Study on debris flow vulnerability of ensemble learning model based on spy technology A case study of upper Minjiang river basin by Yutao Chen, Ning Li, Fucheng Xing, Han Xiang, Zilong Chen

“…Since it is challenging to predict debris flows with precision using traditional methods, machine learning algorithms have been used more and more in this field in recent years. …”
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Predictive Modeling of Acute Respiratory Distress Syndrome Using Machine Learning: Systematic Review and Meta-Analysis by Jinxi Yang, Siyao Zeng, Shanpeng Cui, Junbo Zheng, Hongliang Wang

“…Early detection and accurate prediction of ARDS can significantly improve patient outcomes. While machine learning (ML) models are increasingly being used for ARDS prediction, there is a lack of consensus on the most effective model or methodology. …”
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Digital Land Suitability Assessment for Irrigated Cultivation of Some Agricultural Crops Using Machine Learning Approaches (Case Study: Qazvin-Abyek) by F. Jannati, F. Sarmadian

“…The utilization of modern mapping techniques such as digital soil mapping and machine learning algorithms can significantly improve the accuracy of land suitability assessment and crop performance prediction. …”
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Artificial intelligence in hospital infection prevention: an integrative review by Rabie Adel El Arab, Zainab Almoosa, May Alkhunaizi, May Alkhunaizi, Fuad H. Abuadas, Joel Somerville, Joel Somerville

“…Further research is needed to evaluate cost-effectiveness, real-world applications, and strategies (e.g., clinician training and the integration of explainable AI) to improve trust and broaden clinical adoption.…”
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Mapping Polyclonal HIV-1 Antibody Responses via Next-Generation Neutralization Fingerprinting. by Nicole A Doria-Rose, Han R Altae-Tran, Ryan S Roark, Stephen D Schmidt, Matthew S Sutton, Mark K Louder, Gwo-Yu Chuang, Robert T Bailer, Valerie Cortez, Rui Kong, Krisha McKee, Sijy O'Dell, Felicia Wang, Salim S Abdool Karim, James M Binley, Mark Connors, Barton F Haynes, Malcolm A Martin, David C Montefiori, Lynn Morris, Julie Overbaugh, Peter D Kwong, John R Mascola, Ivelin S Georgiev

“…Here, we present next-generation NFP algorithms that substantially improve prediction accuracy for individual donors and enable serologic analysis for entire cohorts. …”
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Measurement Techniques for Highly Dynamic and Weak Space Targets Using Event Cameras by Haonan Liu, Ting Sun, Ye Tian, Siyao Wu, Fei Xing, Haijun Wang, Xi Wang, Zongyu Zhang, Kang Yang, Guoteng Ren

“…In the target denoising phase, we fully consider the characteristics of space targets’ motion trajectories and optimize a classical spatiotemporal correlation filter, thereby significantly improving the signal-to-noise ratio for weak targets. …”
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Research and Application of a Health Management Device for the Electrical Control Cabinet of the EMU by Yongshen WU, Jian FENG, Mingshuai ZHANG, Chaoyue JU, Feihong YI

“…The usage of the device can also beneficial to the intelligent maintenance of electrical cabinets and optimize maintenance costs.…”
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Performance Assessment of Undifferenced GPS/Galileo Precise Time Transfer with a Refined Clock Model by Wei Xu, Pengfei Zhang, Lei Wang, Chao Yan, Jian Chen

“…The improvement is most significant for short term frequency stability, with a maximum enhancement exceeding 85%. …”
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Robust EEG Characteristics for Predicting Neurological Recovery from Coma After Cardiac Arrest by Meitong Zhu, Meng Xu, Meng Gao, Rui Yu, Guangyu Bin

“…These findings provide a clinically actionable framework for advancing neurological prognosis and optimizing patient care.…”
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Verification of the method for classifying the technical state of a turboshaft engine fuel regulator in the space of operational process parameters under factory test conditions by Ihor Ohanian, Sergiy Yepifanov

“…Recommendations for further improvement of the method include using expert systems and developing effective model identification algorithms. …”
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Machine Learning Approach to Model Soil Resistivity Using Field Instrumentation Data by Md Jobair Bin Alam, Ashish Gunda, Asif Ahmed

“…Cross-validation and feature selection methods were used to optimize model performance and identify key variables that most significantly impact soil resistivity. …”
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Lightweight security architecture design for wireless sensor network by Chao WANG, Guang-yue HU, Huan-guo ZHANG

“…Most previous security proposal did not consider key management or their authentication efficiency was very low.Lightweight security architecture and lightweight security algorithm were proposed for wireless sensor network,The problem of network encounters malicious nodes maybe occur in the procedure of backbone networks networking could be solved by threshold secret sharing mechanism.The lightweight ECC was proposed to optimize the CPK architecture based on normal ECC,authentication was efficient without the third-party CA,and could reduce the computational complexity,the key management could meet the resource limit in wireless sensor network,and the key security depended on the exponential computation complexity of the elliptic discrete logarithm decomposition.The scheme used the improved two-way authentication to ensure the communication security between common node and sink node,which could prevent man-in-the-middle attack.…”
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Machine learning-based integration develops relapse related signature for predicting prognosis and indicating immune microenvironment infiltration in breast cancer by Junyi Li, Shixin Li, Dongpo Zhang, Yibing Zhu, Yue Wang, Xiaoxiao Xing, Juefei Mo, Yong Zhang, Daixiang Liao, Jun Li

“…To address these limitations, this study systematically analyzed RNA-seq high-throughput data and combined 10 machine learning algorithms to construct 117 models. The optimal algorithm combination, StepCox[both] and ridge regression, was identified, and an immune-related gene signature (IRGS) composed of 12 genes was developed. …”
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Efficient and Motion Correction-Free Myocardial Perfusion Segmentation in Small MRI Data Using Deep Transfer Learning From Cine Images: A Promising Framework for Clinical Implement... by German Garcia-Jara, Angel Jimenez-Molina, Esteban Reyes, Nicolas Tapia-Rivas, Cristobal Ramos-Gomez, Jose De Grazia, Matias Sepulveda

“…This methodology includes normalization and cropping of cine images using a Region-of-Interest detector based on a Markovian, graph-based visual saliency algorithm improved by a sequence of morphological operations. …”
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PP-QADMM: A Dual-Driven Perturbation and Quantized ADMM for Privacy Preserving and Communication-Efficient Federated Learning by Anis Elgabli

“…We provide a rigorous theoretical proof of convergence, showing that PP-QADMM converges to the optimal solution for convex problems while achieving a convergence rate comparable to standard ADMM, but with significantly lower communication and energy costs, and robust privacy protection. …”
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Zonal Estimation of the Earliest Winter Wheat Identification Time in Shandong Province Considering Phenological and Environmental Factors by Jiaqi Chen, Xin Du, Chen Wang, Cheng Cai, Guanru Fang, Ziming Wang, Mengyu Liu, Huanxue Zhang

“…Other zones reached optimal timing between late December and late January, all with OA above 95%. …”
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The application of blockchain with a comparative approach and its impact on risk, flexibility and internal control evaluation by mohammadsadegh aminipoor, HamidReza GholamniaRoshan, azadeh kiapour, Iman Dadashi

“…Overall, blockchain can help improve risk, flexibility and internal control assessment. …”
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The Influence of Viewing Geometry on Hyperspectral-Based Soil Property Retrieval by Yucheng Gao, Lixia Ma, Zhongqi Zhang, Xianzhang Pan, Ziran Yuan, Changkun Wang, Dongsheng Yu

“…The optimal viewing zenith angle ranged from 10° to 20° for SOM and around 40° for PSD. …”
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Ultrasound combined with serological markers for predicting neonatal necrotizing enterocolitis: a machine learning approach by Yi Yang, Shoulan Zhou, Xiaomin Liu, Yanhong Zhang, Liping Lin, Chenhan Zheng, Xiaohong Zhong

“…SHAP analysis identified bowel peristalsis, C-reactive protein, albumin, bowel thickness, and procalcitonin as the most influential predictors. Decision curve analysis demonstrated a positive relative net benefit of the USPN model compared to the US and serological models in the validation set.ConclusionA machine learning model integrating ultrasound and serological markers significantly improves the prediction of NEC in neonates compared to single-modality approaches. …”
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Research on the Application of Artificial Intelligence in Quantitative Investment: Implementation Scenarios, Practical Challenges, and Future Trends by Chen Boshan

“…Second, the research focuses on key AI applications in quantitative investment, including multi-factor model optimization, high-frequency market risk management, multimodal data integration, and algorithmic trading enhancement. …”
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