Handover Strategy for LEO Satellite Networks Using Bipartite Graph and Hysteresis Margin by Sahar Eydian, Maryam Hosseini, Gunes Karabulut Kurt

“…The proposed approach utilizes the Kuhn-Munkres (KM) algorithm to achieve optimal matching with maximum weight, thereby ensuring efficient load distribution and high-quality communication. …”
Get full text

Experimental study on mechanical properties of triaxial geogrid reinforced marine coral sand-clay mixture based on 3D printing technology by Danda Shi, Kaiwei Xu, Zhiming Chao, Zhiming Chao, Peng Cui, Peng Cui

“…Based on the experimental results, a dataset was established, while a novel machine learning model named GP-BPNN was proposed, integrating genetic algorithm (GA), particle swarm optimization (PSO), and backpropagation neural network (BPNN). …”
Get full text

A data driven approach to urban area delineation using multi source geospatial data by Chenyu Fang, Lin Zhou, Xinyue Gu, Xing Liu, Martin Werner

“…Abstract This study introduces a data-driven, bottom-up approach to urban delineation, integrating feature engineering with the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, which represents a significant improvement in precision and methodology compared to traditional approaches that rely on simplistic OpenStreetMap (OSM) road node data aggregations. …”
Get full text

Ripening Study Based on Multi-Structural Inversion of Cherry Tomato qMRI by Yanan Li, Jingfa Yao, Wenhui Yang, Zhao Wei, Peng Luan, Guifa Teng

“…The structural T2 relaxation inversion was refined by integrating an ACS-CIPSO algorithm. This approach addresses the challenge of low signal-to-noise ratios in multi-echo MRI images from low-field equipment by introducing an innovative solution that effectively reduces voxel noise while retaining structural relaxation variability. …”
Get full text

Three-Dimensional Imaging of High-Contrast Subsurface Anomalies: Composite Model-Constrained Dual-Parameter Full-Waveform Inversion for GPR by Siyuan Ding, Deshan Feng, Xun Wang, Tianxiao Yu, Shuo Liu, Mengchen Yang

“…Numerical experiments show that TV regularization can optimize permittivity reconstruction, while MSG regularization is more suitable for conductivity inversion. …”
Get full text

Disulfide bond-related gene signature development for bladder cancer prognosis prediction and immune microenvironment characterization by Hua Huang, Haiyan Shao, Yifan Wang, Lili Ge

“…The DRPS model, optimized by the StepCox[backward] algorithm, demonstrated robust prognostic accuracy across four validation cohorts (mean C-index = 0.658). …”
Get full text

Delphi consensus statement for the management of delayed post-polypectomy bleeding by Enrique Rodríguez de Santiago, Sandra Pérez de la Iglesia, Diego de Frutos, José Carlos Marín-Gabriel, Carolina Mangas-SanJuan, Raúl Honrubia López, Hugo Uchima, Marta Aicart-Ramos, Miguel Ángel Rodríguez Gandía, Eduardo Valdivielso Cortázar, Felipe Ramos Zabala, Marco Antonio Álvarez, Marina Solano Sánchez, Jesús Manuel González Santiago, Eduardo Albéniz, Gonzalo Hijos-Mallada, Nerea Castro Quismondo, Miguel Fraile-López, David Martínez Ares, Javier Tejedor-Tejada, Luis Hernández, Joan B. Gornals, Sergi Quintana-Carbo, Juan Ocaña, João A. Cunha Neves, Juan Martínez Martínez, María López-Cerón Pinilla, Carlos Dolz Abadía, María Pellisé

“…These recommendations aim to improve patient outcomes and optimize healthcare resources while fostering a standardized approach to this common adverse event.…”
Get full text

Efficient Positive Semidefinite Matrix Approximation by Iterative Optimisations and Gradient Descent Method by Vali Asimit, Runshi Wang, Feng Zhou, Rui Zhu

“…Experiments on randomly generated data show that this method enjoys better resilience to noise while maintaining good accuracy. For example, in our experiments with noised data, the iterative quadratic programming algorithm performs best in more than 41% to 67% of the samples when the standard deviation of noise is 0.02, and the gradient descent method performs best in more than 70% of the samples when the standard deviation of noise is 0.2. …”
Get full text

A Target Near-Field Scattering Measurement Technique Utilizing 3D Near-Field Imaging via Cylindrical Scanning by Zongkai Yang, Jingcheng Zhao, Weikang Si, Changyu Lou, Xin Zhao, Jungang Miao

“…To resolve this matter, we propose a hybrid 3D imaging algorithm that is optimized for cylindrical sampling and operates in both the wavenumber domain and time domain (WDTD). …”
Get full text

Construction of reliable QSPR models for predicting the impact sensitivity of nitroenergetic compounds using correlation weights of the fragments of molecular structures by Shahram Lotfi, Shahin Ahmadi, Alla P. Toropova, Andrey A. Toropov

“…This study aimed to develop a QSPR model for predicting the impact sensitivity of 404 nitro compounds using the Monte Carlo algorithm implemented in CORAL-2023 software. The Simplified Molecular Input Line Entry System (SMILES) was employed to represent the molecular structures, while correlation weight descriptors were computed. …”
Get full text

Practical DU-CU Placement in an Enhanced Mobile BroadBand Request During 5G Traffic by Ange Joel Nounga Njanda, Joao Filipe Muchanga, Hojjat Baghban, Karcius Day R. Assis

“…The objective is to identify the optimal candidate sites for deploying the DU and CU functions to ensure a continuous service path from the RU to the DC. …”
Get full text

Prediction Model of Household Carbon Emission in Old Residential Areas in Drought and Cold Regions Based on Gene Expression Programming by Shiao Chen, Yaohui Gao, Zhaonian Dai, Wen Ren

“…., electricity usage and heating energy consumption) were selected using Pearson correlation analysis and the Random Forest (RF) algorithm. Subsequently, a hybrid prediction model was constructed, with its parameters optimized by minimizing the root mean square error (RMSE) as the fitness function. …”
Get full text

An Intelligent Method for C++ Test Case Synthesis Based on a Q-Learning Agent by Serhii Semenov, Oleksii Kolomiitsev, Mykhailo Hulevych, Patryk Mazurek, Olena Chernyk

“…An explicit synthesis algorithm constructs new test cases by selecting API calls from a learned policy encoded in a Q-table. …”
Get full text

Reconstruction for Scanning LiDAR with Array GM-APD on Mobile Platform by Di Liu, Jianfeng Sun, Wei Lu, Sining Li, Xin Zhou

“…This method avoids the need for field-of-view registration, improves data utilization, and reduces the complexity of the algorithm while eliminating the effect of LiDAR motion. …”
Get full text

Towards Intelligent Unmanned Adversarial Games: A Reinforcement Learning Framework with the PHP-ROW Method by Guoqing Shi, Yi Cao, Dinghan Wang, Qiming Yang, Jiandong Zhang, Zhuoyong Shi

“…The superiority of the PHP-ROW method is showcased by contrasting it against the conventional proximal policy optimization (PPO) algorithm. Conclusively, the utility and efficacy of the presented framework are corroborated through human–machine adversarial game simulations in a hyper-realistic environment. …”
Get full text

Intelligent Robot in Unknown Environments: Walk Path Using Q-Learning and Deep Q-Learning by Mouna El Wafi, My Abdelkader Youssefi, Rachid Dakir, Mohamed Bakir

“…This eliminates the need for manually fixed parameters and enables the learning algorithm to automatically determine optimal values, ensuring adaptability to diverse environments rather than being constrained to specific cases. …”
Get full text

Heuristic Binary Search for Modulated Predictive Control by Rafael FIgueiredo, Igor Oliani, Angelo Lunardi, Alfeu J. Sguarezi Filho

“…This paper introduces the Heuristic Binary Search, an intelligent search algorithm that efficiently explores the solution space, accommodating arbitrary cost function constraints similar to Finite Control Set, while maintaining a fixed switching frequency. …”
Get full text

An Enhanced Approach for Remaining Useful Life Prediction of Bearings Using Incomplete Lifecycle Data by Xunmeng An, Chao Zhang, Caiye Liu, Wentao Zhao

“…Accurately predicting the remaining useful life (RUL) of rolling bearings is crucial for ensuring optimal equipment operation and timely maintenance. …”
Get full text

Economic Production Quantity Model under Back Order, Rework, Imperfect Quality, Electricity Tariff, and Emission Tax by Dana Marsetiya Utama, Yolanda Dwi Asmara Putri, Shanty Kusuma Dewi

“…To solve this complex optimization problem, the Genetic Algorithm (GA) is used for its efficiency in handling non-linear and combinatorial problems. …”
Get full text

Blind super-resolution network based on local fuzzy discriminative loss for fabric data augmentation by Ning Dai, Xiaohan Hu, Kaixin Xu, Xudong Hu, Yanhong Yuan, Bo Cao, Luhong Shi

“…To address these challenges, this paper proposes a blind super-resolution algorithm for fabric defect data augmentation. The model is based on Real-ESRGAN and has been optimized specifically for the resolution degradation module to better adapt to the resolution degradation process in fabric images. …”
Get full text