Determination of Spatiotemporal Gait Parameters Using a Smartphone’s IMU in the Pocket: Threshold-Based and Deep Learning Approaches by Seunghee Lee, Changeon Park, Eunho Ha, Jiseon Hong, Sung Hoon Kim, Youngho Kim

“…This study proposes a hybrid approach combining threshold-based algorithm and deep learning to detect four major gait events—initial contact (IC), toe-off (TO), opposite initial contact (OIC), and opposite toe-off (OTO)—using only a smartphone’s built-in inertial sensor placed in the user’s pocket. …”
Get full text

Mechanical performance prediction of basalt fiber reinforced concrete based on random forest and hyperparameter optimization by Dalian Bai, Junwen Chen, Jialiang Wang, Cunpeng Liu

“…This study applies the Random Forest (RF) algorithm combined with hyperparameter optimization methods including Grid Search (GS), Random Search (RS), Bayesian Optimization (BO), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Optuna Optimization (OO) to build a predictive model. …”
Get full text

Integrated Carbon Flow Tracing and Topology Reconfiguration for Low-Carbon Optimal Dispatch in DG-Embedded Distribution Networks by Rao Fu, Guofeng Xia, Sining Hu, Yuhao Zhang, Handaoyuan Li, Jiachuan Shi

“…To efficiently solve this complex constrained model, a novel Q-learning enhanced Moth Flame Optimization (QMFO) algorithm was proposed. QMFO synergized the global search capability of the Moth Flame Optimization (MFO) algorithm with the adaptive decision-making of Q-learning, embedding an adaptive exploration strategy to significantly enhance solution efficiency and accuracy for multi-objective problems. …”
Get full text

Effects of PET image reconstruction parameters and tumor-to-background uptake ratio on quantification of PET images from PET/MRI and PET/CT systems by Amena Ali Hussain, Eva Forssell-Aronsson, Tobias Rosholm, Esmaeil Mehrara

“…The Bayesian penalized likelihood (BPL) algorithm, recently introduced, uses a noise penalty factor (β) to achieve full convergence while controlling noise. …”
Get full text

A high performance approach to ensure image security during transmission by Adithya S Nair, Charvi Upreti, Advaith Arun, Renuka Devi S

“…The randomization is achieved through a Mersenne Twister algorithm. This project uses parallelization techniques to optimize computational performance and reduce the runtime. …”
Get full text

Informative Path Planning Using Physics-Informed Gaussian Processes for Aerial Mapping of 5G Networks by Jonas F. Gruner, Jan Graßhoff, Carlos Castelar Wembers, Kilian Schweppe, Georg Schildbach, Philipp Rostalski

“…Ensuring reliable coverage while maintaining certain requirements at its boundaries is crucial for successful deployment yet challenging without extensive measurements. …”
Get full text

Predicting soil organic carbon with ensemble learning techniques by using satellite images for precision farming by Shyamal Mundada, Pooja Jain

“…For testing dataset, RMSE ranged between 0.15 and 0.16 while sMAPE recorded as 0.19–0.20 and R2 was recorded as 0.12 for Random Forest and 0.03 for XGBoost algorithm. …”
Get full text

A Hybrid Approach to Cloud Data Security Using ChaCha20 and ECDH for Secure Encryption and Key Exchange by Rebwar Khalid Muhammed, Zryan Najat Rashid, Shaida Jumaah Saydah

“…This approach enhances security during data transmission and storage while mitigating the common vulnerabilities found in single-algorithm solutions. …”
Get full text

Automated irrigation of apple trees based on dendrometer sensors by Thainná Waldburger, Thomas Anken, Marianne Cockburn, Achim Walter, Matthias Hatt, Camilo Chiang, Hassan-Roland Nasser

“…Although the tested algorithm proved to be efficient, the results also indicated the potential for optimization. …”
Get full text

A Diagnostic Model of Breast Cancer Based on Digital Mammogram Images Using Machine Learning Techniques by Farouk A. K. Al-Fahaidy, Belal Al-Fuhaidi, Ishaq AL-Darouby, Faheem AL-Abady, Mohammed AL-Qadry, Abdurhman AL-Gamal

“…The first level classifier is used to categorize the given image as normal or abnormal while the second-level classifier is used for further classifying the abnormal image as either a malignant or benign cancer. …”
Get full text

SensorDBSCAN: Semi-Supervised Active Learning Powered Method for Anomaly Detection and Diagnosis by Petr Ivanov, Maria Shtark, Alexander Kozhevnikov, Maksim Golyadkin, Dmitry Botov, Ilya Makarov

“…The proposed approach combines a transformer-based encoder trained with a triplet-based contrastive learning objective and the classical density-based clustering algorithm DBSCAN, enabling strong feature extraction, efficient and interpretable feature space organization and simple clustering algorithm. …”
Get full text

YOLO-Ssboat: Super-Small Ship Detection Network for Large-Scale Aerial and Remote Sensing Scenes by Yiliang Zeng, Xiuhong Wang, Jinlin Zou, Hongtao Wu

“…To address this issue, we propose YOLO-ssboat, a novel small-target ship recognition algorithm based on the YOLOv8 framework. YOLO-ssboat integrates the C2f_DCNv3 module to extract fine-grained features of small vessels while mitigating background interference and preserving critical target details. …”
Get full text

A Study on the Impact of Obstacle Size on Training Models Based on DQN and DDQN by Lu Siyu, Tao Ye, Zeng Junwei, Zuo Qihuan

“…This paper presents a comparative analysis of Deep Q-Network (DQN) and Double Deep Q-Network (DDQN) algorithms in a simulated car racing environment, focusing on how variations in obstacle density affect each algorithm’s learning and trajectory planning, with the goal of enhancing adaptability and safety in autonomous driving systems. …”
Get full text

Scene Text Detection Based on Multi-scale Feature Extraction and Bidirectional Feature Fusion by LIAN Zhe, YIN Yanjun, ZHI Min, XU Qiaozhi

“…The proposed algorithm constructs a multi-scale feature extraction module based on convolutional kernels of different sizes to take into account the feature extraction of text targets of different scales and shapes, while capturing contextual information dependencies at different distances. …”
Get full text

Characteristics stochastic analysis of long and narrow deep excavations under soil spatial variability by Shouhua Liu, Zhaoliang Wang, Yadong Chen, Guohua Fang, Yiding Zhao, Junsheng Yang, Huasheng Sun

“…This algorithm was created within the framework of random field theory and Monte Carlo simulation. …”
Get full text

A Formal Fuzzy Concept-Based Approach for Association Rule Discovery with Optimized Time and Storage by Gamal F. Elhady, Haitham Elwahsh, Maazen Alsabaan, Mohamed I. Ibrahem, Ebtesam Shemis

“…The proposed approach incorporates a ‘fuzzy min-max basis algorithm’ to derive exact and approximate rule bases from the extracted fuzzy closed item sets, eliminating redundancy while preserving valuable insights. …”
Get full text

Enhancing grid-connected PV-EV charging station performance through a real-time dynamic power management using model predictive control by Aziz Watil, Hamid Chojaa

“…Furthermore, these systems often require multiple power electronics converters, increasing complexity and costs while reducing overall system efficiency. To overcome these limitations, the proposed algorithm dynamically switches between on-grid and off-grid modes based on real-time weather conditions, grid availability, and the state of charge of the battery electric vehicle (BEV). …”
Get full text

Iterative Fast Super-Twisting Flux Sliding Mode Observer for SPMSM with Tangent Quadrature Phase-Locked Loop by Fujiong Zhao, Yunxia Xie, Jianfeng Mao, Yingjie Xu, Gaosheng Li, Rongsheng Jia, Weigang Wang

“…Notably, the feedback matrix is redesigned to ensure the algorithm’s stability during speed reversal. Furthermore, an iterative calculation strategy is implemented under low-speed and light-load conditions, improving steady-state accuracy of estimated flux while avoiding increased computational burden at medium and high speeds. …”
Get full text

Stellar Ages: A Code to Infer Properties of Stellar Populations by Joseph J. Guzman, Jeremiah W. Murphy, Andrés F. Barrientos, Benjamin F. Williams, Julianne J. Dalcanton

“…Stellar Ages does both, combining the strengths of these approaches to provide precise individual ages for stars while leveraging population-level constraints. We verify the algorithm’s capabilities by determining the age of synthetic stellar populations and actual stellar populations surrounding a nearby supernova, SN 2004dj. …”
Get full text

South China Sea SST Fronts, 2015–2022 by Igor M. Belkin, Yi-Tao Zang

“…The SST data from 2015 to 2022 were processed with the Belkin–O’Reilly algorithm to generate maps of SST gradient magnitude GM. …”
Get full text