Detection Technology for Catenary Stagger Value Based on Acceleration Signals by CHEN Hongming, ZHOU Ning, LU Wenwei, YANG Zixian, CHENG Yao, WANG Dong, ZHANG Weihua

“…［Result & Conclusion］ The proposed method accurately detects catenary stagger values across various operating speeds, achieving a root mean square error as low as 5.84, outperforming other existing algorithms. In brief, the study effectively enhances the measurement efficiency of catenary stagger values, avoiding the limitations imposed by previous methods on operational environmental conditions, and provides a novel approach for catenary stagger value detection.…”
Get full text

Advanced Classifiers and Feature Reduction for Accurate Insomnia Detection Using Multimodal Dataset by Ameya Chatur, Mostafa Haghi, Nagarajan Ganapathy, Nima TaheriNejad, Ralf Seepold, Natividad Martinez Madrid

“…Our results demonstrate that the ensemble classifiers generalize well on the dataset regardless of the feature count, while other algorithms are hindered by the curse of dimensionality.…”
Get full text

Enhancing Dongba Pictograph Recognition Using Convolutional Neural Networks and Data Augmentation Techniques by Shihui Li, Lan Thi Nguyen, Wirapong Chansanam, Natthakan Iam-On, Tossapon Boongoen

“…The recognition of Dongba pictographs presents significant challenges due to the pitfalls in traditional feature extraction methods, classification algorithms’ high complexity, and generalization ability. …”
Get full text

Research and predictive analysis of pyrolysis characteristics of multi-source organic solid wastes by ZHANG Zihang, XING Bo, MA Zhongqing, HU Yanjun, ZHANG Zhixiao, YUAN Shizhen, LU Rufei, CHEN Yingquan, WANG Shurong*

“…Subsequently, the random forest (RF), gradient boosting decision tree (GBDT), and extreme gradient boosting (XGBoost) algorithms were utilized to predict the high heating value (HHV) of organic solid waste, the distribution of fast pyrolysis products, and the thermogravimetric curves under various atmospheres. …”
Get full text

From 6G to <i>SeaX-G</i>: Integrated 6G TN/NTN for AI-Assisted Maritime Communications—Architecture, Enablers, and Optimization Problems by Anastasios Giannopoulos, Panagiotis Gkonis, Alexandros Kalafatelis, Nikolaos Nomikos, Sotirios Spantideas, Panagiotis Trakadas, Theodoros Syriopoulos

“…Furthermore, the critical Artificial Intelligence/Machine Learning (AI/ML) concepts and algorithms are described to highlight their potential in optimizing maritime functionalities. …”
Get full text

Virtual Reality-Assisted Goalkeeper Training for Upper Limb Rehabilitation in a Safe and Adapted Patient Environment by Vanesa Herrera, Javier Albusac, Eusebio Angulo, Carlos Gonzalez-Morcillo, Ana de Los Reyes-Guzman, David Vallejo

“…The proposed system aims to simplify technology use, featuring a single VR headset integrating body tracking, and functional and spatial-temporal data analysis algorithms, without the need for additional tracking devices. …”
Get full text

A Human-Centric, Uncertainty-Aware Event-Fused AI Network for Robust Face Recognition in Adverse Conditions by Akmalbek Abdusalomov, Sabina Umirzakova, Elbek Boymatov, Dilnoza Zaripova, Shukhrat Kamalov, Zavqiddin Temirov, Wonjun Jeong, Hyoungsun Choi, Taeg Keun Whangbo

“…Face recognition systems often falter when deployed in uncontrolled settings, grappling with low light, unexpected occlusions, motion blur, and the degradation of sensor signals. Most contemporary algorithms chase raw accuracy yet overlook the pragmatic need for uncertainty estimation and multispectral reasoning rolled into a single framework. …”
Get full text

Leveraging citizen science to classify and track benthic habitat states: An unsupervised UMAP-HDBSCAN pipeline applied to the global reef life survey dataset by Clément Violet, Aurélien Boyé, Stanislas Dubois, Graham J. Edgar, Elizabeth S. Oh, Rick D. Stuart-Smith, Martin P. Marzloff

“…We applied an innovative clustering pipeline that combines three algorithms — Uniform Manifold Approximation and Projection (UMAP) for dimension reduction; Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) — to identify benthic habitat states and Shapley values to interpret the clusters identified. …”
Get full text

Intelligent energy management of microgrids using machine learning: Leveraging random forest models for solar and wind power by Hasanur Zaman Anonto, Md Ismail Hossain, Abu Shufian, Md. Shaoran Sayem, S M Tanvir Hassan Shovon, Protik Parvez Sheikh, Sadman Shahriar Alam

“…The study at hand suggests dedicating a new type of energy management of the microgrid by using the machine-learning algorithms, namely the Random Forest (RF) regressor along with real-time forecasting the energy use and renewable-energy production. …”
Get full text

Synthetic and real-world datasets for crosswalk segmentation under diverse weather and lighting conditionsMendeley Data by Krešimir Romić, Hrvoje Leventić, Marija Habijan, Irena Galić

“…This dataset addresses the scarcity of publicly available crosswalk segmentation data with environmental diversity and has potential applications in developing and benchmarking computer vision algorithms for assistive navigation systems, investigating synthetic data augmentation efficacy, and advancing pedestrian safety technologies.…”
Get full text

Cyber-Physical Systems Enabled Transport Networks in Smart Cities: Challenges and Enabling Technologies of the New Mobility Era by Amit Pundir, Sanjeev Singh, Manish Kumar, Anil Bafila, Geetika J. Saxena

“…However, the major intellectual challenge lies in effectively designing-developing-deploying models and algorithms to harness the powers of the integrated TCPS system implemented in the intended environment.…”
Get full text

A Machine Learning Platform for Isoform-Specific Identification and Profiling of Human Carbonic Anhydrase Inhibitors by Lisa Piazza, Miriana Di Stefano, Clarissa Poles, Giulia Bononi, Giulio Poli, Gioele Renzi, Salvatore Galati, Antonio Giordano, Marco Macchia, Fabrizio Carta, Claudiu T. Supuran, Tiziano Tuccinardi

“…<b>Methods:</b> By integrating four molecular representations with four ML algorithms, we built 64 classification models, each extensively optimized and validated. …”
Get full text

Analysis of soil salinization and land use change under water conservation retrofit in the Hetao irrigation district by Yi Zhao, Shuya Yang, Haibin Shi, Haoqi Han, Yunlei Dong, Xianyue Li, Jianwen Yan, Yan Yan, Xu Dou, Feng Tian, Qingfeng Miao

“…We establish soil sampling sites in this region, employ Google Earth Engine algorithms to develop models for soil salinity inversion and land use classification, and analyze the change patterns of land salinization and land use types. …”
Get full text

Classification accuracy of pain intensity induced by leg blood flow restriction during walking using machine learning based on electroencephalography by Hirotatsu Imai, Yuya Kanie, Shusuke Yoshimoto, Natsuki Yamamoto, Masayuki Furuya, Takahito Fujimori, Seiji Okada

“…Three machine learning algorithms—Random Forest, eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine—were employed. …”
Get full text

Permanent terrestrial laser scanning for near-continuous environmental observations: Systems, methods, challenges and applications by Roderik Lindenbergh, Katharina Anders, Mariana Campos, Daniel Czerwonka-Schröder, Bernhard Höfle, Mieke Kuschnerus, Eetu Puttonen, Rainer Prinz, Martin Rutzinger, Annelies Voordendag, Sander Vos

“…Extracting information from these 4D data sets turns out to be challenging, first, because of insufficient knowledge on error budget and correlations, and, second, because of lack of algorithms, benchmarks, and best-practice workflows. …”
Get full text

Fragmenstein: predicting protein–ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology by Matteo P. Ferla, Rubén Sánchez-García, Rachael E. Skyner, Stefan Gahbauer, Jenny C. Taylor, Frank von Delft, Brian D. Marsden, Charlotte M. Deane

“…Abstract Current strategies centred on either merging or linking initial hits from fragment-based drug design (FBDD) crystallographic screens generally do not fully leaverage 3D structural information. We show that an algorithmic approach (Fragmenstein) that ‘stitches’ the ligand atoms from this structural information together can provide more accurate and reliable predictions for protein–ligand complex conformation than general methods such as pharmacophore-constrained docking. …”
Get full text

Clinical Phenotypes of Patients with Anti-DFS70/LEDGF Antibodies in a Routine ANA Referral Cohort by Makoto Miyara, Roger Albesa, Jean-Luc Charuel, Mohamed El Amri, Marvin J. Fritzler, Pascale Ghillani-Dalbin, Zahir Amoura, Lucile Musset, Michael Mahler

“…Although anti-DFS70 antibodies cannot exclude the presence of SARD, the likelihood is significantly lower than in patients with other IIF patterns and should be included in test algorithms for ANA testing.…”
Get full text

Seismic Identification and Characterization of Deep Strike-Slip Faults in the Tarim Craton Basin by Fei Tian, Wenhao Zheng, Aosai Zhao, Jingyue Liu, Yunchen Liu, Hui Zhou, Wenjing Cao

“…This model incorporates select seismic attributes and leverages fusion algorithms like K-means, ellipsoid growth, and wavelet transformations. …”
Get full text

The Hourglass Simulation: A Catalog for the Roman High-latitude Time-domain Core Community Survey by B. M. Rose, M. Vincenzi, R. Hounsell, H. Qu, L. Aldoroty, D. Scolnic, R. Kessler, P. Macias, D. Brout, M. Acevedo, R. C. Chen, S. Gomez, E. Peterson, D. Rubin, M. Sako, the Roman Supernova Project Infrastructure Team

“…Additionally, Hourglass is a useful data set to train machine learning classification algorithms. We show that SCONE is able to photometrically classify Type Ia supernovae with high precision (∼95%) to a z > 2. …”
Get full text

Prevention and management of degenerative lumbar spine disorders through artificial intelligence-based decision support systems: a systematic review by Paolo Giaccone, Federico D’Antoni, Fabrizio Russo, Luca Ambrosio, Giuseppe Francesco Papalia, Onorato d’Angelis, Gianluca Vadalà, Albert Comelli, Luca Vollero, Mario Merone, Rocco Papalia, Vincenzo Denaro

“…Several different machine learning and deep learning algorithms were employed, and their predictive ability on clinical, demographic, psychosocial, and imaging data was assessed. …”
Get full text