Solving Data Overlapping Problem Using A Class‐Separable Extreme Learning Machine Auto‐Encoder
The overlapping and imbalanced data in classification present key challenges. Class‐separable extreme learning machine auto‐encoding (CS‐ELM‐AE) is proposed, which is an enhancement of ELM‐AE that better handles overlapping data by clustering points from the same class together. Applying oversampling addresses imbalanced data.
Ekkarat Boonchieng, Wanchaloem Nadda
wiley +1 more source
Early Career Reviewer Hub: Paving the way for the next generation of peer reviewers. [PDF]
Fuentes S, De la Rosa MA.
europepmc +1 more source
Robot‐Assisted Measurement of the Critical Micelle Concentration
The study introduces (SIMO) smart integrator for manual operations, a robotic platform for precise, repeatable determination of (CMC) critical micelle concentration in surfactants. SIMO reduces standard deviation by 80% compared to manual methods. Surfactant, dye, and diluent selection, robotic protocols, and data handling are detailed.
Vincenzo Scamarcio +3 more
wiley +1 more source
Global and regional inequalities in dairy recommendations: a natural language processing analysis of food-based dietary guidelines across income groups. [PDF]
Bertini A +3 more
europepmc +1 more source
A laser pointer‐guided robotic grasping method for arbitrary objects based on promptable segment anything model and force‐closure analysis is presented. Grasp generation methods based on force‐closure analysis can calculate the optimal grasps for objects through their appearances. However, the limited visual perception ability makes robots difficult to
Yan Liu +5 more
wiley +1 more source
From transcriptomic profiling to precision oncology: a bibliometric analysis of RNA sequencing in acute myeloid leukemia. [PDF]
Ren Y, Ma J, Hu W, Zhang L, Wang X.
europepmc +1 more source
This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker +2 more
wiley +1 more source
Enhanced recovery after orthopaedic surgery: global research trends, collaboration, and emerging themes. [PDF]
Zhang E +4 more
europepmc +1 more source
Ecoefficiency Analysis and Regression in Data Conversion for Spiking Neural Network Training
The environmental footprint of spiking neural networks is quantified during dataset encoding and training for autonomous driving regression across three benchmarks. Temporal depth emerges as the dominant driver of energy consumption and CO2 emissions, while the accuracy–energy trade‐off proves dataset‐dependent. On conventional hardware, spiking models
Fernando S. Martínez +3 more
wiley +1 more source
A Holistic Bibliometric Exploration of the Evolution of Epidermodysplasia Verruciformis (EV) Research. [PDF]
Danesh F +3 more
europepmc +1 more source

