MED-AGNeT: An attention-guided network of customized augmentation of samples based on conditional diffusion for textile defect detection by Jun Liu, Haolin Li, Hao Liu, Jiuzhen Liang

“…Ultimately, AGNet’s true positive rate (TPR), positive predictive value (PPV), and f-measure exceed those of the state-of-the-art (SOTA) algorithms by 1.88%, 0.05%, and 0.77%, respectively, and with a consistent model architecture, its parameter quantity is reduced by 56%.…”
Get full text

Machine learning-enhanced SERS for accurate azoospermia diagnosis via seminal plasma exosome analysis by Jiarui Wang, Shiyan Jiang, Jiaxin Shi, Jing Wang, Shengrong Du, Zufang Huang

“…Semen samples from healthy controls ([Formula: see text]) and azoospermic patients ([Formula: see text]) were collected, and their exosomal SERS spectra were obtained. Machine learning algorithms were employed to distinguish between the SERS profiles of healthy and azoospermic samples, achieving an impressive sensitivity of 99.61% and a specificity of 99.58%, thereby highlighting significant spectral differences. …”
Get full text

Enhancing unsupervised learning in medical image registration through scale-aware context aggregation by Yuchen Liu, Ling Wang, Xiaolin Ning, Yang Gao, Defeng Wang

“…Traditional registration algorithms often require significant computational resources due to iterative optimization, while deep learning approaches face challenges in managing diverse deformation complexities and task requirements. …”
Get full text

Multigoal-oriented a posteriori error control for heated material processing using a generalized Boussinesq model by Beuchler, Sven, Endtmayer, Bernhard, Lankeit, Johannes, Wick, Thomas

“…The error indicators are used to employ adaptive algorithms, which are substantiated with several numerical tests such as one benchmark and two further experiments that are motivated from laser material processing. …”
Get full text

Enhancing university remote language learning through innovative applications of artificial intelligence technologies amidst global challenges by N. Sarnovska, J. Rybinska, Yu. Mykhailichenko

“…The study delves into how AI algorithms analyse individual learner data to tailor educational content, providing a customized and adaptive learning experience. …”
Get full text

Elicitation of Norwegian EQ-5D-5L values for hypothetical and experience-based health states based on the EuroQol Valuation Technology (EQ-VT) protocol by Knut Stavem, Tonya Moen Hansen, Ylva Helland, Liv Ariane Augestad, Kim Rand, Andrew Garratt

“…Introduction Norway is one of several European countries that lacks a national value set and scoring algorithm for the EuroQol five dimensions (EQ-5D). …”
Get full text

Real-Time Hardware-in-the-Loop Laboratory Testing for Multisensor Sense and Avoid Systems by Giancarmine Fasano, Domenico Accardo, Lidia Forlenza, Alfredo Renga, Giancarlo Rufino, Urbano Tancredi, Antonio Moccia

“…This paper focuses on a hardware-in-the-loop facility aimed at real-time testing of architectures and algorithms of multisensor sense and avoid systems. It was developed within a research project aimed at flight demonstration of autonomous non-cooperative collision avoidance for Unmanned Aircraft Systems. …”
Get full text

Sentiment analysis of the Hamas-Israel war on YouTube comments using deep learning by Ashagrew Liyih, Shegaw Anagaw, Minichel Yibeyin, Yitayal Tehone

“…For classification model building, commonly used classification algorithms LSTM, Bi-LSTM, GRU, and Hybrid of CNN and Bi-LSTM were applied, and their performance is compared. …”
Get full text

U-Sodar: Noncontact Vital Sign Detection Technology Based on Ultrasonic Radar by Shuaiming HUANG, Xiaohua ZHU, Wubin WANG, Heng ZHAO, Hong HONG

“…The signal processing algorithm of U-Sodar adopts the graph processing technique of signal chord length and realizes accurate recovery of signal phase under 5 dB Signal-to-Noise Ratio (SNR) using picture filtering and then reconstruction. …”
Get full text

Leveraging mRNA technology for antigen based immuno-oncology therapies by Wei Zheng, Michele Ceccarelli, Charalampos S Floudas, Siranush Sarkizova

“…The identification and prioritization of patient-specific tumor neoantigens are based on advanced computational algorithms taking advantage of the profiling with next-generation sequencing considering factors involved in human leukocyte antigen (HLA)-peptide-T-cell receptor (TCR) complex formation, including peptide presentation, HLA-peptide affinity, and TCR recognition. …”
Get full text

A Dynamic Interval Auto-Scaling Optimization Method Based on Informer Time Series Prediction by Yu Ding, Chenhao Li, Zhengong Cai, Xinghao Wang, Bowei Yang

“…In the experiments conducted on the official World Cup forum load and Alibaba cluster CPU load, the Informer time series prediction algorithm demonstrated better long-sequence time series prediction capabilities compared to algorithms such as LSTM and RNN. …”
Get full text

PaleAle 6.0: Prediction of Protein Relative Solvent Accessibility by Leveraging Pre-Trained Language Models (PLMs) by Wafa Alanazi, Di Meng, Gianluca Pollastri

“…In particular, recent breakthroughs in deep learning—driven by the integration of natural language processing (NLP) algorithms—have significantly advanced the field of protein research. …”
Get full text

Robust Identification of Vegetation Change Using Shapelet-Based Temporal Segmentation of Landsat Time-Series Stacks: A Case Study in the Qilian Mountains by Lipeng Jiao, Randolph H. Wynne

“…Although many algorithms have been developed for monitoring annual vegetation change, most require complex controlling parameters or can only detect abrupt forest disturbances. …”
Get full text

Wireless sensor networks and structural health monitoring: Experiences with slab track infrastructures by Eduardo Cañete, Jaime Chen, Manuel Díaz, Luis Llopis, Bartolomé Rubio

“…On arrival at the station, the data are stored in a database, which is queried by an application to extract relevant information by means of analysis algorithms to detect and predict failures. The first real scenario tests the limits of the system under stress situations. …”
Get full text

Metabolic Syndrome Prediction Using Machine Learning Models with Genetic and Clinical Information from a Nonobese Healthy Population by Eun Kyung Choe, Hwanseok Rhee, Seungjae Lee, Eunsoon Shin, Seung-Won Oh, Jong-Eun Lee, Seung Ho Choi

“…A prediction model for MS was designed for a nonobese population using clinical and genetic polymorphism information with five machine learning algorithms, including naïve Bayes classification (NB). …”
Get full text

Optimizing Hydrogen Production in the Co-Gasification Process: Comparison of Explainable Regression Models Using Shapley Additive Explanations by Thavavel Vaiyapuri

“…This study aims to bridge these gaps through two primary objectives: (1) modeling the co-gasification process using seven different ML algorithms, and (2) developing a framework for evaluating model interpretability, ultimately identifying the most suitable model for process optimization. …”
Get full text

Identification of a Non-Linear Landing Gear Model Using Nature-Inspired Optimization by Felipe A.C. Viana, Valder Steffen Jr., Marcelo A.X. Zanini, Sandro A. Magalhães, Luiz C.S. Góes

“…In the present formulation two nature-based methods, namely the Genetic Algorithms and the Particle Swarm Optimization were used. …”
Get full text

Analysis of sensitive urban form indicators of flood susceptible prediction based on machine learning models by M. Srivanit, S. Pattanasri, N. Phichetkunbodee, S. Manokeaw, S. Sitthikankun, D. Rinchumphu

“…Eight urban factors were input into eleven multiclass classification algorithms to assess flood risk, and the results were displayed on a geographic information systems map.FINDINGS: The study discovered that the bagging decision tree algorithm model produced the best flood risk assessment model, with an accuracy of 88.58 percent compared to the government's flood simulation model results. …”
Get full text

Prediction of Visual Acuity after anti-VEGF Therapy in Diabetic Macular Edema by Machine Learning by Ying Zhang, Fabao Xu, Zhenzhe Lin, Jiawei Wang, Chao Huang, Min Wei, Weibin Zhai, Jianqiao Li

“…Six different machine learning algorithms were used to predict VA in patients after anti-VEGF therapy. …”
Get full text

Autopilot control unmanned aerial vehicle system for sewage defect detection using deep learning by Binay Kumar Pandey, Digvijay Pandey, S. K. Sahani

“…In order to get rid of the false negative outcome or false positive outcome, a guided image filter (GIF) is implemented in this proposed method during the pre‐processing stage. Afterwards, the algorithms Gabor transform (GT) and stroke width transform (SWT) were used to obtain the features of the UAV‐captured surveillance image. …”
Get full text