Results 241 to 250 of about 176,220 (309)

Who Leads, What Matters? Machine Learning and the Complexity of University Performance. [PDF]

PLoS One
Ballestar MT, Komp-Leukkunen K, Malfeito-Gaviro J, Ramos A, Sainz J.   +4 more
europepmc   +1 more source

The role of the cash flow budget in the budgeting process

Научный диалог: Экономика и менеджмент, 2018
openaire   +1 more source

GraphRAG for engineering diagrams: ChatP&ID enables LLM interaction with P&IDs

AIChE Journal, EarlyView.
Abstract Piping and Instrumentation Diagrams (P&IDs) are central to process engineering workflows, yet extracting information from them remains a tedious and time‐consuming task. This work introduces ChatP&ID, a framework enabling natural‐language interaction with smart P&IDs through Graph Retrieval‐Augmented Generation (GraphRAG), to our knowledge ...
Achmad Anggawirya Alimin, Artur M. Schweidtmann   +1 more
wiley   +1 more source

Improved closure of the global mean sea level budget from observational advances since 1960. [PDF]

Sci Adv
Zheng H, Cheng L, Dangendorf S, Meyssignac B, Barnoud A, Trenberth KE, Fasullo JT, Abraham J.   +7 more
europepmc   +1 more source

Machine Learning‐Enhanced Random Matrix Theory Design for Human Immunodeficiency Virus Vaccine Development

Advanced Intelligent Discovery, EarlyView.
This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah, Muhammad Zulqarnain Zeb, Muhammad Husnain Zeb, Babar Shabbir   +3 more
wiley   +1 more source

Paying for hospital care in seven central and Eastern European countries - a comparative analysis. [PDF]

Health Econ Rev
Dubas-Jakóbczyk K, Davidovics K, Dimova A, Habicht T, Hroboň P, Imre L, Kasekamp K, Minev M, Murauskienė L, Smatana M, Rethazi G, Szalayova A, Szetela A, Šlegerová L, Topór-Mądry R.   +14 more
europepmc   +1 more source

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

Advanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj, Ella Paasio, Sayani Majumdar   +2 more
wiley   +1 more source

Calibration of impulse high-voltage test systems above 500 kV peak: implementation and evaluation. [PDF]

Sci Rep
Haiba AS.
europepmc   +1 more source

Sampling Strategy: An Overlooked Factor Affecting Artificial Intelligence Prediction Accuracy of Peptides’ Physicochemical Properties

Advanced Intelligent Discovery, EarlyView.
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan, Ankeer Abuduhebaier, Haojin Zhou, Jiaqi Wang   +3 more
wiley   +1 more source

Factorization Machine with Iterative Quantum Reverse Annealing: A Python Package for Batch Black‐Box Optimization With Reverse Quantum Annealing

Advanced Intelligent Discovery, EarlyView.
Factorization machine with iterative quantum reverse annealing (FMIRA) leverages quantum reverse annealing to perform batch black‐box optimization. Factorization machine with quantum annealing (FMQA) is a widely used python package for solving black‐box optimization problems using D‐Wave quantum annealers.
Andrejs Tučs, Ryo Tamura, Koji Tsuda
wiley   +1 more source