Results 41 to 50 of about 36,493,496 (144)

RES‐AD: An AutoML‐Driven Robust Ensemble Framework for Real‐Time Anomaly Detection and Energy Forecasting in Smart Grids

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Accurate load forecasting and reliable anomaly detection are critical for the stable operation of modern smart grids (SGs), which increasingly rely on cyber‐connected infrastructures. However, the integration of smart metres and two‐way communication exposes SGs to data integrity attacks that can manipulate consumption measurements, degrade ...
Murad Ali Khan   +4 more
wiley   +1 more source

Research on Embodied Intelligence Technology for Electric Power Equipment Based on Large‐Scale Pre‐Trained Models

open access: yesHigh Voltage, EarlyView.
ABSTRACT With the development of electric power artificial intelligence (AI) technology, many complicated challenges emerged during application. Traditional AI algorithms work well in specialised tasks such as detection and classification. However, they are unlikely to solve general problems.
Yuanpeng Tan   +4 more
wiley   +1 more source

Comparison of outcomes after DA‐EPOCH‐R or GMALL high‐intensity therapy for front‐line treatment of Burkitt lymphoma: A retrospective cohort

open access: yesBritish Journal of Haematology, EarlyView.
In this retrospective cohort of adult Burkitt lymphoma, DA‐EPOCH‐R showed no signal of inferior survival or relapse risk compared with GMALL‐based high‐intensity therapy. Outcomes were driven mainly by established prognostic factors, particularly age, advanced stage and Burkitt lymphoma International Prognostic Index.
Eduard Schulz   +4 more
wiley   +1 more source

Department of Computer Science newsletter 2020

open access: yes, 2020
A Newsletter for Friends and Supporters of the Mines Computer Science ...

core  

BrECADD in three days: Implementation of a condensed intensive first‐line regimen in Hodgkin lymphoma

open access: yesBritish Journal of Haematology, EarlyView.
BrECADD can be delivered over 3 days instead of four, reducing intravenous treatment days by 25% without compromising dose intensity. Among 30 patients with advanced‐stage Hodgkin lymphoma, no unexpected toxicity was observed; there were no early discontinuations, and 1‐year progression‐free and overall survival were both 100%.
Christian Peter Jaworek   +16 more
wiley   +1 more source

Emerging applications of large language models in ecology and conservation science

open access: yesConservation Biology, EarlyView.
Abstract Large language models (LLMs) mark a major development in artificial intelligence, with potentially transformative implications for ecology and conservation science. Built on advanced deep‐learning architectures, these models can support a wide range of tasks. We reviewed emerging applications of LLMs, drawing on the wider scientific literature
Christos Mammides   +5 more
wiley   +1 more source

A Normative Framework for Agent-Based Systems [PDF]

open access: yes, 2005
One of the key issues in the computational representation of open societies relates to the introduction of norms that help to cope with the heterogeneity, the autonomy and the diversity of interests among their members.
Luck, Michael   +8 more
core   +1 more source

Impact of Intensified Chemoimmunotherapy Regimens in Aggressive Non‐Hodgkin Lymphoma on Reproduction Patterns

open access: yesEuropean Journal of Haematology, EarlyView.
ABSTRACT Concerns about treatment‐related fertility impairment are common among young adult lymphoma survivors. Evidence on the impact of treatment for aggressive non‐Hodgkin lymphoma (NHL) on future childbearing is limited, although many individuals of reproductive age are affected.
Stefanie Antonilli   +10 more
wiley   +1 more source

Preference‐Based Representations for Collective Agency

open access: yesTopics in Cognitive Science, EarlyView.
Abstract Computational accounts of learning and decision‐making in cognitive systems, and models thereof, such as reinforcement learning, typically assume that the behavior of individual agents is determined by an externally designated reward signal such that the agent's goal is the maximization of its expected accumulated reward under the state ...
Nadav Amir   +2 more
wiley   +1 more source

Goal‐Directed Latent Variable Inference: A Unified Active Inference Framework for Embodied Intelligence in Continuous Spatiotemporal Domains

open access: yesTopics in Cognitive Science, EarlyView.
AbstractThis review presents goal‐directed latent variable inference (GLean) as a unified active inference framework for embodied intelligence operating in continuous spatiotemporal domains. We address a central challenge in cognitive science: how agents generate, adapt, and understand goal‐directed actions in noisy, high‐dimensional sensorimotor ...
Takazumi Matsumoto   +2 more
wiley   +1 more source

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