Cooper, Haibin Wu, Hung-Yu Wei, Hsin-Min Wang, Hung-yi Lee, Yu Tsao
https://arxiv.org/abs/2506.21951

HighRateMOS: Sampling-Rate Aware Modeling for Speech Quality Assessment
Modern speech quality prediction models are trained on audio data resampled to a specific sampling rate. When faced with higher-rate audio at test time, these models can produce biased scores. We introduce HighRateMOS, the first non-intrusive mean opinion score (MOS) model that explicitly considers sampling rate. HighRateMOS ensembles three model variants that exploit the following information: (i) a learnable embedding of speech sampling rate, (ii) Wav2vec 2.0 self-supervised embeddings, (iii)…

Multidimensional Assessment of Public Space Quality: A Comprehensive Framework Across Urban Space Typologies
Mary John, Sherzod Turaev, Saja Al-Dabet, Rawad Abdulghafor
https://arxiv.org/abs/2505.21555

Multidimensional Assessment of Public Space Quality: A Comprehensive Framework Across Urban Space Typologies
This study presents a comprehensive framework for evaluating the quality of public spaces across various urban typologies. Through a systematic review of 159 research studies, we identify universal quality factors that transcend spatial types as well as specialized factors unique to specific public environments. Our findings establish accessibility (73.6%), safety/security (58.4%), and comfort (52.8%) as foundational requirements across all public space types, while revealing distinct quality p…

A nice (and thorough) assessment of the late Chris Whelan's work in the latest Economic and Social Review https://www.esr.ie/index.php/esr/article/view/3238

Ask before you Build: Rethinking AI-for-Good in Human Trafficking Interventions
Pratheeksha Nair, Gabriel Lefebvre, Sophia Garrel, Maryam Molamohammadi, Reihaneh Rabbany
https://arxiv.org/abs/2506.22512

Ask before you Build: Rethinking AI-for-Good in Human Trafficking Interventions
AI for good initiatives often rely on the assumption that technical interventions can resolve complex social problems. In the context of human trafficking (HT), such techno-solutionism risks oversimplifying exploitation, reinforcing power imbalances and causing harm to the very communities AI claims to support. In this paper, we introduce the Radical Questioning (RQ) framework as a five step, pre-project ethical assessment tool to critically evaluate whether AI should be built at all, especiall…

MedSAM-CA: A CNN-Augmented ViT with Attention-Enhanced Multi-Scale Fusion for Medical Image Segmentation
Peiting Tian, Xi Chen, Haixia Bi, Fan Li
https://arxiv.org/abs/2506.23700 …

MedSAM-CA: A CNN-Augmented ViT with Attention-Enhanced Multi-Scale Fusion for Medical Image Segmentation
Medical image segmentation plays a crucial role in clinical diagnosis and treatment planning, where accurate boundary delineation is essential for precise lesion localization, organ identification, and quantitative assessment. In recent years, deep learning-based methods have significantly advanced segmentation accuracy. However, two major challenges remain. First, the performance of these methods heavily relies on large-scale annotated datasets, which are often difficult to obtain in medical s…

I've been in meetings where #ACC "experts" testified "truthpartly" - but not "truthfully" - about chemical hazards - referencing old tests of health impacts (1970s/80s knowledge) while ignoring the mass of robust data developed in the late 90s and 2000s. This is another repeat performance for #ACC

I've been in meetings where #ACC "experts" testified "truthpartly" - but not "truthfully" - about chemical hazards - referencing old tests of health impacts (1970s/80s knowledge) while ignoring the mass of robust data developed in the late 90s and 2000s. This is another repeat performance for #ACC

Zum 20. Geburtstag der #Vorratsdatenspeicherung im Jahr 2025 freut sich die EU-Kommission über Eure Meinung zur Idee, die #VDS für Internet-Provider zum Zweck der Strafverfolgung einzuführen.
Noch bis zum 30.6. mit SMS für die Authentifizierung, danach nur mit eID, per Facebook od…

Resilience assessment framework for cyber-physical distribution power system based on coordinated cyber-physical attacks under dynamic game
Yulin Liu, Zhaojun Ruan, Libao Shi
https://arxiv.org/abs/2506.19636

Resilience assessment framework for cyber-physical distribution power system based on coordinated cyber-physical attacks under dynamic game
Owing to the advanced communication networks and intelligent electronic devices, the cyber-physical distribution systems (CPDSs) possess the capability to perform flexible economic dispatch and achieve rapid self-healing from extreme events. Meanwhile, the deep integration of cyber and physical systems makes CPDS vulnerable to coordinated cyber-physical attacks. In this paper, a resilience assessment framework for the CPDS under coordinated cyber-physical attacks is proposed to investigate the …

Bills WR Keon Coleman gives harsh self-assessment of rookie season: 'When that (expletive) trash, you got to be better' https://www.nfl.com/news/bills-wr-keon-coleman-gives-harsh-self-assessment-of-rookie-season-yo…

AI-Driven Tools in Modern Software Quality Assurance: An Assessment of Benefits, Challenges, and Future Directions
Ihor Pysmennyi, Roman Kyslyi, Kyrylo Kleshch
https://arxiv.org/abs/2506.16586

AI-Driven Tools in Modern Software Quality Assurance: An Assessment of Benefits, Challenges, and Future Directions
Traditional quality assurance (QA) methods face significant challenges in addressing the complexity, scale, and rapid iteration cycles of modern software systems and are strained by limited resources available, leading to substantial costs associated with poor quality. The object of this research is the Quality Assurance processes for modern distributed software applications. The subject of the research is the assessment of the benefits, challenges, and prospects of integrating modern AI-orient…

Vulnerability Assessment Combining CVSS Temporal Metrics and Bayesian Networks
Stefano Perone, Simone Guarino, Luca Faramondi, Roberto Setola
https://arxiv.org/abs/2506.18715

Vulnerability Assessment Combining CVSS Temporal Metrics and Bayesian Networks
Vulnerability assessment is a critical challenge in cybersecurity, particularly in industrial environments. This work presents an innovative approach by incorporating the temporal dimension into vulnerability assessment, an aspect neglected in existing literature. Specifically, this paper focuses on refining vulnerability assessment and prioritization by integrating Common Vulnerability Scoring System (CVSS) Temporal Metrics with Bayesian Networks to account for exploit availability, remediatio…

Rethinking Mean Opinion Scores in Speech Quality Assessment: Aggregation through Quantized Distribution Fitting
Yuto Kondo, Hirokazu Kameoka, Kou Tanaka, Takuhiro Kaneko
https://arxiv.org/abs/2506.18307

Rethinking Mean Opinion Scores in Speech Quality Assessment: Aggregation through Quantized Distribution Fitting
Speech quality assessment (SQA) aims to evaluate the quality of speech samples without relying on time-consuming listener questionnaires. Recent efforts have focused on training neural-based SQA models to predict the mean opinion score (MOS) of speech samples produced by text-to-speech or voice conversion systems. This paper targets the enhancement of MOS prediction models' performance. We propose a novel score aggregation method to address the limitations of conventional annotations for MOS, w…

Early US intel assessment finds strikes set back Iran's nuclear program only by months (ABC News)
https://abcnews.go.com/Politics/early-us-intel-assessment-finds-us-strikes-set/story?id=123169267
http://www.memeorandum.com/250624/p124#a250624p124

US strikes did not destroy Iran nuclear programme, says Pentagon assessment
https://www.bbc.com/news/articles/ckglxwp5x03o

Predictive Analysis of Gmelina arborea (Melina) Growth in Plantations of Esmeraldas: A Perspective for Silvicultural Management in Tropical Ecuador
Jos\'e Gabriel Carvajal Benavides, Hugo Orlando Paredes Rodr\'iguez, Oscar Armando Rosales Enr\'iquez, Eduardo Jaime Chagna Avila, Xavier Germ\'an Valencia Valenzuela, Guillermo David Varela J\'acome

Predictive Analysis of Gmelina arborea (Melina) Growth in Plantations of Esmeraldas: A Perspective for Silvicultural Management in Tropical Ecuador
This study presents a rigorous assessment of the growth performance of Gmelina arborea (melina) in a 67-hectare plantation located in Chontaduro, Tabiazo Parish, Esmeraldas, Ecuador. The plantation was established in 2017 under a high-density planting system (650 trees/ha). Permanent monitoring techniques were applied in 16 one-hectare plots to analyze structural growth variables, including survival rate, diameter at breast height (DBH), total height, commercial height, basal area, volume, and …

A Terminology and Quantitative Framework for Assessing the Habitability of Solar System and Extraterrestrial Worlds
Daniel Apai, Rory Barnes, Matthew M. Murphy, Tim Lichtenberg, Noah Tuchow, Regis Ferriere, Kevin Wagner, Antonin Affholder, Renu Malhotra, Baptiste Journaux, Allona Vazan, Ramses Ramirez, Abel Mendez, Stephen R. Kane, Veronica H. Klawender, NExSS Quantitative Habitability Science Working Group

A Terminology and Quantitative Framework for Assessing the Habitability of Solar System and Extraterrestrial Worlds
The search for extraterrestrial life in the Solar System and beyond is a key science driver in astrobiology, planetary science, and astrophysics. A critical step is the identification and characterization of potential habitats, both to guide the search and to interpret its results. However, a well-accepted, self-consistent, flexible, and quantitative terminology and method of assessment of habitability are lacking. Our paper fills this gap based on a three year-long study by the NExSS Quantitat…

Adapting University Policies for Generative AI: Opportunities, Challenges, and Policy Solutions in Higher Education
Russell Beale
https://arxiv.org/abs/2506.22231

Adapting University Policies for Generative AI: Opportunities, Challenges, and Policy Solutions in Higher Education
The rapid proliferation of generative artificial intelligence (AI) tools - especially large language models (LLMs) such as ChatGPT - has ushered in a transformative era in higher education. Universities in developed regions are increasingly integrating these technologies into research, teaching, and assessment. On one hand, LLMs can enhance productivity by streamlining literature reviews, facilitating idea generation, assisting with coding and data analysis, and even supporting grant proposal d…

Experimental Assessment of A Framework for In-body RF-backscattering Localization
Noa Jie Vives Zaguirre, Oscar Lasierra, Filip Lemic, Gerard Calvo Bartra, Pablo Jos\'e Galv\'an Calder\'on, Gines Garcia-Aviles, Sergi Abadal, Xavier Costa-P\'erez
https://arxiv.org/abs/2506.19499

Experimental Assessment of A Framework for In-body RF-backscattering Localization
Localization of in-body devices is beneficial for Gastrointestinal (GI) diagnosis and targeted treatment. Traditional methods such as imaging and endoscopy are invasive and limited in resolution, highlighting the need for innovative alternatives. This study presents an experimental framework for Radio Frequency (RF)-backscatter-based in-body localization, inspired by the ReMix approach, and evaluates its performance in real-world conditions. The experimental setup includes an in-body backscatte…

On the Role of Demagnetizing Tensors in Arbitrary Orientations of General Ellipsoid: Implications for MRI Safety Assessment
Tomppa Pakarinen
https://arxiv.org/abs/2505.21761

On the Role of Demagnetizing Tensors in Arbitrary Orientations of General Ellipsoid: Implications for MRI Safety Assessment
This work explores the behaviour of demagnetizing tensors for general ellipsoids under arbitrary rotations in homogeneous magnetic fields. The work is motivated by the concerns in magnetic resonance imaging safety and their practical evaluation in clinical environments. Whereas demagnetizing tensor is a well-defined concept in the principal axes, its transformation under three-dimensional reorientation is often overlooked - a justifiable omission for solutions derived from Poisson equation, whe…

[Beat-to-beat AV nodal assessment] ECG-based beat-to-beat assessment of AV node conduction properties during AF
Mattias Karlsson, Felix Plappert, Pyotr G Platonov, Sten \"Ostenson, Mikael Wallman, Frida Sandberg
https://arxiv.org/abs/2506.19427

[Beat-to-beat AV nodal assessment] ECG-based beat-to-beat assessment of AV node conduction properties during AF
The refractory period and conduction delay of the atrioventricular (AV) node play a crucial role in regulating the heart rate during atrial fibrillation (AF). Beat-to-beat variations in these properties are known to be induced by the autonomic nervous system (ANS) but have previously not been assessable during AF. Assessing these could provide novel information for improved diagnosis, prognosis, and treatment on an individual basis. To estimate AV nodal conduction properties with beat-to-beat…

ICME 2025 Generalizable HDR and SDR Video Quality Measurement Grand Challenge
Yixu Chen, Bowen Chen, Hai Wei, Alan C. Bovik, Baojun Li, Wei Sun, Linhan Cao, Kang Fu, Dandan Zhu, Jun Jia, Menghan Hu, Xiongkuo Min, Guangtao Zhai, Dounia Hammou, Fei Yin, Rafal Mantiuk, Amritha Premkumar, Prajit T Rajendran, Vignesh V Menon
https://…

ICME 2025 Generalizable HDR and SDR Video Quality Measurement Grand Challenge
This paper reports IEEE International Conference on Multimedia \& Expo (ICME) 2025 Grand Challenge on Generalizable HDR and SDR Video Quality Measurement. With the rapid development of video technology, especially High Dynamic Range (HDR) and Standard Dynamic Range (SDR) contents, the need for robust and generalizable Video Quality Assessment (VQA) methods has become increasingly demanded. Existing VQA models often struggle to deliver consistent performance across varying dynamic ranges, distor…

Profiling Frailty: A parsimonious Frailty Index from health administrative data based on POSET theory
Margherita Silan, Maurizio Nicolaio, Giovanna Boccuzzo
https://arxiv.org/abs/2506.23158

Profiling Frailty: A parsimonious Frailty Index from health administrative data based on POSET theory
Frailty assessment is crucial for stratifying populations and addressing healthcare challenges associated with ageing. This study proposes a Frailty Index based on administrative health data, with the aim of facilitating informed decision-making and resource allocation in population health management. The aim of this work is to develop a Frailty Index that 1) accurately predicts multiple adverse health outcomes, 2) comprises a parsimonious set of variables, 3) aggregates variables without prede…

Response Quality Assessment for Retrieval-Augmented Generation via Conditional Conformal Factuality
Naihe Feng, Yi Sui, Shiyi Hou, Jesse C. Cresswell, Ga Wu
https://arxiv.org/abs/2506.20978

Response Quality Assessment for Retrieval-Augmented Generation via Conditional Conformal Factuality
Existing research on Retrieval-Augmented Generation (RAG) primarily focuses on improving overall question-answering accuracy, often overlooking the quality of sub-claims within generated responses. Recent methods that attempt to improve RAG trustworthiness, such as through auto-evaluation metrics, lack probabilistic guarantees or require ground truth answers. To address these limitations, we propose Conformal-RAG, a novel framework inspired by recent applications of conformal prediction (CP) on…

A tangible user interface for assessing cognitive mapping ability
Ehud Sharlin, Benjamin Watson, Steve Sutphen, Lili Liu, Robert Lederer, John Frazer
https://arxiv.org/abs/2506.22597

A tangible user interface for assessing cognitive mapping ability
Wayfinding, the ability to recall the environment and navigate through it, is an essential cognitive skill relied upon almost every day in a person's life. A crucial component of wayfinding is the construction of cognitive maps, mental representations of the environments through which a person travels. Age, disease or injury can severely affect cognitive mapping, making assessment of this basic survival skill particularly important to clinicians and therapists. Cognitive mapping has also been t…

Unveiling the Pitfalls of CPL Parametrization at High Redshifts: A Critical Assessment of the $\omega_{0}$$\omega_a$CDM Model with DESI DR2 BAO Data
Seokcheon Lee
https://arxiv.org/abs/2506.18230

Unveiling the Pitfalls of CPL Parametrization at High Redshifts: A Critical Assessment of the $ω_{0}$$ω_a$CDM Model with DESI DR2 BAO Data
We critically assess the w0waCDM model, employing the Chevallier-Polarski-Linder (CPL) parametrization, w(z) = w0 + wa * z / (1 + z), using Baryon Acoustic Oscillation (BAO) measurements from DESI Data Release 2 (DR2). While DESI BAO data broadly align with the standard LambdaCDM model, giving Omega_m = 0.3, our Markov Chain Monte Carlo fits show notable variation in best-fit values and degeneracy directions for w0waCDM across combinations of BAO observables (DV/rd, DM/rd, DH/rd, and DM/DH). …

Experimental Assessment of Neural 3D Reconstruction for Small UAV-based Applications
Gen\'is Castillo G\'omez-Raya, \'Almos Veres-Vit\'alyos, Filip Lemic, Pablo Royo, Mario Montagud, Sergi Fern\'andez, Sergi Abadal, Xavier Costa-P\'erez
https://arxiv.org/abs/2506.19491

Experimental Assessment of Neural 3D Reconstruction for Small UAV-based Applications
The increasing miniaturization of Unmanned Aerial Vehicles (UAVs) has expanded their deployment potential to indoor and hard-to-reach areas. However, this trend introduces distinct challenges, particularly in terms of flight dynamics and power consumption, which limit the UAVs' autonomy and mission capabilities. This paper presents a novel approach to overcoming these limitations by integrating Neural 3D Reconstruction (N3DR) with small UAV systems for fine-grained 3-Dimensional (3D) digital re…

QISCIT: A validated concept inventory assessment for quantum information science
Kelley Durkin, Manshuo Lin, Michael H. Kolodrubetz, Ryan P. McMahan
https://arxiv.org/abs/2506.17122

QISCIT: A validated concept inventory assessment for quantum information science
Quantum information science (QIS) is a critical interdisciplinary field that requires a well-educated workforce in the near future. Numerous researchers and educators have been actively investigating how to best educate and prepare such a workforce. An open issue has been the lack of a validated tool to asses QIS understanding without requiring college-level math. In this paper, we present the systematic development and content validation of a new assessment instrument called the Quantum Inform…

Deep Learning-Based Semantic Segmentation for Real-Time Kidney Imaging and Measurements with Augmented Reality-Assisted Ultrasound
Gijs Luijten, Roberto Maria Scardigno, Lisle Faray de Paiva, Peter Hoyer, Jens Kleesiek, Domenico Buongiorno, Vitoantonio Bevilacqua, Jan Egger
https://arxiv.org/abs/2506.23721

Deep Learning-Based Semantic Segmentation for Real-Time Kidney Imaging and Measurements with Augmented Reality-Assisted Ultrasound
Ultrasound (US) is widely accessible and radiation-free but has a steep learning curve due to its dynamic nature and non-standard imaging planes. Additionally, the constant need to shift focus between the US screen and the patient poses a challenge. To address these issues, we integrate deep learning (DL)-based semantic segmentation for real-time (RT) automated kidney volumetric measurements, which are essential for clinical assessment but are traditionally time-consuming and prone to fatigue. …

Mesoscale FEM Model of Concrete: Statistical Assessment of Inherent Stress Concentrations in Dependence on Phase Heterogeneity
Jan Ma\v{s}ek (Institute of Physics of Materials, Czech Academy of Sciences, Brno, Czech Republic, Institute of Structural Mechanics, Faculty of Civil Engineering, Brno University of Technology, Brno, Czech Republic), Petr Miarka (Institute of Physics of Materials, Czech Academy of Sciences, Brno, Czech Republic, Institute of Structural Mechanics, Faculty of Ci…

Mesoscale FEM Model of Concrete: Statistical Assessment of Inherent Stress Concentrations in Dependence on Phase Heterogeneity
Concrete heterogeneity originates from its production process, which involves bonding aggregates with a binder matrix. This study presents a mesoscale finite element model (MFEM) that offers detailed insights into the fracture process at the aggregate-cement matrix interface, focusing on one of concrete's key properties: its mechanical response. Unlike discrete models, which often average out critical stress concentrations within the mesostructure, the MFEM approach captures detailed stress dis…

Automatic Depression Assessment using Machine Learning: A Comprehensive Survey
Siyang Song, Yupeng Huo, Shiqing Tang, Jiaee Cheong, Rui Gao, Michel Valstar, Hatice Gunes
https://arxiv.org/abs/2506.18915

Automatic Depression Assessment using Machine Learning: A Comprehensive Survey
Depression is a common mental illness across current human society. Traditional depression assessment relying on inventories and interviews with psychologists frequently suffer from subjective diagnosis results, slow and expensive diagnosis process as well as lack of human resources. Since there is a solid evidence that depression is reflected by various human internal brain activities and external expressive behaviours, early traditional machine learning (ML) and advanced deep learning (DL) mo…

A quantitative assessment of EOG eye tracking during free viewing in sighted and in congenitally blind https://doi.org/10.1016/j.brainres.2025.149794
"Our work further emphasizes the presence of blinks and saccadic muscular movements both in sighted individuals with…

First Reports Are Always Wrong. The Iran Strike Is No Exception. (Mark Hertling/The Bulwark)
https://www.thebulwark.com/p/first-reports-are-always-wrong-iran-strike-nuclear-dia-intelligence-assessment
http://www.memeorandum.com/250625/p71#a250625p71

It would be very interesting to see the RAMS and risk assessment for installing the Butts exhibition at the #WhitechapelGallery.
#Registrar
#RiskAssessment

CodeMorph: Mitigating Data Leakage in Large Language Model Assessment
Hongzhou Rao, Yanjie Zhao, Wenjie Zhu, Ling Xiao, Meizhen Wang, Haoyu Wang
https://arxiv.org/abs/2506.17627

CodeMorph: Mitigating Data Leakage in Large Language Model Assessment
Concerns about benchmark leakage in large language models for code (Code LLMs) have raised issues of data contamination and inflated evaluation metrics. The diversity and inaccessibility of many training datasets make it difficult to prevent data leakage entirely, even with time lag strategies. Consequently, generating new datasets through code perturbation has become essential. However, existing methods often fail to produce complex and diverse variations, struggle with complex cross-file depe…

URGENT-PK: Perceptually-Aligned Ranking Model Designed for Speech Enhancement Competition
Jiahe Wang, Chenda Li, Wei Wang, Wangyou Zhang, Samuele Cornell, Marvin Sach, Robin Scheibler, Kohei Saijo, Yihui Fu, Zhaoheng Ni, Anurag Kumar, Tim Fingscheidt, Shinji Watanabe, Yanmin Qian
https://arxiv.org/abs/2506.23874

URGENT-PK: Perceptually-Aligned Ranking Model Designed for Speech Enhancement Competition
The Mean Opinion Score (MOS) is fundamental to speech quality assessment. However, its acquisition requires significant human annotation. Although deep neural network approaches, such as DNSMOS and UTMOS, have been developed to predict MOS to avoid this issue, they often suffer from insufficient training data. Recognizing that the comparison of speech enhancement (SE) systems prioritizes a reliable system comparison over absolute scores, we propose URGENT-PK, a novel ranking approach leveraging…

Irony. The "land of the free" has driven out a worldwide meeting of #humanists. So much for #religiousfreedom.

Announcing Relocation of the 2026 World Humanist Congress
American Atheists, in close coordination with Humanists International and Humanist Canada, announces the 2026 World Humanist Congress will no longer be held in Washington, D.C., but will instead take place in Ottawa, Canada, August 7-9, 2026. The decision to relocate comes after a thorough assessment of the social, political, and economic environment in the United States under the current administration. Escalating religious nationalism and executive actions restricting movement, targeting civi…

Anti-Phishing Training Does Not Work: A Large-Scale Empirical Assessment of Multi-Modal Training Grounded in the NIST Phish Scale
Andrew T. Rozema, James C. Davis
https://arxiv.org/abs/2506.19899

Anti-Phishing Training Does Not Work: A Large-Scale Empirical Assessment of Multi-Modal Training Grounded in the NIST Phish Scale
Social engineering attacks using email, commonly known as phishing, are a critical cybersecurity threat. Phishing attacks often lead to operational incidents and data breaches. As a result, many organizations allocate a substantial portion of their cybersecurity budgets to phishing awareness training, driven in part by compliance requirements. However, the effectiveness of this training remains in dispute. Empirical evidence of training (in)effectiveness is essential for evidence-based cybersec…

Fine-Grained HDR Image Quality Assessment From Noticeably Distorted to Very High Fidelity
Mohsen Jenadeleh, Jon Sneyers, Davi Lazzarotto, Shima Mohammadi, Dominik Keller, Atanas Boev, Rakesh Rao Ramachandra Rao, Ant\'onio Pinheiro, Thomas Richter, Alexander Raake, Touradj Ebrahimi, Jo\~ao Ascenso, Dietmar Saupe
https://arxiv…

Fine-Grained HDR Image Quality Assessment From Noticeably Distorted to Very High Fidelity
High dynamic range (HDR) and wide color gamut (WCG) technologies significantly improve color reproduction compared to standard dynamic range (SDR) and standard color gamuts, resulting in more accurate, richer, and more immersive images. However, HDR increases data demands, posing challenges for bandwidth efficiency and compression techniques. Advances in compression and display technologies require more precise image quality assessment, particularly in the high-fidelity range where perceptual…

skLEP: A Slovak General Language Understanding Benchmark
Marek \v{S}uppa, Andrej Ridzik, Daniel Hl\'adek, Tom\'a\v{s} Jav\r{u}rek, Vikt\'oria Ondrejov\'a, Krist\'ina S\'asikov\'a, Martin Tamajka, Mari\'an \v{S}imko
https://arxiv.org/abs/2506.21508

skLEP: A Slovak General Language Understanding Benchmark
In this work, we introduce skLEP, the first comprehensive benchmark specifically designed for evaluating Slovak natural language understanding (NLU) models. We have compiled skLEP to encompass nine diverse tasks that span token-level, sentence-pair, and document-level challenges, thereby offering a thorough assessment of model capabilities. To create this benchmark, we curated new, original datasets tailored for Slovak and meticulously translated established English NLU resources. Within this p…

Virtual failure assessment diagrams for hydrogen transmission pipelines
J. Wijnen, J. Parker, M. Gagliano, E. Mart\'inez-Pa\~neda
https://arxiv.org/abs/2506.18554

Virtual failure assessment diagrams for hydrogen transmission pipelines
We combine state-of-the-art thermo-metallurgical welding process modelling with coupled diffusion-elastic-plastic phase field fracture simulations to predict the failure states of hydrogen transport pipelines. This enables quantitatively resolving residual stress states and the role of brittle, hard regions of the weld such as the heat affected zone (HAZ). Failure pressures can be efficiently quantified as a function of asset state (existing defects), materials and weld procedures adopted, and …

FundaQ-8: A Clinically-Inspired Scoring Framework for Automated Fundus Image Quality Assessment
Lee Qi Zun, Oscar Wong Jin Hao, Nor Anita Binti Che Omar, Zalifa Zakiah Binti Asnir, Mohamad Sabri bin Sinal Zainal, Goh Man Fye
https://arxiv.org/abs/2506.20303

FundaQ-8: A Clinically-Inspired Scoring Framework for Automated Fundus Image Quality Assessment
Automated fundus image quality assessment (FIQA) remains a challenge due to variations in image acquisition and subjective expert evaluations. We introduce FundaQ-8, a novel expert-validated framework for systematically assessing fundus image quality using eight critical parameters, including field coverage, anatomical visibility, illumination, and image artifacts. Using FundaQ-8 as a structured scoring reference, we develop a ResNet18-based regression model to predict continuous quality scores…

Libration of Pluto's argument of perihelion and the role of the major planets
Takashi Ito, Renu Malhotra
https://arxiv.org/abs/2505.21821 https://

Libration of Pluto's argument of perihelion and the role of the major planets
Pluto's argument of perihelion is known to librate around $90^\circ$. This libration is related to the secular phenomenon known as the von Zeipel-Lidov-Kozai (vZLK) oscillation. In this work, we make a quantitative assessment of the influence of Neptune's mean motion resonance and of the other giant planets' secular perturbations on the libration of Pluto's argument of perihelion. Here, a parameter $k^2 = (1-e^2) \cos^2 I$ is the key where $e$ is eccentricity and $I$ is inclination. When $k^2$ …

Evaluating Explainability: A Framework for Systematic Assessment and Reporting of Explainable AI Features
Miguel A. Lago, Ghada Zamzmi, Brandon Eich, Jana G. Delfino
https://arxiv.org/abs/2506.13917

Evaluating Explainability: A Framework for Systematic Assessment and Reporting of Explainable AI Features
Explainability features are intended to provide insight into the internal mechanisms of an AI device, but there is a lack of evaluation techniques for assessing the quality of provided explanations. We propose a framework to assess and report explainable AI features. Our evaluation framework for AI explainability is based on four criteria: 1) Consistency quantifies the variability of explanations to similar inputs, 2) Plausibility estimates how close the explanation is to the ground truth, 3) F…

Acoustic scattering AI for non-invasive object classifications: A case study on hair assessment
Long-Vu Hoang, Tuan Nguyen, Tran Huy Dat
https://arxiv.org/abs/2506.14148

Acoustic scattering AI for non-invasive object classifications: A case study on hair assessment
This paper presents a novel non-invasive object classification approach using acoustic scattering, demonstrated through a case study on hair assessment. When an incident wave interacts with an object, it generates a scattered acoustic field encoding structural and material properties. By emitting acoustic stimuli and capturing the scattered signals from head-with-hair-sample objects, we classify hair type and moisture using AI-driven, deep-learning-based sound classification. We benchmark compr…

In New Assessment, C.I.A. Chief Says U.S. Strikes 'Severely Damaged' Iranian Program (New York Times)
https://www.nytimes.com/2025/06/25/us/politics/trump-iran-nuclear.html?unlocked_article_code=1.R08.OzgS.gO8j34Gep6o-&smid=url-share
http://www.memeorandum.com/250626/p19#a250626p19

A Comparison of Bacterial Colonies Count from Petri Dishes Utilizing Hough Transform and Traditional Manual Counting
Areesha Rehman, Zikria Saleem, Jarrar Amjad, Syed Rehan Shah, Kamran Siddique
https://arxiv.org/abs/2505.20365

A Comparison of Bacterial Colonies Count from Petri Dishes Utilizing Hough Transform and Traditional Manual Counting
Bacterial colony enumeration is an essential stage in microbiological research, allowing susceptibility to antibiotics assessment, monitoring of the environment, and clinical diagnostics. Traditional manual counting methods are costly and susceptible to human mistakes, prompting the creation of automated detection systems. This research compares the efficacy of the Hough Circle Transform method for automated colony detection to hand counting of E. coli, S. aureus, and P. aeruginosa colonies on …

This https://arxiv.org/abs/2505.12485 has been replaced.
initial toot: https://mastoxiv.page/@arX…

A Reduced-Order CFD Approach for Intermediate grade Coronary Arterial Clinical Parameter Assessment A Reduced-Order CFD Approach for Intermediate grade Coronary Arterial Clinical Parameter Assessment
Coronary heart disease (CHD) remains a top reason of mortality worldwide. This study introduces a novel approach by integrating patient-specific Multi-slice CT scans into CAD models and employing a one-dimensional numerical framework to assess varying degrees of stenosis. The computational analysis encompasses the entire arterial tree, with a particular focus on stenosed coronary arteries modelled using an analytical equation. One-dimensional characteristic equations, utilizing forward and back…

lcpy: an open-source python package for parametric and dynamic Life Cycle Assessment and Life Cycle Costing
Spiros Gkousis, Evina Katsou
https://arxiv.org/abs/2506.13744

lcpy: an open-source python package for parametric and dynamic Life Cycle Assessment and Life Cycle Costing
This article describes lcpy, an open-source python package that allows for advanced parametric Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) analysis. The package is designed to allow the user to model a process with a flexible, modular design based on dictionaries and lists. The modeling can consider in-time variations, uncertainty, and allows for dynamic analysis, uncertainty assessment, as well as conventional static LCA and LCC. The package is compatible with optimization and unc…

Security Assessment of DeepSeek and GPT Series Models against Jailbreak Attacks
Xiaodong Wu, Xiangman Li, Jianbing Ni
https://arxiv.org/abs/2506.18543 http…

Security Assessment of DeepSeek and GPT Series Models against Jailbreak Attacks
The widespread deployment of large language models (LLMs) has raised critical concerns over their vulnerability to jailbreak attacks, i.e., adversarial prompts that bypass alignment mechanisms and elicit harmful or policy-violating outputs. While proprietary models like GPT-4 have undergone extensive evaluation, the robustness of emerging open-source alternatives such as DeepSeek remains largely underexplored, despite their growing adoption in real-world applications. In this paper, we present …

Quantum Radar and Research Assessment
Gaspare Galati, Gabriele Pavan, Frederick Daum
https://arxiv.org/abs/2506.13797 https://arxiv.o…

Quantum Radar and Research Assessment
Quantum Radar was studied in many Nations for about fifteen years with the production of some hundred publications. In the post 2020 literature, it is shown that, due to the exceedingly low transmitted power, Quantum Radar cannot produce neither significant results nor real world applications. Regrettably, most of the scientific community ignored this negative outcome: a fact worth of exam. A detailed study of such an assessment failure depicts the main shortcomings of the present situation, ca…

AI-assisted radiographic analysis in detecting alveolar bone-loss severity and patterns
Chathura Wimalasiri, Piumal Rathnayake, Shamod Wijerathne, Sumudu Rasnayaka, Dhanushka Leuke Bandara, Roshan Ragel, Vajira Thambawita, Isuru Nawinne
https://arxiv.org/abs/2506.20522

AI-assisted radiographic analysis in detecting alveolar bone-loss severity and patterns
Periodontitis, a chronic inflammatory disease causing alveolar bone loss, significantly affects oral health and quality of life. Accurate assessment of bone loss severity and pattern is critical for diagnosis and treatment planning. In this study, we propose a novel AI-based deep learning framework to automatically detect and quantify alveolar bone loss and its patterns using intraoral periapical (IOPA) radiographs. Our method combines YOLOv8 for tooth detection with Keypoint R-CNN models to id…

VulStamp: Vulnerability Assessment using Large Language Model
Haoshen, Ming Hu, Xiaofei Xie, Jiaye Li, Mingsong Chen
https://arxiv.org/abs/2506.11484 https…

VulStamp: Vulnerability Assessment using Large Language Model
Although modern vulnerability detection tools enable developers to efficiently identify numerous security flaws, indiscriminate remediation efforts often lead to superfluous development expenses. This is particularly true given that a substantial portion of detected vulnerabilities either possess low exploitability or would incur negligible impact in practical operational environments. Consequently, vulnerability severity assessment has emerged as a critical component in optimizing software dev…

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment
Siqiao Li, Chen Hui, Wei Zhang, Rui Liang, Chenyue Song, Feng Jiang, Haiqi Zhu, Zhixuan Li, Hong Huang, Xiang Li
https://arxiv.org/abs/2506.20200

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment
Positron Emission Tomography / Computed Tomography (PET/CT) plays a critical role in medical imaging, combining functional and anatomical information to aid in accurate diagnosis. However, image quality degradation due to noise, compression and other factors could potentially lead to diagnostic uncertainty and increase the risk of misdiagnosis. When evaluating the quality of a PET/CT image, both low-level features like distortions and high-level features like organ anatomical structures affect …

Error-Guided Pose Augmentation: Enhancing Rehabilitation Exercise Assessment through Targeted Data Generation
Omar Sherif, Ali Hamdi
https://arxiv.org/abs/2506.09833

Error-Guided Pose Augmentation: Enhancing Rehabilitation Exercise Assessment through Targeted Data Generation
Effective rehabilitation assessment is essential for monitoring patient progress, particularly in home-based settings. Existing systems often face challenges such as data imbalance and difficulty detecting subtle movement errors. This paper introduces Error-Guided Pose Augmentation (EGPA), a method that generates synthetic skeleton data by simulating clinically relevant movement mistakes. Unlike standard augmentation techniques, EGPA targets biomechanical errors observed in rehabilitation. Comb…

Trump throws Gabbard under the bus -- again (Eli Stokols/Politico)
https://www.politico.com/news/2025/06/20/trump-gabbard-dismiss-iran-assessment-00415805
http://www.memeorandum.com/250621/p5#a250621p5

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment
Wei Wang, Wangyou Zhang, Chenda Li, Jiatong Shi, Shinji Watanabe, Yanmin Qian
https://arxiv.org/abs/2506.12260

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment
Speech quality assessment (SQA) aims to predict the perceived quality of speech signals under a wide range of distortions. It is inherently connected to speech enhancement (SE), which seeks to improve speech quality by removing unwanted signal components. While SQA models are widely used to evaluate SE performance, their potential to guide SE training remains underexplored. In this work, we investigate a training framework that leverages a SQA model, trained to predict multiple evaluation metri…

A Question Bank to Assess AI Inclusivity: Mapping out the Journey from Diversity Errors to Inclusion Excellence
Rifat Ara Shams, Didar Zowghi, Muneera Bano
https://arxiv.org/abs/2506.18538

A Question Bank to Assess AI Inclusivity: Mapping out the Journey from Diversity Errors to Inclusion Excellence
Ensuring diversity and inclusion (D&I) in artificial intelligence (AI) is crucial for mitigating biases and promoting equitable decision-making. However, existing AI risk assessment frameworks often overlook inclusivity, lacking standardized tools to measure an AI system's alignment with D&I principles. This paper introduces a structured AI inclusivity question bank, a comprehensive set of 253 questions designed to evaluate AI inclusivity across five pillars: Humans, Data, Process, System, and …

Accelerating Delta Debugging through Probabilistic Monotonicity Assessment
Yonggang Tao, Jingling Xue
https://arxiv.org/abs/2506.11614 https://

Accelerating Delta Debugging through Probabilistic Monotonicity Assessment
Delta debugging assumes search space monotonicity: if a program causes a failure, any supersets of that program will also induce the same failure, permitting the exclusion of subsets of non-failure-inducing programs. However, this assumption does not always hold in practice. This paper introduces Probabilistic Monotonicity Assessment (PMA), enhancing the efficiency of DDMIN-style algorithms without sacrificing effectiveness. PMA dynamically models and assesses the search space's monotonicity ba…

Enhanced Dermatology Image Quality Assessment via Cross-Domain Training
Ignacio Hern\'andez Montilla, Alfonso Medela, Paola Pasquali, Andy Aguilar, Taig Mac Carthy, Gerardo Fern\'andez, Antonio Martorell, Enrique Onieva
https://arxiv.org/abs/2506.16116

Enhanced Dermatology Image Quality Assessment via Cross-Domain Training
Teledermatology has become a widely accepted communication method in daily clinical practice, enabling remote care while showing strong agreement with in-person visits. Poor image quality remains an unsolved problem in teledermatology and is a major concern to practitioners, as bad-quality images reduce the usefulness of the remote consultation process. However, research on Image Quality Assessment (IQA) in dermatology is sparse, and does not leverage the latest advances in non-dermatology IQA,…

Effect of Haptic Feedback on Avoidance Behavior and Visual Exploration in Dynamic VR Pedestrian Environment
Kyosuke Ishibashi, Atsushi Saito, Zin Y. Tun, Lucas Ray, Megan C. Coram, Akihiro Sakurai, Allison M. Okamura, Ko Yamamoto
https://arxiv.org/abs/2506.20952

Effect of Haptic Feedback on Avoidance Behavior and Visual Exploration in Dynamic VR Pedestrian Environment
Human crowd simulation in virtual reality (VR) is a powerful tool with potential applications including emergency evacuation training and assessment of building layout. While haptic feedback in VR enhances immersive experience, its effect on walking behavior in dense and dynamic pedestrian flows is unknown. Through a user study, we investigated how haptic feedback changes user walking motion in crowded pedestrian flows in VR. The results indicate that haptic feedback changed users' collision av…

This https://arxiv.org/abs/2410.12675 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

AttentiveMOS: A Lightweight Attention-Only Model for Speech Quality Prediction
Research in modeling subjective metrics for quality assessment has led to the development of no-reference speech models that directly operate on utterance waveforms to predict the Mean Opinion Score (MOS). These models often rely on convolutional layers for local feature extraction and embeddings from impractically large pretrained networks to enhance generalization. We propose an attention-only model based on Swin transformer and standard transformer layers to extract local context features an…

Quality Assessment of Python Tests Generated by Large Language Models
Victor Alves, Carla Bezerra, Ivan Machado, Larissa Rocha, T\'assio Virg\'inio, Publio Silva
https://arxiv.org/abs/2506.14297

Quality Assessment of Python Tests Generated by Large Language Models
The manual generation of test scripts is a time-intensive, costly, and error-prone process, indicating the value of automated solutions. Large Language Models (LLMs) have shown great promise in this domain, leveraging their extensive knowledge to produce test code more efficiently. This study investigates the quality of Python test code generated by three LLMs: GPT-4o, Amazon Q, and LLama 3.3. We evaluate the structural reliability of test suites generated under two distinct prompt contexts: Te…

(AI peers) are people learning from the same standpoint: Perception of AI characters in a Collaborative Science Investigation
Eunhye Grace Ko, Soo Hyoung Joo
https://arxiv.org/abs/2506.06165

(AI peers) are people learning from the same standpoint: Perception of AI characters in a Collaborative Science Investigation
While the complexity of 21st-century demands has promoted pedagogical approaches to foster complex competencies, a persistent gap remains between in-class learning activities and individualized learning or assessment practices. To address this, studies have explored the use of AI-generated characters in learning and assessment. One attempt is scenario-based assessment (SBA), a technique that not only measures but also fosters the development of competencies throughout the assessment process. SB…

Comparison of ConvNeXt and Vision-Language Models for Breast Density Assessment in Screening Mammography
Yusdivia Molina-Rom\'an, David G\'omez-Ortiz, Ernestina Menasalvas-Ruiz, Jos\'e Gerardo Tamez-Pe\~na, Alejandro Santos-D\'iaz
https://arxiv.org/abs/2506.13964

Comparison of ConvNeXt and Vision-Language Models for Breast Density Assessment in Screening Mammography
Mammographic breast density classification is essential for cancer risk assessment but remains challenging due to subjective interpretation and inter-observer variability. This study compares multimodal and CNN-based methods for automated classification using the BI-RADS system, evaluating BioMedCLIP and ConvNeXt across three learning scenarios: zero-shot classification, linear probing with textual descriptions, and fine-tuning with numerical labels. Results show that zero-shot classification a…

StreetLens: Enabling Human-Centered AI Agents for Neighborhood Assessment from Street View Imagery
Jina Kim, Leeje Jang, Yao-Yi Chiang, Guanyu Wang, Michelle Pasco
https://arxiv.org/abs/2506.14670

StreetLens: Enabling Human-Centered AI Agents for Neighborhood Assessment from Street View Imagery
Traditionally, neighborhood studies have employed interviews, surveys, and manual image annotation guided by detailed protocols to identify environmental characteristics, including physical disorder, decay, street safety, and sociocultural symbols, and to examine their impact on developmental and health outcomes. While these methods yield rich insights, they are time-consuming and require intensive expert intervention. Recent technological advances, including vision-language models (VLMs), have…

UniMind: Unleashing the Power of LLMs for Unified Multi-Task Brain Decoding
Weiheng Lu, Chunfeng Song, Jiamin Wu, Pengyu Zhu, Yuchen Zhou, Weijian Mai, Qihao Zheng, Wanli Ouyang
https://arxiv.org/abs/2506.18962

UniMind: Unleashing the Power of LLMs for Unified Multi-Task Brain Decoding
Decoding human brain activity from electroencephalography (EEG) signals is a central challenge at the intersection of neuroscience and artificial intelligence, enabling diverse applications in mental state assessment, clinical monitoring, and human-machine interaction. Recent efforts have extensively explored EEG-based brain foundation models for generalized brain decoding, employing large-scale training on multiple datasets. However, most of these attempts struggle with generalizability and fa…

Volumetric segmentation of muscle compartments using in vivo imaging and architectural validation in human finger flexors
Yang Li
https://arxiv.org/abs/2506.20206

Volumetric segmentation of muscle compartments using in vivo imaging and architectural validation in human finger flexors
Segmenting muscle compartments and measuring their architecture can facilitate movement function assessment, accurate musculoskeletal modeling, and synergy-based electromyogram simulation. Here, we presented a novel method for volumetric segmentation of muscle compartments using in vivo imaging, focusing on the independent compartments for finger control of flexor digitorum superficialis (FDS). Besides, we measured the architectural properties of FDS compartments and validated the segmentation.…

Opportunistic Osteoporosis Diagnosis via Texture-Preserving Self-Supervision, Mixture of Experts and Multi-Task Integration
Jiaxing Huang, Heng Guo, Le Lu, Fan Yang, Minfeng Xu, Ge Yang, Wei Luo
https://arxiv.org/abs/2506.20282

Opportunistic Osteoporosis Diagnosis via Texture-Preserving Self-Supervision, Mixture of Experts and Multi-Task Integration
Osteoporosis, characterized by reduced bone mineral density (BMD) and compromised bone microstructure, increases fracture risk in aging populations. While dual-energy X-ray absorptiometry (DXA) is the clinical standard for BMD assessment, its limited accessibility hinders diagnosis in resource-limited regions. Opportunistic computed tomography (CT) analysis has emerged as a promising alternative for osteoporosis diagnosis using existing imaging data. Current approaches, however, face three limi…