Machine learning approaches for predicting the link of the global trade network of liquefied natural gas. by Pei Zhao, Hao Song, Guang Ling

“…This study demonstrates that machine learning algorithms-specifically random forest and decision tree-outperform in predicting links within the global LNG trade network based on local information proximity, while the graph attention network, a deep learning model, exhibits stable optimization and effective feature learning. …”
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Unmanned aerial vehicle image stitching based on multi‐region segmentation by Weidong Pan, Anhu Li, Xingsheng Liu, Zhaojun Deng

“…Most existing image stitching methods based on optimal seamline searching algorithms can eliminate defects such as ghosting and distortion in stitched images, which unfortunately suffer from the problem that the seamline may cross those regions with significant geometric misalignment between different images. …”
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Dynamic Evacuation Shelter Allocation in Response to Human Mobility: A Case Study of Taipei City by Chang-Hung Shih, Cheng-Yun Wu, Shu-Ping Tseng, Yi-Lin Huang, Rong-Pu Jhuang, Yi-Chung Chen, Tien-Yi Yang, Wei-Ting Chen

“…Weighted Voronoi diagrams delineated regions to identify optimal evacuation points, while real-time SMS notifications through base station positioning disseminated evacuation information to the public. …”
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Monitoring Canopy Height in the Hainan Tropical Rainforest Using Machine Learning and Multi-Modal Data Fusion by Qingping Ling, Yingtan Chen, Zhongke Feng, Huiqing Pei, Cai Wang, Zhaode Yin, Zixuan Qiu

“…The results showed that RH80 was the optimal choice for the prediction model regarding percentile selection, and the RF algorithm exhibited the optimal performance in terms of accuracy and stability, with R² values of 0.71 and 0.60 for the training and testing sets, respectively, and a relative root mean square error of 21.36%. …”
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Cooperative control method for multi-agent ground fracturing truck group based on offline reinforcement learning by RuYi Wang, HuiShen Jiao, YingCheng Tian, Yi Zhao, SiQi Wang, Ke Zhang, Bo Huang, QinRui Sun, DanDan Zhu

“…The core of this method is an improved algorithm based on the TD3, which is enhanced by the incorporation of the CQL algorithm to improve the stability of the collaborative control strategy. …”
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Disjunctive and conjunctive decompositions of incompletely defined Boolean functions in a Binary Decision Diagram by P. N. Bibilo

“…The application of the proposed algorithms and already known algorithms for minimizing multilevel BDD representations of partial function systems allows us to obtain the best results of technologically independent logical optimization, the initial stage of logic circuit synthesis.…”
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Transmitting Double-D Coil to Wirelessly Recharge the Battery of a Drone with a Receiving Coil Integrated in the Landing Gear by Wassim Boumerdassi, Tommaso Campi, Silvano Cruciani, Francesca Maradei, Mauro Feliziani

“…To this aim, a double-D configuration is here proposed and optimized for the transmitting coil, while a double coil receiver in combination with a charge controller that uses a maximum power point tracking (MPPT) algorithm is integrated into the landing gear. …”
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Quantitative structure-properties relationship, molecular dynamic simulations and designs of some novel lubricant additives by Usman Abdulfatai, Adamu Uzairu, Sani Uba, Gideon Adamu Shallangwa

“…Quantitative structure-properties relationship (QSPR) method was used to design some novel antioxidant lubricant additives, while molecular dynamics simulations were used to calculate their dynamic binding energies on steel and to hydrogen-containing DLC (a-C: H) crystal surfaces. 29 synthesized antioxidant lubricant additives were collected from literature and geometrically optimized by Spartan’14 version 1.1.2 software while Genetic Function Algorithm (GFA) method of the material studio version 8.0 software was used to build the predictive QSPR model. …”
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RSWD-YOLO: A Walnut Detection Method Based on UAV Remote Sensing Images by Yansong Wang, Xuanxi Yang, Haoyu Wang, Huihua Wang, Zaiqing Chen, Lijun Yun

“…Through model deployment and testing on small edge devices, we demonstrate the feasibility of our proposed method. The detection algorithm achieves 86.1% mean Average Precision on the walnut dataset while maintaining operational functionality on small edge devices. …”
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Intelligent deep learning for human activity recognition in individuals with disabilities using sensor based IoT and edge cloud continuum by Mohammed Maray

“…For feature subset selection, the enhanced honey badger algorithm (EHBA) model is used to effectively reduce dimensionality while retaining critical activity-related features. …”
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Ship-DETR: A Transformer-Based Model for EfficientShip Detection in Complex Maritime Environments by Yi Wang, Xiang Li

“…To address these issues, we propose an effective ship detection algorithm—Ship Detection Transformer (Ship-DETR). …”
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Emerging generalization advantage of quantum-inspired machine learning in the diagnosis of hepatocellular carcinoma by Domenico Pomarico, Alfonso Monaco, Nicola Amoroso, Loredana Bellantuono, Antonio Lacalamita, Marianna La Rocca, Tommaso Maggipinto, Ester Pantaleo, Sabina Tangaro, Sebastiano Stramaglia, Roberto Bellotti

“…The variational optimization of PQCs achieves better accuracy than classical counterparts on the independent test set, reaching an advantage equal to $$11\%$$ 11 % in accuracy, while tensor networks offer equivalent performance with fewer parameters.…”
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Anomaly Detection in Network Traffic Using Advanced Machine Learning Techniques by Stephanie Ness, Vishwanath Eswarakrishnan, Harish Sridharan, Varun Shinde, Naga Venkata Prasad Janapareddy, Vineet Dhanawat

“…By comparing different algorithms, this research contributes to advancing the application of machine learning in network security, offering guidance on model selection and optimization for improved detection of cyber threats.…”
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Multi-label classification for image tamper detection based on Swin-T segmentation network in the spatial domain by Li Li, Kejia Zhang, Jianfeng Lu, Shanqing Zhang

“…Our method introduces three key innovations: (1) A spatial perception module that combines the spatial rich model (SRM) with constrained convolution, enabling focused detection of tampering traces while suppressing interference from image content; (2) A hierarchical feature learning architecture that integrates Swin Transformer with UperNet for effective multi-scale tampering pattern recognition; and (3) A comprehensive optimization strategy including auxiliary supervision, self-supervised learning, and hard example mining, which significantly improves model convergence and detection accuracy. …”
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Benchmarking Big Data Systems: Performance and Decision-Making Implications in Emerging Technologies by Leonidas Theodorakopoulos, Aristeidis Karras, Alexandra Theodoropoulou, Georgios Kampiotis

“…GraphX’s strength was in processing batch in-memory workloads typical of blockchain and machine learning model optimization, while Flink excelled in processing stream data, which is timely and important to the IoT world. …”
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Artificial intelligence in the food industry: innovations and applications by Hang Yang, Wenxuan Jiao, Lingyun Zouyi, Hongli Diao, Shibin Xia

“…This review assesses the current state and future prospects of AI applications in key areas such as food traceability, safety, quality control, supply chain optimization, and intelligent packaging solutions. AI technologies, including machine learning (ML) algorithms and computer vision systems, are widely used to optimize supply chains, predict demand, reduce waste, and enhance food safety and quality monitoring. …”
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Prediction of Temperature Distribution on an Aircraft Hot-Air Anti-Icing Surface by ROM and Neural Networks by Ziying Chu, Ji Geng, Qian Yang, Xian Yi, Wei Dong

“…The proposed models not only provide faster predictions of anti-icing surface temperature distributions than traditional numerical simulation methods but also ensure acceptable accuracy, which supports the design of aircraft hot-air anti-icing systems based on optimization methods such as genetic algorithms.…”
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YOLO-MES: An Effective Lightweight Underwater Garbage Detection Scheme for Marine Ecosystems by Chengxu Huang, Wenyuan Zhang, Beitian Zheng, Jiahao Li, Bochen Xie, Ruisi Nan, Zongming Tan, Baohua Tan, Neal N. Xiong

“…To address this issue, this paper introduces YOLO-MES, an innovative underwater debris detection algorithm that integrates a lightweight design and a feature enhancement mechanism to enable efficient model deployment while preserving high accuracy. …”
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Hybrid neural network method for damage localization in structural health monitoring by Fatahlla Moreh, Yusuf Hasan, Zarghaam Haider Rizvi, Sven Tomforde, Frank Wuttke

“…Many existing methods for crack detection rely on deep learning algorithms or traditional approaches that typically use image data. …”
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Architectural Gaps in Generative AI: Quantifying Cognitive Risks for Safety Applications by He Wen, Pingfan Hu

“…<b>Conclusions</b>: These findings suggest that such distances represent not only algorithmic abstraction but also potential safety risks when generative AI is deployed in practice. …”
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