Establishing a differential diagnosis model between primary membranous nephropathy and non-primary membranous nephropathy by machine learning algorithms by Shangmei Cao, Shaozhe Yang, Bolin Chen, Xixia Chen, Xiuhong Fu, Shuifu Tang

“…Context Four algorithms with relatively balanced complexity and accuracy in deep learning classification algorithm were selected for differential diagnosis of primary membranous nephropathy (PMN).Objective This study explored the most suitable classification algorithm for PMN identification, and to provide data reference for PMN diagnosis research.Methods A total of 500 patients were referred to Luo-he Central Hospital from 2019 to 2021. …”
Get full text

Context-Adaptable Deployment of FastSLAM 2.0 on Graphic Processing Unit with Unknown Data Association by Jessica Giovagnola, Manuel Pegalajar Cuéllar, Diego Pedro Morales Santos

“…The parallelization process involves identifying the parameters affecting the computational complexity in order to distribute the computation among single multiprocessors as efficiently as possible. …”
Get full text

Interaction of the Antibiotic Rifampicin with Lipid Membranes by Rui M. S. Santos, Jaime Samelo, Alexandre C. Oliveira, Margarida M. Cordeiro, Maria Julia Mora, Gladys E. Granero, Hugo A. L. Filipe, Luís M. S. Loura, Maria João Moreno

“…It is a relatively large and structurally complex molecule, including numerous polar groups. …”
Get full text

Dynamic Optimization of Xylitol Production Using Legendre-Based Control Parameterization by Eugenia Gutiérrez, Marianela Noriega, Cecilia Fernández, Nadia Pantano, Leandro Rodriguez, Gustavo Scaglia

“…The proposed technique employs Legendre polynomials to parameterize two control actions (the feeding rates of glucose and xylose), and it uses a hybrid optimization algorithm combining Monte Carlo sampling with genetic algorithms for coefficient selection. Unlike traditional optimization approaches based on piecewise parameterization, which produce discontinuous control profiles and require post-processing, this method generates smooth profiles directly applicable to real systems. …”
Get full text

Synthesis of Rhodamine TEMPO Conjugates via Isonitrile‐Based Multicomponent‐Reactions for Mitochondria‐Targeted ROS‐Detection in Cancer Cells by Haider N. Sultani, Ibrahim M. Morgan, Hidayat Hussain, Haleh H. Haeri, Dariush Hinderberger, Goran N. Kaluđerović, Bernhard Westermann

Get full text

Reconstruction of U.S. Regional-Scale Soybean SIF Based on MODIS Data and BP Neural Network by YAO Jianen, LIU Haiqiu, YANG Man, FENG Jinying, CHEN Xiu, ZHANG Peipei

“…The Pearson correlation coefficient between the original OCO-2 SIF data and MODIS GPP stood were at a modest 0.53. …”
Get full text

Analysis and comprehensive evaluation of fruit quality of 39 sweet cherry accessions in Shanxi region by HOU Xuan, YIN Kaihua, NIE Guowei, LI Kai, ZHANG Yanan, ZHANG Xiaoping, TIAN Yongqiang

“…Correlation analysis showed that the relationships among various phenotypic traits of different germplasms were close and complex. Cluster analysis divided the 39 sweet cherries into three groups. …”
Get full text

Adaptive federated learning for resource-constrained IoT devices through edge intelligence and multi-edge clustering by Fahad Razaque Mughal, Jingsha He, Bhagwan Das, Fayaz Ali Dharejo, Nafei Zhu, Surbhi Bhatia Khan, Saeed Alzahrani

“…This architecture enables edge AI nodes to collaborate, dynamically selecting significant nodes and optimizing global learning tasks with low complexity. …”
Get full text

Optimizing Traffic Speed Prediction Using a Multi-Objective Genetic Algorithm-Enhanced RNN for Intelligent Transportation Systems by C. Swetha Priya, F. Sagayaraj Francis

“…A comprehensive comparative study demonstrates that our approach outperforms state-of-the-art models in both prediction accuracy and computational efficiency.…”
Get full text

Hybrid AI-Based Framework for Renewable Energy Forecasting: One-Stage Decomposition and Sample Entropy Reconstruction with Least-Squares Regression by Nahed Zemouri, Hatem Mezaache, Zakaria Zemali, Fabio La Foresta, Mario Versaci, Giovanni Angiulli

“…This process effectively extracts meaningful components while reducing background noise, improving data quality, and minimizing uncertainty. The complexity of these components is assessed using entropy-based selection to retain only the most relevant features. …”
Get full text

HRT-Net: A Cell-free Cooperative Sensing Method Based on Attention-weighted Hierarchical Network by Shengheng LIU, He YAN, Xingkang LI, Dazhuan XU, Dongming WANG, Yongming HUANG

“…HRT-Net is designed to enhance multi-station collaborative sensing problems for Dual-Functional Radar-Communication (DFRC) systems, offering accurate and resource-efficient target location estimation. First, the sensing area is divided into sub-regions and a lightweight region selection network employing depthwise separable convolution; this approach coarsely identifies the target’s sub-region, reducing computational demands and enabling extensive area coverage. …”
Get full text

Integrating Learning-Driven Model Behavior and Data Representation for Enhanced Remaining Useful Life Prediction in Rotating Machinery by Tarek Berghout, Eric Bechhoefer, Faycal Djeffal, Wei Hong Lim

“…The first part focuses on comprehensive data preprocessing using only feature scaling and selection via random forest (RF) algorithm, streamlining the process by minimizing human intervention while managing data complexity. …”
Get full text

small industrial cities. Heritage update. Tatiana Bystrova. Review by Mariya S. Frolova

“…The author shows the foundations of the stability of this system, the specifics of the architecture of industrial buildings and complexes, and the everyday culture of the region.The methods and cases of work with historical and cultural heritage introduced into scientific circulation in different regions of the world are selected taking into account the current economic, demographic, social processes in small Russian cities, which increases the efficiency of their possible use. …”
Get full text

PAPR optimization based on SLM and PTS algorithms in NC-OFDM systems by Jie ZHOU, Bernardo Esono Esono Mikue, Xueying WANG, Huiting ZHOU, Hong LUO

“…Based on the non-continuous orthogonal frequency division multiplexing (NC-OFDM) model, a fusion optimization technology based on selected mapping (SLM) algorithm and partial transmit sequence (PTS) algorithm was proposed, and a system model of fusion technology was designed.Through simulation comparison with other literature methods, it was verified that the SLM-PTS fusion technology had excellent peak to average power ratio (PAPR) reduction ability, but the algorithm implementation complexity was too high.Therefore, a complementary SLM-Clipping fusion solution was proposed, and the deep learning method PAPRnet model was construted.The simulation results verif that prove the effectiveness of the method, the algorithm has an excellent PAPR suppressed effect on the NC-OFDM system, and greatly improves the computational efficiency.…”
Get full text

PAPR optimization based on SLM and PTS algorithms in NC-OFDM systems by Jie ZHOU, Bernardo Esono Esono Mikue, Xueying WANG, Huiting ZHOU, Hong LUO

“…Based on the non-continuous orthogonal frequency division multiplexing (NC-OFDM) model, a fusion optimization technology based on selected mapping (SLM) algorithm and partial transmit sequence (PTS) algorithm was proposed, and a system model of fusion technology was designed.Through simulation comparison with other literature methods, it was verified that the SLM-PTS fusion technology had excellent peak to average power ratio (PAPR) reduction ability, but the algorithm implementation complexity was too high.Therefore, a complementary SLM-Clipping fusion solution was proposed, and the deep learning method PAPRnet model was construted.The simulation results verif that prove the effectiveness of the method, the algorithm has an excellent PAPR suppressed effect on the NC-OFDM system, and greatly improves the computational efficiency.…”
Get full text

Red-KPLS Feature Reduction with 1D-ResNet50: Deep Learning Approach for Multiclass Alzheimer’s Staging by Syrine Neffati, Ameni Filali, Kawther Mekki, Kais Bouzrara

“…The early detection of Alzheimer’s disease (AD) is essential for improving patient outcomes, enabling timely intervention, and slowing disease progression. However, the complexity of neuroimaging data presents significant obstacles to accurate classification. …”
Get full text

Higher performance enhancement of direct torque control by using Space Vector Modulation for doubly fed induction machine by Gouaamar Radouan, El Fadl Adiba, Bri Seddik, Mekrini Zineb

“…A comprehensive study comparing the performance of these speed control within DTC framework is carried out with a detailed insight to important metrics such as dynamic response, reference tracking, torque ripple content involved and complexity among others. This study discusses the pros and cons of all mentioned methods, which helps in better understanding for optimal speed control selection to improve DFIM performance at different operating conditions. …”
Get full text

An Effective Off-Grid DOA Estimation Algorithm Using Difference Coarrays with Limited Snapshots by Yanan Ma, Jian Wang, Lu Cao, Pengyu Guo, Guangteng Fan

“…Moreover, most existing DOA estimation techniques exhibit a high computational complexity, limiting their practical implementation in real-time systems. …”
Get full text

Exploring the relationship between data sample size and traffic flow prediction accuracy by Jianhu Zheng, Minghua Wang, Mingfang Huang

“…Efficiently extracting and analyzing large urban traffic data, accurately predicting traffic conditions, and improving urban traffic management require careful selection of an appropriate data sample size. …”
Get full text

Comparative analysis of innovative cooling systems for Li-ion cells using carbon-graphene coatings, metal foams, and 3D printing by Luigi Sequino, Bianca Maria Vaglieco

“…However, electric vehicles operate at high working temperatures, so designers must devote considerable effort to developing efficient cooling systems. The complexity of battery-cooling solutions varies with the application: city cars, trucks, and hyper-cars require increasingly sophisticated systems. …”
Get full text