Results 41 to 50 of about 25,302 (170)
A greedy stacking algorithm for model ensembling and domain weighting
Objective Because it is impossible to know which statistical learning algorithm performs best on a prediction task, it is common to use stacking methods to ensemble individual learners into a more powerful single learner.
Christoph F. Kurz +2 more
doaj +1 more source
Optimization of PWSN transmission performance on coal mining face
In view of problems of long end-to-end time and high packet loss rate of positioning wireless sensor network (PWSN) on coal mining face, a guaranteed greedy scheduling (GGS) algorithm was proposed to optimize network transmission performance.
FANG Zuhao +3 more
doaj +1 more source
Real‐World Performance of CSF Kappa Free Light Chains in the 2024 McDonald Criteria
ABSTRACT Objective Kappa free light chains (KFLCs) in the cerebrospinal fluid (CSF) have a similar performance to CSF‐restricted oligoclonal bands (OCB) for multiple sclerosis (MS) diagnosis. To help with implementation, we set out to resolve several remaining uncertainties: (1) performance in a real‐world cohort and the 2024 McDonald criteria; (2 ...
Maya M. Leibowitz +11 more
wiley +1 more source
The Feature Compression Algorithms for Identifying Cytokines Based on CNT Features
As the signaling proteins, cytokines regulate a wide range of biological functions. It is important to distinguish the cytokines from other kinds of proteins.
Guilin Li, Xing Gao
doaj +1 more source
Clustering Algorithm Reveals Dopamine‐Motor Mismatch in Cognitively Preserved Parkinson's Disease
ABSTRACT Objective To explore the relationship between dopaminergic denervation and motor impairment in two de novo Parkinson's disease (PD) cohorts. Methods n = 249 PD patients from Parkinson's Progression Markers Initiative (PPMI) and n = 84 from an external clinical cohort.
Rachele Malito +14 more
wiley +1 more source
What Do Large Language Models Know About Materials?
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
An Improved Q-Learning Algorithm and Its Application in Path Planning
Traditional Q-Learning algorithm has the problems of too many random searches and slow convergence speed. Therefore, in this paper an improved ε-Q-Learning algorithm based on traditional Q-Learning algorithm was propased and applied to path planning. The
Guojun MAO, Shimin GU
doaj +1 more source
Smart Catheters for Diagnosis, Monitoring, and Therapy
This study presents a comprehensive review of smart catheters, an emerging class of medical devices that integrate embedded sensors, robotics, and communication systems, offering increased functionality and complexity to enable real‐time health monitoring, diagnostics, and treatment. Abstract This review explores smart catheters as an emerging class of
Azra Yaprak Tarman +12 more
wiley +1 more source
Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application
This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong +12 more
wiley +1 more source
No-Wait Job Shop Scheduling Using a Population-Based Iterated Greedy Algorithm
When no-wait constraint holds in job shops, a job has to be processed with no waiting time from the first to the last operation, and the start time of a job is greatly restricted. Using key elements of the iterated greedy algorithm, this paper proposes a
Mingming Xu +2 more
doaj +1 more source

