Results 61 to 70 of about 93,524 (286)

A Study on Dropout Prediction for University Students Using Machine Learning

Applied Sciences, 2023
Student dropout is a serious issue in that it not only affects the individual students who drop out but also has negative impacts on the former university, family, and society together.
Choong Hee Cho, Yang Woo Yu, Hyeon Gyu Kim   +2 more
doaj   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Oversampling Techniques for Imbalanced Data in Regression

Expert Systems with Applications, 2023
Our study addresses the challenge of imbalanced regression data in Machine Learning (ML) by introducing tailored methods for different data structures. We adapt K-Nearest Neighbor Oversampling-Regression (KNNOR-Reg), originally for imbalanced classification, to address imbalanced regression in low population datasets, evolving to KNNOR-Deep Regression (
Samir Brahim Belhaouari, Ashhadul Islam, Khelil Kassoul, Ala I. Al-Fuqaha, Abdesselam Bouzerdoum   +4 more
openaire   +2 more sources

Dual‐Mode Oscillations in SiOx‐Based Threshold Switching Devices for Unconventional Probabilistic Computing

Advanced Intelligent Discovery, EarlyView.
To enable versatile unconventional computing, a single SiOx threshold switching device is engineered to exhibit controllable dual‐mode oscillation. By modulating the input voltage, the device selectively provides stable full oscillation for oscillatory neural networks and stochastic probabilistic oscillation for probabilistic bits and true random ...
Hyeonsik Choi, Jihyun Kim, Yonghun Kim, Jiyong Woo   +3 more
wiley   +1 more source

Solving Data Overlapping Problem Using A Class‐Separable Extreme Learning Machine Auto‐Encoder

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
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

Oversampling ADC: A Review of Recent Design Trends

IEEE Access
Oversampling analog-to-digital converters (ADC) serve as the backbone of high-performance, high-precision data interfaces, owing to their remarkable ability to filter out quantization noise. This attribute makes them the preferred choice for applications
Antoine Verreault, Paul-Vahe Cicek, Alexandre Robichaud   +2 more
doaj   +1 more source

A Parameter-Free Cleaning Method for SMOTE in Imbalanced Classification

IEEE Access, 2019
Oversampling is an efficient technique in dealing with class-imbalance problem. It addresses the problem by reduplicating or generating the minority class samples to balance the distribution between the samples of the majority and the minority class ...
Yuanting Yan, Ruiqing Liu, Zihan Ding, Xiuquan Du, Jie Chen, Yanping Zhang   +5 more
doaj   +1 more source

Phase Retrieval with Random Phase Illumination

, 2012
This paper presents a detailed, numerical study on the performance of the standard phasing algorithms with random phase illumination (RPI). Phasing with high resolution RPI and the oversampling ratio $\sigma=4$ determines a unique phasing solution up to ...
Albert Fannjiang, Almoro, Anand, Bauschke, Fannjiang, Fienup, Fienup, Fienup, Gerchberg, Hayes, Hayes, Levi, Marchesini, Miao, Miao, Miao, Miao, Miao, Millane, Pitts, Wenjing Liao   +20 more
core   +3 more sources

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

Advanced 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, Solomon Amsalu Chekol, Julius Rasbach, Susanne Hoffmann‐Eifert, Stephan Menzel   +4 more
wiley   +1 more source

Optimizing 3D Bin Packing of Heterogeneous Objects Using Continuous Transformations in SE(3)

Advanced Intelligent Systems, EarlyView.
This article presents a method for solving the three‐dimensional bin packing problem for heterogeneous objects using continuous rigid‐body transformations in SE(3). A heuristic optimization framework combines signed‐distance functions, neural network approximations, point‐cloud bin modeling, and physics simulation to ensure feasibility and stability ...
Michele Angelini, Marco Carricato
wiley   +1 more source