Results 61 to 70 of about 52,631 (263)

Human-AI Collaboration in Data Science [PDF]

open access: yesProceedings of the ACM on Human-Computer Interaction, 2019
The rapid advancement of artificial intelligence (AI) is changing our lives in many ways. One application domain is data science. New techniques in automating the creation of AI, known as AutoAI or AutoML, aim to automate the work practices of data scientists. AutoAI systems are capable of autonomously ingesting and pre-processing data, engineering new
Dakuo Wang   +8 more
openaire   +2 more sources

Whole‐Genome Sequencing Pilot of the Central Asian Genomic Diversity Project Reveals Distinct Histories, Adaptation, and Introgression

open access: yesAdvanced Science, EarlyView.
As a pilot phase of the Central Asian Genomic Diversity Project, whole‐genome sequencing of 166 individuals from 20 Central Asian and Afghan Hazara populations reveals fine‐scale substructure shaped by repeated trans‐Eurasian migration and admixture. Integrated analyses uncover post‐admixture adaptation, archaic introgression, and medically relevant ...
Mengge Wang   +11 more
wiley   +1 more source

Long-Term Trajectory Prediction for Oil Tankers via Grid-Based Clustering

open access: yesJournal of Marine Science and Engineering, 2023
Vessel trajectory prediction is an important step in route planning, which could help improve the efficiency of maritime transportation. In this article, a high-accuracy long-term trajectory prediction algorithm is proposed for oil tankers.
Xuhang Xu   +4 more
doaj   +1 more source

From Chatbots to Co‐Scientists: The Impact of Knowledge‐Generating AI (AI 4.0) on Healthcare and Research

open access: yesAdvanced Science, EarlyView.
This perspective contrasts the historical, linear progression of early AI with the dynamic, iterative nature of AI 4.0; and it describes the real‐world medical applications and the necessary evolution of laboratory infrastructure brought about by AI 4.0.
Weida Liu, Gary Peltz
wiley   +1 more source

Modeling of Accidental Bunker Oil Spills as a Result of Ship's Bunker Tanks Rupture - a Case Study [PDF]

open access: yesTransNav, 2012
AIS (Automatic Identification System) data analysis is used to define ship domain for grounding scenarios. The domain has been divided into two areas as inner and outer domains.
Przemyslaw Krata   +2 more
doaj  

Chlorine‐Functionalized Silane‐Modified Copper Electrocatalyst for Enhanced CO2 Reduction to Multi‐Carbon Products

open access: yesAdvanced Science, EarlyView.
A chlorine‐functionalized silane modifier (CPTMS) is introduced to cooperatively regulate CO2 reduction to C2+ products on Cu‐based catalysts. Dual‐functional interface sequentially enhances CO2 activation, intermediates protonation and C─C coupling, delivering a 5‐fold increase in C2+ faradaic efficiency (FE, 75% vs.
Ying Ying Ch'ng   +14 more
wiley   +1 more source

Data Transmission in Inland AIS System [PDF]

open access: yesTransNav, 2010
The article presents the technical aspects of applying the marine Automatic Identification System (AIS) for the purposes of vessel traffic control in inland shipping.
Piotr Wolejsza
doaj  

Detection of AIS Closing Behavior and MMSI Spoofing Behavior of Ships Based on Spatiotemporal Data

open access: yesRemote Sensing, 2020
In marine transportation, many ships are equipped with AIS devices. The AIS data sent by AIS devices can help the maritime authorities and other ships obtain the navigation condition of the ship, thereby ensuring the safety of ships during navigation ...
Tao Zhang   +3 more
doaj   +1 more source

Compact Modeling of Volatile‐Switching Electrochemical Metallization Memory Cells by Means of the Electromotive Force

open access: yesAdvanced Intelligent Systems, EarlyView.
A volatile‐switching compact model of electrochemical metallization memory cells for neuromorphic architecture is developed and validated by reliable reproduction of device characterization measurements: I−V sweeps, SET kinetics, relaxation dynamics.
Rana Walied Ahmad   +4 more
wiley   +1 more source

Integrating Reinforcement Learning With Explainable Artificial Intelligence for Real‐Time Clinical Decision Support in Dynamic Healthcare Environments

open access: yesAdvanced Intelligent Systems, EarlyView.
A hybrid Reinforcement Learning–Explainable AI framework integrates SHAP and LIME explanations directly into a Deep Q‐Network inference loop for real‐time ICU decision support. Trained on 18 142 mechanically ventilated stays from the eICU database, the system attains 93.0% decision accuracy, 20% fewer errors than RL alone, and a 91% clinician trust ...
Jannatul Ferdaus Disha   +2 more
wiley   +1 more source

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