Influence maximization under imbalanced heterogeneous networks via lightweight reinforcement learning with prior knowledge by Kehong You, Sanyang Liu, Yiguang Bai

“…It is significant that the reduction of number of seed set selections T not only keeps the quality of solutions, but lowers the algorithm’s computational cost.…”
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A graph-based sensor recommendation model in semantic sensor network by Yuanyi Chen, Yihao Lin, Peng Yu, Yanyun Tao, Zengwei Zheng

“…We use the improved fast non-dominated sorting algorithm to obtain the local optimal solutions of sensor data set, and we apply the simple additive weight algorithm to characterize and sort local optional solutions. …”
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Adjustment of angle error and tolerance allocation methods for RV reducers by ZHANG Bowen, ZHOU Jianxing, CUI Quanwei, LIN Kaihong, ZHOU Yadong, XU Wenqiang

“…Finally, with the minimum total processing cost as the objective function, the angular tolerance allocation of key components was completed by using the genetic algorithm.ResultsThe research results prove the effectiveness of this method in improving the transmission accuracy and stability of RV reducers, but different accuracy weight values should be selected according to actual accuracy requirements to minimize costs.…”
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Deep learning-based identification of patients at increased risk of cancer using routine laboratory markers by Vivek Singh, Shikha Chaganti, Matthias Siebert, Sowmya Rajesh, Andrei Puiu, Raj Gopalan, Jamie Gramz, Dorin Comaniciu, Ali Kamen

“…Abstract Early screening for cancer has proven to improve the survival rate and spare patients from intensive and costly treatments due to late diagnosis. …”
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AGW-YOLO-Based UAV Remote Sensing Approach for Monitoring Levee Cracks by HU Weibo, ZHOU Shaoliang, ZHAO Erfeng, ZHAO Xueqiang

“…Comparative experiments indicated that AGW-YOLO outperformed several mainstream object detection algorithms, including Faster R-CNN, YOLOv8n, YOLOv9-tiny, YOLOv10n, RT-DETR-R50, and TPH-YOLO, across most evaluation metrics, offering high recognition accuracy with lower computational complexity. …”
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Research on Hyperspectral Inversion of Soil Organic Carbon in Agricultural Fields of the Southern Shaanxi Mountain Area by Yunhao Han, Bin Wang, Jingyi Yang, Fang Yin, Linsen He

“…The results indicate that (1) the Spectral Space Transformation (SST) algorithm effectively eliminates environmental interference on image spectra, enhancing SOC prediction accuracy; (2) continuous wavelet transform significantly reduces data noise compared to other spectral processing methods, further improving SOC prediction accuracy; and (3) among feature band selection methods, the CARS algorithm demonstrated the best performance, achieving the highest SOC prediction accuracy when combined with the random forest model. …”
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P-Band PolInSAR Sub-Canopy Terrain Retrieval in Tropical Forests Using Forest Height-to-Unpenetrated Depth Mapping by Chuanjun Wu, Jiali Hou, Peng Shen, Sai Wang, Gang Chen, Lu Zhang

“…A nonlinear iterative optimization algorithm is then employed to estimate forest height, from which a fundamental mapping between forest height and unpenetrated depth is established. …”
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Guaranteed efficient energy estimation of quantum many-body Hamiltonians using ShadowGrouping by Alexander Gresch, Martin Kliesch

“…They are helpful for identifying measurement settings that improve the energy estimate the most. This task constitutes an NP-hard problem. …”
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Global air quality index prediction using integrated spatial observation data and geographics machine learning by Tania Septi Anggraini, Hitoshi Irie, Anjar Dimara Sakti, Ketut Wikantika

“…The GML considers geographical characteristics in the analysis by calculating the optimal bandwidth area in its algorithm. The study employs nine scenarios to identify which parameters significantly contribute to the model and determine the best parameter combinations. …”
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Data mining methods application in reflexive adaptation realization in e-learning systems by A. S. Bozhday, Y. I. Evseeva, A. A. Gudkov

“…Finding such regularities and their subsequent analysis will make it possible to reorganize the structure of the system in a more optimal way and without human intervention, which will prolong the life cycle of the software and reduce the costs of its maintenance. …”
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Modular-based psychotherapy (MoBa) versus cognitive–behavioural therapy (CBT) for patients with depression, comorbidities and a history of childhood maltreatment: study protocol fo... by Elisabeth Schramm, Martin Hautzinger, Carolin Jenkner, Moritz Elsaesser, Sabine Herpertz, Hannah Piosczyk

“…By optimally tailoring module selection and application to the specific needs of each patient, MoBa has great potential to improve the currently unsatisfying results of psychotherapy as a bridge between disorder-specific and personalised approaches.Methods and analysis In a randomised controlled feasibility trial, N=70 outpatients with episodic or persistent major depression, comorbidity and childhood maltreatment are treated in 20 individual sessions with MoBa or standard cognitive–behavioural therapy for depression. …”
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Utilization of Neural Network in the Diagnosis of Pes Planus and Pes Cavus with a Smartphone Camera by Samir Ghandour MD, Anton Lebedev BS, Wei Shao Tung BS, Konstantin Semianov BS, Artem Semyanov MS, Daniel Guss MD, MBA, Gregory R. Waryasz MD, John Y. Kwon MD, Christopher W. DiGiovanni MD, Soheil Ashkani-Esfahani MD, Lorena Bejarano-Pineda MD

“…While effective, traditional diagnostic methods pose limitations such as cost, radiation exposure, and accessibility, particularly in underserved areas. …”
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Optimasi Algoritma Naive Bayes dengan Diskritisasi K-Means pada Diagnosis Penyakit Jantung by Nafa Fajriati, Budi Prasetiyo

“…This shows that K-means discretization plays a role in optimizing the performance of the Naïve Bayes algorithm to produce better accuracy. …”
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Frequency Regulation Provided by Doubly Fed Induction Generator Based Variable-Speed Wind Turbines Using Inertial Emulation and Droop Control in Hybrid Wind–Diesel Power Systems by Muhammad Asad, José Ángel Sánchez-Fernández

“…Wind energy (WE) is the most adopted renewable energy source due to its technical readiness, competitive cost, and environmentally friendly characteristics. …”
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Radio Map Reconstruction With Adaptive Spatial Feature Learning by Jie Yang, Wenbin Guo

“…In this paper, we first explore the spatial features of signals on the radio map and formulate the reconstruction problem as an optimization problem with feature penalties. Then, we propose an iteration algorithm with spatial feature learning to reconstruct signals on the radio map, which improves the reconstruction accuracy by using an adaptive feature dictionary. …”
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Sequential Hybrid Beamforming for Radio Stripes by Joumana JOUMANA, Daniel Castanheira, Adao Silva, Rui Dinis, Atilio Gameiro

“…In this regard, radio stripe (RS) is a promising and cost-efficient approach to deal with these issues, improving system efficiency and scalability. …”
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Loop-mediated isothermal amplification assays for the detection of antimicrobial resistance elements in Vibrio cholera by Daniel Antonio Negrón, Shipra Trivedi, Nicholas Tolli, David Ashford, Gabrielle Melton, Stephanie Guertin, Katharine Jennings, Bryan D. Necciai, Shanmuga Sozhamannan, Bradley W. Abramson

“…Methods We developed an algorithm for the in silico design and evaluation of LAMP assays within the open-source PCR Signature Erosion Tool (PSET) and a computer vision application for the quantitative analysis of colorimetric outputs. …”
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Reliable Event Detection via Multiple Edge Computing on Streaming Traffic Social Data by Yipeng Ji, Jingyi Wang, Yan Niu, Hongyuan Ma

“…Then, we utilize graph neural networks to perform semi-supervised learning on HIN to obtain the optimal meta-path weights. We also develop Binary Sample Graph Convolutional Neural Network (BS-GCN) and Binary Sample Graph Attention Network (BS-GAT) to improve the reliability of graph neural network models based on the characteristics of traffic event detection and design an incremental clustering algorithm based on event similarity to implement streaming social traffic event detection. …”
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AI Applications for Chronic Condition Self-Management: Scoping Review by Misun Hwang, Yaguang Zheng, Youmin Cho, Yun Jiang

“…Conversational AI (21/66, 32%) and multiple machine learning algorithms (16/66, 24%) were the most used AI technologies. …”
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Leveraging petrophysical and geological constraints for AI-driven predictions of total organic carbon (TOC) and hardness in unconventional reservoir prospects by Nandito Davy, Ammar El-Husseiny, Umair bin Waheed, Korhan Ayranci, Manzar Fawad, Mohamed Mahmoud, Nicholas B. Harris

“…Our optimized models achieved R2 (coefficient of determination) of 0.89 and RMSE (root-mean-square error) of 0.47 for TOC predictions and 0.90 and 34.8 for hardness predictions, reducing RMSE by up to 13.52% compared to the unconstrained model. …”
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