SGDO-SLAM: A Semantic RGB-D SLAM System with Coarse-to-Fine Dynamic Rejection and Static Weighted Optimization by Qiming Hu, Shuwen Wang, Nanxing Chen, Wei Li, Jiayu Yuan, Enhui Zheng, Guirong Wang, Weimin Chen

“…The method achieves accurate dynamic scene perceptions and improves the accuracy of the system’s positioning. …”
Get full text

Comparison of Bioelectric Signals and Their Applications in Artificial Intelligence: A Review by Juarez-Castro Flavio Alfonso, Toledo-Rios Juan Salvador, Aceves-Fernández Marco Antonio, Tovar-Arriaga Saul

“…AI-driven approaches are shown to have the potential to enhance diagnostic precision and improve patient outcomes. However, further research is needed to optimize these models for diverse clinical environments and fully exploit the interaction between bioelectrical signals and AI technologies.…”
Get full text

Reliability and Quality of Complex Systems by I.V. Peshkov, V.A. Zhigulin, N.A. Fortunova

“…The general principles of operation of DoA estimation algorithms are presented. The effect of mutual coupling of antenna array elements is considered, and the method of accounting for the effect when modelling the received signal is given. …”

A Novel Ensemble Classifier Selection Method for Software Defect Prediction by Xin Dong, Jie Wang, Yan Liang

“…This method makes full use of the diversity characteristics of base learners, leverages their classification ability, optimizes the selection method for ensemble learning, and enhances the predictive performance of the ensemble model. The experimental results demonstrate that the DFD ensemble learning-based software defect prediction model outperforms the ten other models, including five common machine learning (ML) classification algorithms (logistic regression (LR), naïve Bayes (NB), K-nearest neighbor (KNN), decision tree (DT), and support vector machine (SVM)), two deep learning (DL) algorithms (multi-layer perceptron (MLP) and convolutional neural network (CNN)), and three ensemble learning algorithms (random forest (RF), extreme gradient boosting (XGB), and stacking). …”
Get full text

The moderating role of professional grief in the relationship between job stress dimensions and turnover intention among nurses by Xue Liang, Jue Wang

“…Methods This study utilized linear regression models and the Extreme Gradient Boosting machine (XGBoost) learning algorithm to analyze the impact of the total score of job stress and their dimensions on turnover intention. …”
Get full text

Optimization of Geometric Characteristics of Cycloidal Profiles of Gerotor Hydraulic Machines by S. O. Kireev, A. R. Lebedev, M. V. Korchagina

“…The basic research method was modeling the gerotor machine profile using Mathcad computer mathematics system. …”
Get full text

Investigation of the ecology of winter plankton of Lake Baikal using complex instrumental methods by E. Yu. Naumova, T. P. Rzhepka, M. M. Makarov, A. S. Olshukov, K. M. Kucher, M. Z. Magomedova, E. S. Troitskaya

“…The obtained field data will make it possible to further improve the pattern recognition algorithm in the software of the holographic installation for the specific conditions of Lake Baikal. …”
Get full text

Assessing the Soldier Survivability Tradespace Using a Single IMU by Matthew P. Mavor, Victor C. H. Chan, Kristina M. Gruevski, Linda L. M. Bossi, Thomas Karakolis, Ryan B. Graham

“…Presented are three models based on Indoor, Section Attack (outdoors), and a General approach. …”
Get full text

Graph Neural Network With Hessian-Based Locally Linear Embedding for Cancer Metastasis Analysis in Lymph Nodes Using DeepLab Segmentation by Senthil Jayapal, R. Annamalai

“…These segmented regions are then modeled as graphs, where the nodes signify the segmented areas and the edges reflect spatial and functional coupling. …”
Get full text

Subtyping Service Receipt in Personality Disorder Services in South London: Observational Validation Study Using Latent Profile Analysis by Jack Steadman, Rob Saunders, Mark Freestone, Robert Stewart

“…ConclusionsThese results suggest that routinely collected data may be used to classify likely engagement subtypes among patients with complex needs. The algorithm identified factors associated with service use and has the potential to inform clinical decision-making to improve treatment for individuals with complex needs.…”
Get full text

An illustration of multi-class roc analysis for predicting internet addiction among university students. by Nishat Tasnim Thity, Atikur Rahman, Adisha Dulmini, Mst Nilufar Yasmin, Rumana Rois

“…We identified the important features related to IA using the Boruta algorithm. Predictions were made using different machine learning (ML) (decision tree (DT), random forest (RF), support vector machines (SVMs), and logistic regression (LR)) models. …”
Get full text

Adaptive Support Weight-Based Stereo Matching with Iterative Disparity Refinement by Alexander Richter, Till Steinmann, Andreas Reichenbach, Stefan J. Rupitsch

“…Real-time 3D reconstruction in minimally invasive surgery improves depth perception and supports intraoperative decision-making and navigation. …”
Get full text

Robust Forward-Looking Sonar-Image Mosaicking Without External Sensors for Autonomous Deep-Sea Mining by Xinran Liu, Jianmin Yang, Changyu Lu, Enhua Zhang, Wenhao Xu

“…For image fusion, a radial adaptive fusion algorithm with a protective frame is proposed to improve edge transitions and preserve structural consistency in the resulting panoramic image. …”
Get full text

Experimental Study of Trajectory Features for the Recognition of Low-Flying Low-Speed Radar Targets Using Passive Coherent Radar Systems by V. L. Dao, A. A. Konovalov, M. H. Le

“…The knowledge of differences between the flight path of UAVs and birds can improve the quality of the UAV recognition problem.…”
Get full text

Bio-Inspired Compliant Joints and Economic MPC Co-Design for Energy-Efficient, High-Speed Locomotion in Snake-like Robots by Shuai Zhou, Gengbiao Chen, Mingyu Gong, Jing Liu, Peng Xu, Binshuo Liu, Nian Yin

“…The joint mimics biological skeletal flexibility using specialized wheeled mechanisms and adaptive parallel linkages, while the control network enables adaptive gait generation and seamless transitions through a phase-smoothing algorithm. Critically, this work adopts a synergistic design philosophy where mechanical components and control parameters are co-optimized through shared dynamic modeling. …”
Get full text

Privacy-Preserving Hierarchical Reinforcement Learning Framework for Task Offloading in Low-Altitude Vehicular Fog Computing by Zhiwei Wei, Jingxin Mao, Bing Li, Rongqing Zhang

“…The framework consists of two levels: the local level provides Deep Reinforcement Learning (DRL) models for task vehicles and UAVs, and the cross-regional contextual level for coordinating the local experiences. …”
Get full text

CPT-DF: Congestion Prediction on Toll-Gates Using Deep Learning and Fuzzy Evaluation for Freeway Network in China by Tongtong Shi, Ping Wang, Xudong Qi, Jiacheng Yang, Rui He, Jingwen Yang, Yu Han

“…The comparative tests show the proposed CPT-DF (congestion prediction on toll-gates using deep learning and fuzzy evaluation) outperforms the current-used other models by 6-15%. The successful prediction could extend to the real-time prediction and early warning of traffic congestion in the toll system to improve the intelligent level of traffic emergency management and guidance on the key road of disasters to some extent.…”
Get full text

Cognitive performance classification of older patients using machine learning and electronic medical records by Monika Richter-Laskowska, Ewelina Sobotnicka, Adam Bednorz

“…Developing efficient diagnostic tools is critical, and machine learning (ML) algorithms have shown potential for improving the accuracy of cognitive impairment classification. …”
Get full text

Autonomous unmanned aerial vehicles exploration for semantic indoor reconstruction using 3D Gaussian splatting by Hao Xuan Zhang, Yilin Yang, Zhengbo Zou

“…Keeping an up-to-date three-dimensional (3D) representation of buildings is a crucial yet time-consuming step for Building Information Modeling (BIM) and digital twins. To address this issue, we propose ICON (Intelligent CONstruction) drone, an unmanned aerial vehicle (UAV) designed to navigate indoor environments autonomously and generate point clouds. …”
Get full text

Automated Class Imbalance Learning via Few-Shot Multi-Objective Bayesian Optimization With Deep Kernel Gaussian Processes by Zhaoyang Wang, Shuo Wang, Damien Ernst, Chenguang Xiao

“…Then, these surrogate models with prior optimization knowledge are combined with the Expected Hypervolume Improvement (EHVI) acquisition function in a Bayesian optimization framework to efficiently discover Pareto-optimal configurations for the target task, which enables AutoCIL-FMOBO to jointly optimize key components, such as resampling methods, classifiers, and their hyperparameters, under a multi-objective setting. …”
Get full text