Tootfinder

Basis Theory, which provides data management and payments infrastructure tools, raised a $33M Series B led by Costanoa, taking its total funding to $50M (David Penn/Finovate)
https://finovate.com/data-privacy-management-software-provider-basis-…

Data Privacy Management Software Provider Basis Theory Secures $33 Million - Finovate
Data management innovator Basis Theory has secured $33 million in Series B funding.

If you're interested in the unique intersection of developing for #Apple platforms - but also being able to enable other people globally to use Apple devices at their own place of work or school - you should come work in my org:
https://jobs.apple.com/en-us/details/200620469/software-engineer-in-enterprise-and-education-technologies
https://jobs.apple.com/en-us/details/200621098/software-development-engineer-device-management
https://jobs.apple.com/en-us/details/200621115/software-development-engineering-manager-device-management

more and more, I think some people could really use an Emergency Management Hologram who just pops up and says "Please state the nature of this management emergency — actually nevermind, that won't change my advice: please go talk to a therapist, and then talk to this person you were about to tell me about"

Modular, On-Site Solutions with Lightweight Anomaly Detection for Sustainable Nutrient Management in Agriculture
Abigail R. Cohen, Yuming Sun, Zhihao Qin, Harsh S. Muriki, Zihao Xiao, Yeonju Lee, Matthew Housley, Andrew F. Sharkey, Rhuanito S. Ferrarezi, Jing Li, Lu Gan, Yongsheng Chen
https://arxiv.org/abs/2509.12247

Modular, On-Site Solutions with Lightweight Anomaly Detection for Sustainable Nutrient Management in Agriculture
Efficient nutrient management is critical for crop growth and sustainable resource consumption (e.g., nitrogen, energy). Current approaches require lengthy analyses, preventing real-time optimization; similarly, imaging facilitates rapid phenotyping but can be computationally intensive, preventing deployment under resource constraints. This study proposes a flexible, tiered pipeline for anomaly detection and status estimation (fresh weight, dry mass, and tissue nutrients), including a comprehen…

Optimal CO2 storage management considering safety constraints in multi-stakeholder multi-site CCS projects: a game theoretic perspective
Jungang Chen, Seyyed A. Hosseini
https://arxiv.org/abs/2508.11618

Optimal CO2 storage management considering safety constraints in multi-stakeholder multi-site CCS projects: a game theoretic perspective
Carbon capture and storage (CCS) projects typically involve a diverse array of stakeholders or players from public, private, and regulatory sectors, each with different objectives and responsibilities. Given the complexity, scale, and long-term nature of CCS operations, determining whether individual stakeholders can independently maximize their interests or whether collaborative coalition agreements are needed remains a central question for effective CCS project planning and management. CCS pr…

InfraMind: A Novel Exploration-based GUI Agentic Framework for Mission-critical Industrial Management
Liangtao Lin, Zhaomeng Zhu, Tianwei Zhang, Yonggang Wen
https://arxiv.org/abs/2509.13704

InfraMind: A Novel Exploration-based GUI Agentic Framework for Mission-critical Industrial Management
Mission-critical industrial infrastructure, such as data centers, increasingly depends on complex management software. Its operations, however, pose significant challenges due to the escalating system complexity, multi-vendor integration, and a shortage of expert operators. While Robotic Process Automation (RPA) offers partial automation through handcrafted scripts, it suffers from limited flexibility and high maintenance costs. Recent advances in Large Language Model (LLM)-based graphical user…

Myopic Optimality: why reinforcement learning portfolio management strategies lose money
Yuming Ma
https://arxiv.org/abs/2509.12764 https://arxiv.org/pdf/2…

Myopic Optimality: why reinforcement learning portfolio management strategies lose money
Myopic optimization (MO) outperforms reinforcement learning (RL) in portfolio management: RL yields lower or negative returns, higher variance, larger costs, heavier CVaR, lower profitability, and greater model risk. We model execution/liquidation frictions with mark-to-market accounting. Using Malliavin calculus (Clark-Ocone/BEL), we derive policy gradients and risk shadow price, unifying HJB and KKT. This gives dual gap and convergence results: geometric MO vs. RL floors. We quantify phantom …

Shoddy excuse 2: “Maybe it was her personal device but she shouldn’t have agreed to let the employer install remote management software”
Could she really say no to such a demand? Not everyone has the power to refuse a coercive demand from an employer. There should be a strong legal firewall around employer demands to surveil people’s lives. And there should be mechanisms for an employee who is met with such demands to put the brakes on their employer.
I realize the word “should” is doing a lot of work there, but let’s at least be clear about how wrong that situation would be.
3/

'Trump management'
De term voor 2025?
(Uit Nieuwsuur)

Who Uses Whose Telescopes? Analyzing the Knowledge Geography and Research Dominance of Global Astronomical Facilities
Yue Chen (Institute of Science of Science,S&T Management,WISE Lab, Dalian University of Technology), Yuqi Wang (Institute of Science of Science,S&T Management,WISE Lab, Dalian University of Technology), Yuying Gao (Institute of Science of Science,S&T Management,WISE Lab, Dalian University of Technology), Zhiqi Wang (Institute of Science of Science,S&T Ma…

Who Uses Whose Telescopes? Analyzing the Knowledge Geography and Research Dominance of Global Astronomical Facilities
Large-scale research infrastructures (LSRIs) are central to contemporary science policy, combining massive capital investments with international access regimes. Yet whether open access to these infrastructures translates into more equitable scientific authority remains contested. Astronomy provides a critical case: world-leading observatories are globally shared but embedded in specific national contexts. We compile a novel country--year dataset (1955--2025) linking the location of astronomica…

A group of 60 Netflix Animation Studios workers requested voluntary union recognition from management as they seek to unionize the Animation Guild (Katie Kilkenny/The Hollywood Reporter)
https://www.hollywoodreporter.com/business

Netflix Animation Studios and ‘Ted’ Series Production Workers Launch Unionization Drives
The staffers are attempting to join the Animation Guild, which continues to organize aggressively inside the production space.

Validation of Dry Bulk Pile Volume Estimation Algorithm based on Angle of Repose using Experimental Images
Madhu Koirala, P{\aa}l Gunnar Ellingsen, Ashenafi Zebene Woldaregay
https://arxiv.org/abs/2509.13890

Validation of Dry Bulk Pile Volume Estimation Algorithm based on Angle of Repose using Experimental Images
Estimation of volume of piles in shipping ports plays a pivotal role for logistics management, facilitates better ship rescheduling and rerouting for economic benefits and contributes to overall efficient shipping management. This paper presents validation results for a volume estimation algorithm for dry bulk cargo piles stored in open ports. Using remote sensing images obtained in a laboratory setting, the method first detects the contour of the pile and then reconstructs its 3D model based o…

Risk-Based Prognostics and Health Management
John W. Sheppard
https://arxiv.org/abs/2508.11031 https://arxiv.org/pdf/2508.11031

Risk-Based Prognostics and Health Management
It is often the case that risk assessment and prognostics are viewed as related but separate tasks. This chapter describes a risk-based approach to prognostics that seeks to provide a tighter coupling between risk assessment and fault prediction. We show how this can be achieved using the continuous-time Bayesian network as the underlying modeling framework. Furthermore, we provide an overview of the techniques that are available to derive these models from data and show how they might be used …

Nach Abgang von Jeff Williams: Apple baut Management um
Einem Bericht zufolge gibt es Veränderungen in Apples Dienstebereich. Fitness und Gesundheit werden in einem neuen Bereich angesiedelt.
https://www.

"Federal regulators have rescinded a set of guidelines for large banking institutions to consider the financial dangers of the climate crisis when making decisions about business strategy, risk management, and strategic planning."
Fed accused of putting 'financial system at risk' with new 'capitulation' - Raw Story
https://www.rawstory.com/federal-reserve-2674210146/

Time-Based State-Management of Hash-Based Signature CAs for VPN-Authentication
Daniel Herzinger, Linus Heise, Daniel Loebenberger, Matthias S\"ollner
https://arxiv.org/abs/2509.11695

Time-Based State-Management of Hash-Based Signature CAs for VPN-Authentication
Advances in quantum computing necessitate migrating the entire technology stack to post-quantum cryptography. This includes IPsec-based VPN connection authentication. Although there is an RFC draft for post-quantum authentication in this setting, the draft does not consider (stateful) hash-based signatures despite their small signature size and trusted long-term security. We propose a design with time-based state-management that assigns VPN devices a certificate authority (CA) based on the ha…

AI Asset Management for Manufacturing (AIM4M): Development of a Process Model for Operationalization
Lukas Rauh, Mel-Rick S\"uner, Daniel Schel, Thomas Bauernhansl
https://arxiv.org/abs/2509.11691

AI Asset Management for Manufacturing (AIM4M): Development of a Process Model for Operationalization
The benefits of adopting artificial intelligence (AI) in manufacturing are undeniable. However, operationalizing AI beyond the prototype, especially when involved with cyber-physical production systems (CPPS), remains a significant challenge due to the technical system complexity, a lack of implementation standards and fragmented organizational processes. To this end, this paper proposes a new process model for the lifecycle management of AI assets designed to address challenges in manufacturin…

« Tous se préparent Š l’après-thermique. »
This post by the Brussels DSO features a nice neologism.
One third of capacity increase requests by non-residential users in the Brussels region are for EV charging. In my opinion, this also suggests a huge potential for smarter energy management.

Pourquoi les entreprises bruxelloises demandent-elles plus de #puissance électrique ? | Sibelga
Pourquoi les entreprises bruxelloises demandent-elles plus de #puissance électrique ? La réponse tient en 2 mots : mobilité électrique ! Chaque jour, nous recevons des demandes de renforcement du réseau. Et dans plus d'1/3 des cas, c’est pour installer des #bornes de recharge pour véhicules électriques. Les Cliniques universitaires Saint-Luc, la prison de Haren, le site Mercedes… Tous se préparent à l’après-thermique. Chez Sibelga, la transition vers une mobilité durable et…

sci pol; NZ pol
ICYMI Another handbrake turn in research management, this time Aotearoa New Zealand under Christopher Luxon's National party coalition.
"New Zealand’s largest source of funding through competitive grants, the Endeavour Fund, remains stagnant at NZ$245 million but has *canceled all applications for the 2026 funding round to “reduce the operational burden of applying for funding”* during the mergers of Crown Research Institutes."
➡️ #NZ #researchfunding #SciPol

Weekend Reads
* How AI can help cybersecurity
https://www.foreignaffairs.com/guest-pass/redeem/Jh1vJ6PqTwc
* Notes on active queue management

The End of Cybersecurity
America’s digital defenses are failing—but AI can save them.

BuildingGym: An open-source toolbox for AI-based building energy management using reinforcement learning
Xilei Dai, Ruotian Chen, Songze Guan, Wen-Tai Li, Chau Yuen
https://arxiv.org/abs/2509.11922

BuildingGym: An open-source toolbox for AI-based building energy management using reinforcement learning
Reinforcement learning (RL) has proven effective for AI-based building energy management. However, there is a lack of flexible framework to implement RL across various control problems in building energy management. To address this gap, we propose BuildingGym, an open-source tool designed as a research-friendly and flexible framework for training RL control strategies for common challenges in building energy management. BuildingGym integrates EnergyPlus as its core simulator, making it suitable…

It feels so good to support a new manager in navigating management challenges and hard conversations, to hear their ideas and goals and values, and to show them how they can affirm their values in their management practices
I'm so glad to be able to help someone go from self-awareness of how they might fall into classic bad management traps, to building their toolkit of actions and techniques they can use to counter their tendencies and instead balance empathetic and accountable le…

GFS: A Preemption-aware Scheduling Framework for GPU Clusters with Predictive Spot Instance Management
Jiaang Duan, Shenglin Xu, Shiyou Qian, Dingyu Yang, Kangjin Wang, Chenzhi Liao, Yinghao Yu, Qin Hua, Hanwen Hu, Qi Wang, Wenchao Wu, Dongqing Bao, Tianyu Lu, Jian Cao, Guangtao Xue, Guodong Yang, Liping Zhang, Gang Chen
https://arxiv.org/…

GFS: A Preemption-aware Scheduling Framework for GPU Clusters with Predictive Spot Instance Management
The surge in large language models (LLMs) has fundamentally reshaped the landscape of GPU usage patterns, creating an urgent need for more efficient management strategies. While cloud providers employ spot instances to reduce costs for low-priority (LP) tasks, existing schedulers still grapple with high eviction rates and lengthy queuing times. To address these limitations, we present GFS, a novel preemptive scheduling framework that enhances service-level objective (SLO) compliance for high-pr…

Crosslisted article(s) found for q-fin.RM. https://arxiv.org/list/q-fin.RM/new
[1/1]:
- Myopic Optimality: why reinforcement learning portfolio management strategies lose money
Yuming Ma

Crosslisted article(s) found for q-fin.PM. https://arxiv.org/list/q-fin.PM/new
[1/1]:
- Myopic Optimality: why reinforcement learning portfolio management strategies lose money
Yuming Ma

Energy-Aware Data Center Management: A Sustainable Approach to Reducing Carbon Footprint
Rabab Khan Rongon, Krishna Das
https://arxiv.org/abs/2509.10462 https://

Energy-Aware Data Center Management: A Sustainable Approach to Reducing Carbon Footprint
The rapid expansion of cloud computing and data center infrastructure has led to significant energy consumption, posing environmental challenges due to the growing carbon footprint. This research explores energy-aware management strategies aimed at creating sustainable data center operations. By integrating advanced energy-efficient technologies and optimizing resource utilization, this study proposes a framework to minimize power usage while maintaining high performance. Key elements include d…

2 @… Workshops zu:
🔹 #LibraryAssessment #Bibliometrie
24. Sept. & 8. Okt., 09:30–13:00 Uhr
- Strategische Steuerung
- …

Activist investor Elliott announces a $2B stake in Workday and says the company's new multi-year plan will drive "substantial long-term value creation" (Ashley Capoot/CNBC)
https://www.cnbc.com/2025/09/17/workday-stock-elliott-activist.html

Workday stock climbs as activist investor Elliott takes $2 billion stake
Elliott Investment Management announced it a $2 billion stake in Workday.

Synthesizing Behaviorally-Grounded Reasoning Chains: A Data-Generation Framework for Personal Finance LLMs
Akhil Theerthala
https://arxiv.org/abs/2509.14180 https://

Synthesizing Behaviorally-Grounded Reasoning Chains: A Data-Generation Framework for Personal Finance LLMs
Personalized financial advice requires consideration of user goals, constraints, risk tolerance, and jurisdiction. Prior LLM work has focused on support systems for investors and financial planners. Simultaneously, numerous recent studies examine broader personal finance tasks, including budgeting, debt management, retirement, and estate planning, through agentic pipelines that incur high maintenance costs, yielding less than 25% of their expected financial returns. In this study, we introduce …

Judge blocks shutdown layoffs after finding Trump's actions are likely illegal (Eric Katz/GovExec.com)
https://www.govexec.com/management/2025/10/judge-blocks-shutdown-layoffs-after-finding-trumps-actions-are-likely-illegal/408828/
http://www.memeorandum.com/251015/p104#a251015p104

The Alliance for International Exchange told Newsweek that it had learned that the Office of Management and Budget (OMB)
🆘 had decided to cut at least 22 offerings from the Bureau of Educational and Cultural Affairs (ECA)
totaling around $100 million in annual funding.
"While this does not impact flagship programs like Fulbright, Gilman, and IVLP at the moment,
it sets a dangerous precedent," Mark Overmann, executive director of the Alliance, told Newsweek. …

Fears Over Fulbright's Future as Trump Admin Cuts Exchange Programs
Funding for over 20 programs was reported to have been cut, leaving participants in limbo.

"you have to try to build that strong organizational structure; one that isn’t so fragile that when one or two senior leaders change, things fall apart. But it’s very difficult and many organizations have weak management systems..."
https://

Swarm-in-Blocks: Simplifying Drone Swarm Programming with Block-Based Language
Agnes Bressan de Almeida, Joao Aires Correa Fernandes Marsicano
https://arxiv.org/abs/2508.11498 h…

Swarm-in-Blocks: Simplifying Drone Swarm Programming with Block-Based Language
Swarm in Blocks, originally developed for CopterHack 2022, is a high-level interface that simplifies drone swarm programming using a block-based language. Building on the Clover platform, this tool enables users to create functionalities like loops and conditional structures by assembling code blocks. In 2023, we introduced Swarm in Blocks 2.0, further refining the platform to address the complexities of swarm management in a user-friendly way. As drone swarm applications grow in areas like del…

🐝 Organic beekeeping can be even more profitable than conventional methods
#business

Organic beekeeping can be even more profitable than conventional methods
Organic beekeeping can support healthy and productive honey bee colonies, and a new study led by researchers in Penn State's College of Agricultural Sciences has found that adopting organic honey bee colony management is not only profitable, but in some cases, it can be even more profitable than conventional management.

“Personality vs. Personalization” in AI Systems: Responsible Design and Risk Management (Part 4)
https://fpf.org/blog/personality-vs-personalization-in-ai-systems-responsible-design-and-risk-management-part-4/

NASA’s Management of the #Dragonfly Project: https://oig.nasa.gov/office-of-inspector-general-oig/audit-reports/nasas-management-of-the-dragonfly-project/ -> After early struggles, NASA’s ambitious mission to Titan is “on track” for launch: https://arstechnica.com/space/2025/09/after-early-struggles-nasas-ambitious-mission-to-titan-is-on-track-for-launch/ -> "A new independent report finds that although NASA's ambitious mission to fly across the surface of Titan is delayed and over budget, the fault is due to the space agency's management rather than the program itself."

Sources: Paramount Skydance plans to begin mass layoffs the week of October 27, cutting around 2,000 US jobs as part of its $2B cost-cutting initiative (Todd Spangler/Variety)
https://variety.com/2025/tv/news/paramount-skydance-mass-layoffs-date-oct-2…

Paramount Skydance Mass Layoffs to Start Week of Oct. 27
Paramount Skydance will lay off about 2,000 U.S. employees under David Ellison's new management regime starting the week of Oct. 27.

Irregular Reminder: Intune is SHIT for macOS Management

Tabularis Formatus: Predictive Formatting for Tables
Mukul Singh, Jos\'e Cambronero, Sumit Gulwani, Vu Le, Gust Verbruggen
https://arxiv.org/abs/2508.11121 https://

Tabularis Formatus: Predictive Formatting for Tables
Spreadsheet manipulation software are widely used for data management and analysis of tabular data, yet the creation of conditional formatting (CF) rules remains a complex task requiring technical knowledge and experience with specific platforms. In this paper we present TaFo, a neuro-symbolic approach to generating CF suggestions for tables, addressing common challenges such as user unawareness, difficulty in rule creation, and inadequate user interfaces. TaFo takes inspiration from component …

Bellman Optimality of Average-Reward Robust Markov Decision Processes with a Constant Gain
Shengbo Wang, Nian Si
https://arxiv.org/abs/2509.14203 https://a…

Bellman Optimality of Average-Reward Robust Markov Decision Processes with a Constant Gain
Learning and optimal control under robust Markov decision processes (MDPs) have received increasing attention, yet most existing theory, algorithms, and applications focus on finite-horizon or discounted models. The average-reward formulation, while natural in many operations research and management contexts, remains underexplored. This is primarily because the dynamic programming foundations are technically challenging and only partially understood, with several fundamental questions remaining…

Federated Multi-Agent Reinforcement Learning for Privacy-Preserving and Energy-Aware Resource Management in 6G Edge Networks
Francisco Javier Esono Nkulu Andong, Qi Min
https://arxiv.org/abs/2509.10163

Federated Multi-Agent Reinforcement Learning for Privacy-Preserving and Energy-Aware Resource Management in 6G Edge Networks
As sixth-generation (6G) networks move toward ultra-dense, intelligent edge environments, efficient resource management under stringent privacy, mobility, and energy constraints becomes critical. This paper introduces a novel Federated Multi-Agent Reinforcement Learning (Fed-MARL) framework that incorporates cross-layer orchestration of both the MAC layer and application layer for energy-efficient, privacy-preserving, and real-time resource management across heterogeneous edge devices. Each age…

Generalizable Blood Pressure Estimation from Multi-Wavelength PPG Using Curriculum-Adversarial Learning
Zequan Liang, Ruoyu Zhang, Wei Shao, Mahdi Pirayesh Shirazi Nejad, Ehsan Kourkchi, Setareh Rafatirad, Houman Homayoun
https://arxiv.org/abs/2509.12518

Generalizable Blood Pressure Estimation from Multi-Wavelength PPG Using Curriculum-Adversarial Learning
Accurate and generalizable blood pressure (BP) estimation is vital for the early detection and management of cardiovascular diseases. In this study, we enforce subject-level data splitting on a public multi-wavelength photoplethysmography (PPG) dataset and propose a generalizable BP estimation framework based on curriculum-adversarial learning. Our approach combines curriculum learning, which transitions from hypertension classification to BP regression, with domain-adversarial training that co…

On Condensation Management - Learn how you can best avoid problems with condensation, damp and mould in winter. #mould #condensation #ventilation -

On Condensation Management
Learn how you can best avoid problems with condensation, damp and mould in winter. #mould #condensation #ventilation

Handows: A Palm-Based Interactive Multi-Window Management System in Virtual Reality
Jindu Wang, Ke Zhou, Haoyu Ren, Per Ola Kristensson, Xiang Li
https://arxiv.org/abs/2508.09469

Handows: A Palm-Based Interactive Multi-Window Management System in Virtual Reality
Window management in virtual reality (VR) remains a challenging task due to the spatial complexity and physical demands of current interaction methods. We introduce Handows, a palm-based interface that enables direct manipulation of spatial windows through familiar smartphone-inspired gestures on the user's non-dominant hand. Combining ergonomic layout design with body-centric input and passive haptics, Handows supports four core operations: window selection, closure, positioning, and scaling. …

@… Some say they did top down management, but that can’t be because they definitely did them bottom up.

Comprehensive Evaluation of CNN-Based Audio Tagging Models on Resource-Constrained Devices
Jordi Grau-Haro, Ruben Ribes-Serrano, Javier Naranjo-Alcazar, Marta Garcia-Ballesteros, Pedro Zuccarello
https://arxiv.org/abs/2509.14049

Comprehensive Evaluation of CNN-Based Audio Tagging Models on Resource-Constrained Devices
Convolutional Neural Networks (CNNs) have demonstrated exceptional performance in audio tagging tasks. However, deploying these models on resource-constrained devices like the Raspberry Pi poses challenges related to computational efficiency and thermal management. In this paper, a comprehensive evaluation of multiple convolutional neural network (CNN) architectures for audio tagging on the Raspberry Pi is conducted, encompassing all 1D and 2D models from the Pretrained Audio Neural Networks (P…

Impact of Geometric Uncertainty on the Computation of Abdominal Aortic Aneurysm Wall Strain
Saeideh Sekhavat, Mostafa Jamshidian, Adam Wittek, Karol Miller
https://arxiv.org/abs/2509.12550

Impact of Geometric Uncertainty on the Computation of Abdominal Aortic Aneurysm Wall Strain
Abdominal aortic aneurysm (AAA) is a life-threatening condition characterized by permanent enlargement of the aorta, often detected incidentally during imaging for unrelated conditions. Current management relies primarily on aneurysm diameter and growth rate, which may not reliably predict patient-specific rupture risk. Computation of AAA wall stress and strain has the potential to improve individualized risk assessment, but these analyses depend on image-derived geometry, which is subject to s…

StreamTensor: Make Tensors Stream in Dataflow Accelerators for LLMs
Hanchen Ye, Deming Chen
https://arxiv.org/abs/2509.13694 https://arxiv.org/pdf/2509.136…

StreamTensor: Make Tensors Stream in Dataflow Accelerators for LLMs
Efficient execution of deep learning workloads on dataflow architectures is crucial for overcoming memory bottlenecks and maximizing performance. While streaming intermediate results between computation kernels can significantly improve efficiency, existing approaches struggle with inter-kernel correlations, external memory access management, and buffer optimization. In this work, we propose StreamTensor, a compiler framework that automatically constructs and optimizes stream-based dataflow acc…

Sources: several xAI execs left after clashing with two of Musk's closest advisers over concerns about unrealistic financial projections and xAI's management (Wall Street Journal)
https://www.wsj.com/tech/ai/elon-musk-xai-executives-advisers-clash-eac3913…

📣 Auf unserer Culture Knowledge Base hat sich wieder einiges getan: #FAIR es Management kulturwissenschaftlicher Forschungsdaten von Angela K…

SHERLOCK: Towards Dynamic Knowledge Adaptation in LLM-enhanced E-commerce Risk Management
Nan Lu, Yurong Hu, Jiaquan Fang, Yan Liu, Rui Dong, Yiming Wang, Rui Lin, Shaoyi Xu
https://arxiv.org/abs/2510.08948

SHERLOCK: Towards Dynamic Knowledge Adaptation in LLM-enhanced E-commerce Risk Management
The growth of the e-commerce industry has intensified the adversarial dynamics between shadow economy actors and risk management teams. Companies often conduct risk investigations into suspicious cases to identify emerging fraud patterns, thereby enhancing both preemptive risk prevention and post-hoc governance. However, the sheer volume of case analyses imposes a substantial workload on risk management analysts, as each case requires the integration of long-term expert experience and meticulou…

Numerical Investigations of Jet A Hexane Binary Fuel Droplet Impact on a Heated Solid Surface
Arghya Paul, Kanak Raj, Pratim Kumar
https://arxiv.org/abs/2509.13225 https://

Numerical Investigations of Jet A Hexane Binary Fuel Droplet Impact on a Heated Solid Surface
In the present work, Jet A-Hexane binary fuel droplet impact dynamics on heated solid surfaces were studied numerically. This study is crucial for practical applications such as fuel injection in combustors and thermal management of engine components. Volume of fluid (VOF) method was used to analyse the impact dynamics, spreading behaviour, vaporisation, and heat transfer of n-hexane and Jet-A blended fuel droplets on heated stainless-steel surfaces. Droplet impact dynamics were investigated fo…

Privacy-Driven Network Data for Smart Cities
T\^ania Carvalho, Jos\'e Barata, Henish Balu, Filipa Moreira, Jo\~ao Bastos, Lu\'is Antunes
https://arxiv.org/abs/2509.12403

Privacy-Driven Network Data for Smart Cities
A smart city is essential for sustainable urban development. In addition to citizen engagement, a smart city enables connected infrastructure, data-driven decision making and smart mobility. For most of these features, network data plays a critical role, particularly from public Wi-Fi infrastructures, where cities can benefit from optimized services such as public transport management and the safety and efficiency of large events. One of the biggest concerns in developing a smart city is using …

Live-Webinar: Apple-Gerätemanagement mit Microsoft Intune
Intune für das Mobile Device Management von iPhones, iPads & Macs – unser Experte zeigt Tipps und Tricks, wo Grenzen liegen und wie Sie Stolperfallen meistern.

Adapting and Evaluating Multimodal Large Language Models for Adolescent Idiopathic Scoliosis Self-Management: A Divide and Conquer Framework
Zhaolong Wu, Pu Luo, Jason Pui Yin Cheung, Teng Zhang
https://arxiv.org/abs/2509.11645

Adapting and Evaluating Multimodal Large Language Models for Adolescent Idiopathic Scoliosis Self-Management: A Divide and Conquer Framework
This study presents the first comprehensive evaluation of Multimodal Large Language Models (MLLMs) for Adolescent Idiopathic Scoliosis (AIS) self-management. We constructed a database of approximately 3,000 anteroposterior X-rays with diagnostic texts and evaluated five MLLMs through a `Divide and Conquer' framework consisting of a visual question-answering task, a domain knowledge assessment task, and a patient education counseling assessment task. Our investigation revealed limitations of MLL…

Topological Phononic Crystal on the Scale of Quasi-Ballistic Phonon Transport
Keita Funayama, Yuki Akura, Hiroya Tanaka, Jun Hirotani
https://arxiv.org/abs/2509.12528 https://…

Topological Phononic Crystal on the Scale of Quasi-Ballistic Phonon Transport
Phonon engineering technology has opened up the functional thermal management of semiconductor-based classical and quantum electronics at the micro- and nanoscales. However, challenges have remained in designing accurate thermal characteristics based on quasi-ballistic phonon transport. The quasi-ballistic thermal transport arises from the combination of wave-like and diffusive phonon behaviors unlike pure diffusion. The topological nature has been known to be compatible with both wave and diff…

"The Research Data Management Workbook: Building a Collection of Data Management Exercises to Bridge Data Information Literacy and Data Management Implementation" @ Journal of eScience Librarianship: https://doi.org/10.7191/jeslib.937

I’ve built quectoCMS, a very small content management system in Python using Flask and SQLite.
It stores pages, blocks, and comments in a single database file and uses plain HTML forms without JavaScript.
Everything fits into a few Python files and templates — easy to read, easy to modify.
Code: https://github.com/mabalew/quectocm…

GitHub - mabalew/quectocms: Ultra small and ultra fast CMS for your personal needs
Ultra small and ultra fast CMS for your personal needs - mabalew/quectocms

Federated Data Analytics for Cancer Immunotherapy: A Privacy-Preserving Collaborative Platform for Patient Management
Mira Raheem, Michael Papazoglou, Bernd Kr\"amer, Neamat El-Tazi, Amal Elgammal
https://arxiv.org/abs/2510.09155

Federated Data Analytics for Cancer Immunotherapy: A Privacy-Preserving Collaborative Platform for Patient Management
Connected health is a multidisciplinary approach focused on health management, prioritizing pa-tient needs in the creation of tools, services, and treatments. This paradigm ensures proactive and efficient care by facilitating the timely exchange of accurate patient information among all stake-holders in the care continuum. The rise of digital technologies and process innovations promises to enhance connected health by integrating various healthcare data sources. This integration aims to persona…

Towards Scalable O-RAN Resource Management: Graph-Augmented Proximal Policy Optimization
Duc-Thinh Ngo (STACK, LS2N), Kandaraj Piamrat, Ons Aouedi, Thomas Hassan, Philippe Raipin-Parv\'edy
https://arxiv.org/abs/2509.10499

Towards Scalable O-RAN Resource Management: Graph-Augmented Proximal Policy Optimization
Open Radio Access Network (O-RAN) architectures enable flexible, scalable, and cost-efficient mobile networks by disaggregating and virtualizing baseband functions. However, this flexibility introduces significant challenges for resource management, requiring joint optimization of functional split selection and virtualized unit placement under dynamic demands and complex topologies. Existing solutions often address these aspects separately or lack scalability in large and real-world scenarios. …

Leveraging OS-Level Primitives for Robotic Action Management
Wenxin Zheng, Boyang Li, Bin Xu, Erhu Feng, Jinyu Gu, Haibo Chen
https://arxiv.org/abs/2508.10259 https://

Leveraging OS-Level Primitives for Robotic Action Management
End-to-end imitation learning frameworks (e.g., VLA) are increasingly prominent in robotics, as they enable rapid task transfer by learning directly from perception to control, eliminating the need for complex hand-crafted features. However, even when employing SOTA VLA-based models, they still exhibit limited generalization capabilities and suboptimal action efficiency, due to the constraints imposed by insufficient robotic training datasets. In addition to addressing this problem using model-…

Generative AI for Cybersecurity of Energy Management Systems: Methods, Challenges, and Future Directions
Aydin Zaboli, Junho Hong
https://arxiv.org/abs/2508.10044 https://

Generative AI for Cybersecurity of Energy Management Systems: Methods, Challenges, and Future Directions
This paper elaborates on an extensive security framework specifically designed for energy management systems (EMSs), which effectively tackles the dynamic environment of cybersecurity vulnerabilities and/or system problems (SPs), accomplished through the incorporation of novel methodologies. A comprehensive multi-point attack/error model is initially proposed to systematically identify vulnerabilities throughout the entire EMS data processing pipeline, including post state estimation (SE) steal…

Distractor-Aware Memory-Based Visual Object Tracking
Jovana Videnovic, Matej Kristan, Alan Lukezic
https://arxiv.org/abs/2509.13864 https://arxiv.org/pdf/2…

Distractor-Aware Memory-Based Visual Object Tracking
Recent emergence of memory-based video segmentation methods such as SAM2 has led to models with excellent performance in segmentation tasks, achieving leading results on numerous benchmarks. However, these modes are not fully adjusted for visual object tracking, where distractors (i.e., objects visually similar to the target) pose a key challenge. In this paper we propose a distractor-aware drop-in memory module and introspection-based management method for SAM2, leading to DAM4SAM. Our design …

Machine Learning-Driven Predictive Resource Management in Complex Science Workflows
Tasnuva Chowdhury, Tadashi Maeno, Fatih Furkan Akman, Joseph Boudreau, Sankha Dutta, Shengyu Feng, Adolfy Hoisie, Kuan-Chieh Hsu, Raees Khan, Jaehyung Kim, Ozgur O. Kilic, Scott Klasky, Alexei Klimentov, Tatiana Korchuganova, Verena Ingrid Martinez Outschoorn, Paul Nilsson, David K. Park, Norbert Podhorszki, Yihui Ren, John Rembrandt Steele, Fr\'ed\'eric Suter, Sairam Sri Vatsavai, Torre Wenaus,…

Machine Learning-Driven Predictive Resource Management in Complex Science Workflows
The collaborative efforts of large communities in science experiments, often comprising thousands of global members, reflect a monumental commitment to exploration and discovery. Recently, advanced and complex data processing has gained increasing importance in science experiments. Data processing workflows typically consist of multiple intricate steps, and the precise specification of resource requirements is crucial for each step to allocate optimal resources for effective processing. Estimat…

...normally that won’t be the case, even when the person seems nearly totally to blame (and that isn’t even a very common situation) normally there are obvious weaknesses in the system that put them in the place to fail and will likely put anyone else in the same place in the future.

Generative AI for Software Project Management: Insights from a Review of Software Practitioner Literature
Lakshana Iruni Assalaarachchi, Zainab Masood, Rashina Hoda, John Grundy
https://arxiv.org/abs/2510.10887

Generative AI for Software Project Management: Insights from a Review of Software Practitioner Literature
Software practitioners are discussing GenAI transformations in software project management openly and widely. To understand the state of affairs, we performed a grey literature review using 47 publicly available practitioner sources including blogs, articles, and industry reports. We found that software project managers primarily perceive GenAI as an "assistant", "copilot", or "friend" rather than as a "PM replacement", with support of GenAI in automating routine tasks, predictive analytics, co…

XASDB -- Design and Implementation of an Open-Access Spectral Database
Denis Spasyuk
https://arxiv.org/abs/2509.13566 https://arxiv.org/pdf/2509.13566

XASDB - Design and Implementation of an Open-Access Spectral Database
The increasing volume and complexity of X-ray absorption spectroscopy (XAS) data generated at synchrotron facilities worldwide require robust infrastructure for data management, sharing, and analysis. This paper introduces the XAS Database (XASDB), a comprehensive web-based platform developed and hosted by the Canadian Light Source (CLS). The database houses more than 1000 reference spectra spanning 40 elements and 324 chemical compounds. The platform employs a Node.js/MongoDB architecture desi…

CattleSense - A Multisensory Approach to Optimize Cattle Well-Being
Srijesh Pillai, M. I. Jawid Nazir
https://arxiv.org/abs/2509.12617 https://arxiv.org/pd…

CattleSense - A Multisensory Approach to Optimize Cattle Well-Being
CattleSense is an innovative application of Internet of Things (IoT) technology for the comprehensive monitoring and management of cattle well-being. This research paper outlines the design and implementation of a sophisticated system using a Raspberry Pi Module 4B, RFID Card Reader, Electret Arduino Microphone Module, DHT11 Sensor, Arduino UNO, Neo-6M GPS Sensor, and Heartbeat Sensor. The system aims to provide real-time surveillance of the environment in which Cows are present and individual …

Air Quality PM2.5 Index Prediction Model Based on CNN-LSTM
Zicheng Guo, Shuqi Wu, Meixing Zhu, He Guandi
https://arxiv.org/abs/2508.11215 https://arxiv.org…

Air Quality PM2.5 Index Prediction Model Based on CNN-LSTM
With the intensification of global climate change, accurate prediction of air quality indicators, especially PM2.5 concentration, has become increasingly important in fields such as environmental protection, public health, and urban management. To address this, we propose an air quality PM2.5 index prediction model based on a hybrid CNN-LSTM architecture. The model effectively combines Convolutional Neural Networks (CNN) for local spatial feature extraction and Long Short-Term Memory (LSTM) net…

Crosslisted article(s) found for q-fin.RM. https://arxiv.org/list/q-fin.RM/new
[1/1]:
- Valuation of Exotic Options and Counterparty Games Based on Conditional Diffusion
Helin Zhao, Junchi Shen

Replaced article(s) found for q-fin.PM. https://arxiv.org/list/q-fin.PM/new
[1/1]:
- Robust forward investment and consumption under drift and volatility uncertainties: A randomizati...
Wing Fung Chong, Gechun Liang

🚀RDMO goes 4Culture! Ab sofort ist der Research Data Management Organizer (RDMO) als kostenfreier Dienst für alle Mitglieder mit #NFDI4Culture-Zugang (Co-Applicants, Participants, Kooperationspartner) verfügbar: https://nfdi4culture.de/id/E60…

Demystifying Progressive Web Application Permission Systems
Mengxiao Wang, Guofei Gu
https://arxiv.org/abs/2509.13563 https://arxiv.org/pdf/2509.13563

Demystifying Progressive Web Application Permission Systems
Progressive Web Applications (PWAs) blend the advantages of web and native apps, offering features like offline access, push notifications, and installability. Beyond these, modern PWAs are increasingly granted system-level capabilities such as auto-start on login and shared context with native applications. However, their permission management remains poorly defined and inconsistently implemented across platforms and browsers. To investigate these gaps, we developed Permissioner, a cross-pla…

PeerTube is a decentralized alternative to YouTube
that doesn't believe in harvesting user data and pushing people into echo chambers via a proprietary algorithm.
Built on open standards and federation,
it lets communities host and share video without depending on a central server.
https://news.itsfoss.com/peertube-7…

Decentralized YouTube Alternative Adds Live Streame Scheduling Option in Latest Release
Also adds multilingual emails, improved admin tools, and session management.

After firing of BLS chief, Lutnick tells federal statisticians that independence is 'nonsense' (Eric Katz/GovExec.com)
https://www.govexec.com/management/2025/08/after-firing-bls-chief-lutnick-tells-federal-statisticians-independence-nonsense/407404/
http://www.memeorandum.com/250812/p145#a250812p145

On Condensation Management - Learn how you can best avoid problems with condensation, damp and mould in winter. #mould #condensation #ventilation -

On Condensation Management
Learn how you can best avoid problems with condensation, damp and mould in winter. #mould #condensation #ventilation

Crosslisted article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[3/7]:
- Understanding Prompt Management in GitHub Repositories: A Call for Best Practices
Hao Li, Hicham Masri, Filipe R. Cogo, Abdul Ali Bangash, Bram Adams, Ahmed E. Hassan

"Umgang mit dem Unsichtbaren – Neurodiversity-Management in Bibliotheken" https://doi.org/10.1515/bfp-2024-0005

Principles of Physiological Closed-Loop Controllers in Neuromodulation
Victoria S. Marks, Joram vanRheede, Dean Karantonis, Rosana Esteller, David Dinsmoor, John Fleming, Barrett Larson, Lane Desborough, Peter Single, Robert Raike, Pierre-Francois DHaese, Dario J. Englot, Scott Lempka, Richard North, Lawrence Poree, Marom Bikson, Tim J. Denison
https://

Principles of Physiological Closed-Loop Controllers in Neuromodulation
As neurostimulation devices increasingly incorporate closed-loop functionality, the greater design complexity brings additional requirements for risk management and special considerations to optimise benefit. This manuscript creates a common framework upon which all current and planned neuromodulation-based physiological closed-loop controllers (PCLCs) can be mapped including integration of the Technical Considerations of Medical Devices with Physiologic Closed-Loop Control Technology guidance …

Intelligent Edge Resource Provisioning for Scalable Digital Twins of Autonomous Vehicles
Mohammad Sajid Shahriar, Suresh Subramaniam, Motoharu Matsuura, Hiroshi Hasegawa, Shih-Chun Lin
https://arxiv.org/abs/2508.11574

Intelligent Edge Resource Provisioning for Scalable Digital Twins of Autonomous Vehicles
The next generation networks offers significant potential to advance Intelligent Transportation Systems (ITS), particularly through the integration of Digital Twins (DTs). However, ensuring the uninterrupted operation of DTs through efficient computing resource management remains an open challenge. This paper introduces a distributed computing archi tecture that integrates DTs and Mobile Edge Computing (MEC) within a software-defined vehicular networking framework to enable intelligent, low-lat…

AIM-Bench: Evaluating Decision-making Biases of Agentic LLM as Inventory Manager
Xuhua Zhao, Yuxuan Xie, Caihua Chen, Yuxiang Sun
https://arxiv.org/abs/2508.11416 https://

AIM-Bench: Evaluating Decision-making Biases of Agentic LLM as Inventory Manager
Recent advances in mathematical reasoning and the long-term planning capabilities of large language models (LLMs) have precipitated the development of agents, which are being increasingly leveraged in business operations processes. Decision models to optimize inventory levels are one of the core elements of operations management. However, the capabilities of the LLM agent in making inventory decisions in uncertain contexts, as well as the decision-making biases (e.g. framing effect, etc.) of th…

John Willis interviewed me for his Profound podcast series
#Deming

How AI is upending India's business process management sector, which employs 1.65M people; conversational AI startup LimeChat claims to have automated 5K jobs (Reuters)
https://www.reuters.com/world/india/meet-ai-chatbots-replacing-in…

CLAIRE: A Dual Encoder Network with RIFT Loss and Phi-3 Small Language Model Based Interpretability for Cross-Modality Synthetic Aperture Radar and Optical Land Cover Segmentation
Debopom Sutradhar, Arefin Ittesafun Abian, Mohaimenul Azam Khan Raiaan, Reem E. Mohamed, Sheikh Izzal Azid, Sami Azam
https://arxiv.org/abs/2509.11952

CLAIRE: A Dual Encoder Network with RIFT Loss and Phi-3 Small Language Model Based Interpretability for Cross-Modality Synthetic Aperture Radar and Optical Land Cover Segmentation
Accurate land cover classification from satellite imagery is crucial in environmental monitoring and sustainable resource management. However, it remains challenging due to the complexity of natural landscapes, the visual similarity between classes, and the significant class imbalance in the available datasets. To address these issues, we propose a dual encoder architecture that independently extracts modality-specific features from optical and Synthetic Aperture Radar (SAR) imagery, which are …

A novel approach of day-ahead cooling load prediction and optimal control for ice-based thermal energy storage (TES) system in commercial buildings
Xuyuan Kang, Xiao Wang, Jingjing An, Da Yan
https://arxiv.org/abs/2509.13371

A novel approach of day-ahead cooling load prediction and optimal control for ice-based thermal energy storage (TES) system in commercial buildings
Thermal energy storage (TES) is an effective method for load shifting and demand response in buildings. Optimal TES control and management are essential to improve the performance of the cooling system. Most existing TES systems operate on a fixed schedule, which cannot take full advantage of its load shifting capability, and requires extensive investigation and optimization. This study proposed a novel integrated load prediction and optimized control approach for ice-based TES in commercial bu…

[2025-09-17 Wed (UTC), 1 new article found for q-fin.RM Risk Management]
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[2025-09-17 Wed (UTC), 2 new articles found for q-fin.PM Portfolio Management]
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Low-cost Highly-interoperable Multiplatform Campus Network: Experience of YARSI University
Surya Agustian, Sandra Permana, Salman Teguh Pratista, Syarifu Adam, Iswandi
https://arxiv.org/abs/2509.13954

Low-cost Highly-interoperable Multiplatform Campus Network: Experience of YARSI University
To some organizations, building campus network is sometimes considered to be very expensive; and this has made the project uneasy to perform. Moreover, if the organization without sufficient IT knowledge does not have capable IT engineers, leaving this project to third parties without supervision would lead to unexpected larger expenses. For this reason, in the year of 2003, YARSI University formed CMIS (Center for Management Infor-mation System) to perform tasks in designing, operations and ma…

Feasibility-Guided Fair Adaptive Offline Reinforcement Learning for Medicaid Care Management
Sanjay Basu, Sadiq Y. Patel, Parth Sheth, Bhairavi Muralidharan, Namrata Elamaran, Aakriti Kinra, Rajaie Batniji
https://arxiv.org/abs/2509.09655

Feasibility-Guided Fair Adaptive Offline Reinforcement Learning for Medicaid Care Management
We introduce Feasibility-Guided Fair Adaptive Reinforcement Learning (FG-FARL), an offline RL procedure that calibrates per-group safety thresholds to reduce harm while equalizing a chosen fairness target (coverage or harm) across protected subgroups. Using de-identified longitudinal trajectories from a Medicaid population health management program, we evaluate FG-FARL against behavior cloning (BC) and HACO (Hybrid Adaptive Conformal Offline RL; a global conformal safety baseline). We report of…

Salesforce says it expects FY 2030 revenue of $60B , vs. $58.37B est., excluding impact from the $8B pending acquisition of data management company Informatica (Jordan Novet/CNBC)
https://www.cnbc.com/2025/10/15/salesforce-stock-jumps-a…

Salesforce stock jumps after company offers rosy forecast for 2030
Salesforce is counting on Agentforce artificial intelligence software to pull in more revenue from customers.

A Highly Compact Direct-Injection Power-Flow Controller and Line-Voltage Regulator with Shared Magnetics and Partial-Power Conversion for Full-Power Control
Davood Keshavarzi, Alexander Koehler, Stefan M. Goetz
https://arxiv.org/abs/2509.10955

A Highly Compact Direct-Injection Power-Flow Controller and Line-Voltage Regulator with Shared Magnetics and Partial-Power Conversion for Full-Power Control
An increasing integration of photovoltaic units, electric vehicle chargers, heat pumps, and energy storage systems challenges low-voltage power grids and can cause voltage range violation, loss of stability, (local) overload of lines, and power management problems. Research suggested universal power-flow control (UPFC) to solve power management problems. In contrast to bulky, slow, and costly conventional UPFCs with their shunt and series transformers, this paper presents a highly compact and c…

[2025-08-18 Mon (UTC), no new articles found for q-fin.RM Risk Management]
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[2025-08-18 Mon (UTC), no new articles found for q-fin.PM Portfolio Management]
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A Scoping Review of Machine Learning Applications in Power System Protection and Disturbance Management
Julian Oelhaf, Georg Kordowich, Mehran Pashaei, Christian Bergler, Andreas Maier, Johann J\"ager, Siming Bayer
https://arxiv.org/abs/2509.09053

A Scoping Review of Machine Learning Applications in Power System Protection and Disturbance Management
The integration of renewable and distributed energy resources reshapes modern power systems, challenging conventional protection schemes. This scoping review synthesizes recent literature on machine learning (ML) applications in power system protection and disturbance management, following the PRISMA for Scoping Reviews framework. Based on over 100 publications, three key objectives are addressed: (i) assessing the scope of ML research in protection tasks; (ii) evaluating ML performance across …

Semantic-Aware LLM Orchestration for Proactive Resource Management in Predictive Digital Twin Vehicular Networks
Seyed Hossein Ahmadpanah
https://arxiv.org/abs/2508.09149 https:…

Semantic-Aware LLM Orchestration for Proactive Resource Management in Predictive Digital Twin Vehicular Networks
Next-generation automotive applications require vehicular edge computing (VEC), but current management systems are essentially fixed and reactive. They are suboptimal in extremely dynamic vehicular environments because they are constrained to static optimization objectives and base their decisions on the current network states. This paper presents a novel Semantic-Aware Proactive LLM Orchestration (SP-LLM) framework to address these issues. Our method transforms the traditional Digital Twin (DT…

[2025-09-18 Thu (UTC), no new articles found for q-fin.RM Risk Management]
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Mumbai-based wealth management startup Dezerv raised a ~$40M Series C co-led by Premji Invest and Accel's Global Growth Fund, taking its total funding to ~$100M (Shashank Pathak/Entrackr)
https://entrackr.com/news/wealthtech-firm-deze…

Wealthtech firm Dezerv raises $40 Mn led by Premji Invest and Accel
Wealth tech platform Dezerv has raised Rs 350 crore (about $40 million) in a funding round co-led by Premji Invest and Accel’s Global Growth Fund. News

Knowledge-Guided Adaptive Mixture of Experts for Precipitation Prediction
Chen Jiang, Kofi Osei, Sai Deepthi Yeddula, Dongji Feng, Wei-Shinn Ku
https://arxiv.org/abs/2509.11459 …

Knowledge-Guided Adaptive Mixture of Experts for Precipitation Prediction
Accurate precipitation forecasting is indispensable in agriculture, disaster management, and sustainable strategies. However, predicting rainfall has been challenging due to the complexity of climate systems and the heterogeneous nature of multi-source observational data, including radar, satellite imagery, and surface-level measurements. The multi-source data vary in spatial and temporal resolution, and they carry domain-specific features, making it challenging for effective integration in con…

Sparrow, which uses AI to consolidate fragmented leave management processes, raised a $35M Series B led by Silver Lake Waterman, for $64M in total funding (Michael Nuñez/VentureBeat)
https://venturebeat.com/ai/sparrow-raises-35m-ser…

Sparrow raises $35M Series B to automate the employee leave management nightmare
Sparrow raises $35M Series B to scale AI-powered employee leave management platform that has grown 14x since 2021, serving 1,000+ companies and saving $200M in payroll costs.

Human-AI Use Patterns for Decision-Making in Disaster Scenarios: A Systematic Review
Emmanuel Adjei Domfeh, Christopher L. Dancy
https://arxiv.org/abs/2509.12034 https://…

Human-AI Use Patterns for Decision-Making in Disaster Scenarios: A Systematic Review
In high-stakes disaster scenarios, timely and informed decision-making is critical yet often challenged by uncertainty, dynamic environments, and limited resources. This paper presents a systematic review of Human-AI collaboration patterns that support decision-making across all disaster management phases. Drawing from 51 peer-reviewed studies, we identify four major categories: Human-AI Decision Support Systems, Task and Resource Coordination, Trust and Transparency, and Simulation and Trainin…