OpenPheno: an open-access, user-friendly, and smartphone-based software platform for instant plant phenotyping by Tianqi Hu, Peng Shen, Yongshuai Zhang, Jiafei Zhang, Xin Li, Chuanzhen Xia, Ping Liu, Hao Lu, Tingting Wu, Zhiguo Han

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The 3D tooth model segmentation method based on GAC+PointMLP network by Jianjun Chen, Liyuan Zheng, Huilai Zou, Jiafa Mao, Weiguo Sheng

“…Compared to other traditional segmentation algorithms, the proposed method shows improvements of 1.1, 2.04, 1.06, 2.2, and 1.8 percentage points in Overall Accuracy (OA), Sensitivity (SEN), Positive Predictive Value (PPV), and Intersection Over Union (IoU), respectively. …”
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Transmission Line Connection Fittings and Corrosion Detection Method Based on PCSA-YOLOv7 Former by Zhiwei SONG, Xinbo HUANG, Chao JI, Fan ZHANG, Ye ZHANG

“…The experimental results show that the proposed method is superior to 12 existing state-of-the-art object detection algorithms in comprehensive detection performance of the constructed TLCF dataset, with the mAP0.5 of the test set reaching 94.9 %. …”
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Micro-stories, Robotic Coding, Digital Applications, and Augmented Reality to Enhance Children's Computational Thinking [Microrrelatos, codificación robótica, aplicaciones digitale... by M. Esther Del-Moral-Pérez, Nerea López Bouzas, Jonathan Castañeda-Fernández

“…Students with Special Educational Needs and Disabilities (SEND) also showed an improvement in their CT skills, albeit with greater challenges. …”
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A Hybrid Evolutionary Fuzzy Ensemble Approach for Accurate Software Defect Prediction by Raghunath Dey, Jayashree Piri, Biswaranjan Acharya, Pragyan Paramita Das, Vassilis C. Gerogiannis, Andreas Kanavos

“…The results show that the proposed method improves classification performance by 1% to 13% while retaining only 33% to 57% of the original feature set, offering a reliable and interpretable solution for software defect prediction. …”
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Distributed Authentication of Power Grid Safety and Stability Control Terminals Based on DHT and Blockchain by Yening LAI, Ke FENG, Tongwei YU, Wang WANG, Guanjun TANG

“…The proposed scheme improves the communication safety between terminals of the power grid safety and stability control system without affecting the communication efficiency, thus ensuring the safe and stable operation of power grid.…”
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On the Extrapolation of Generative Adversarial Networks for Downscaling Precipitation Extremes in Warmer Climates by Neelesh Rampal, Peter B. Gibson, Steven Sherwood, Gab Abramowitz

“…Abstract While deep‐learning downscaling algorithms can generate fine‐scale climate projections cost‐effectively, it is unclear how effectively they extrapolate to unobserved climates. …”
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Investigating Internet of Things and Artificial Intelligence-Based Approaches to Smart Irrigation System Optimisation for Agricultural Water Resource Management by Balassem Zaid Ajzan, Alkhafaij Mahdi Abdulkhudur, Raju Nadimpalli Venkata Ganapathi

“…Our findings demonstrate that the AWRM-AI system significantly improves water-use efficiency, leading to better crop yields and a reduction in water wastage. …”
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Deep-learning based detection of vessel occlusions on CT-angiography in patients with suspected acute ischemic stroke by Gianluca Brugnara, Michael Baumgartner, Edwin David Scholze, Katerina Deike-Hofmann, Klaus Kades, Jonas Scherer, Stefan Denner, Hagen Meredig, Aditya Rastogi, Mustafa Ahmed Mahmutoglu, Christian Ulfert, Ulf Neuberger, Silvia Schönenberger, Kai Schlamp, Zeynep Bendella, Thomas Pinetz, Carsten Schmeel, Wolfgang Wick, Peter A. Ringleb, Ralf Floca, Markus Möhlenbruch, Alexander Radbruch, Martin Bendszus, Klaus Maier-Hein, Philipp Vollmuth

“…Benchmarking against two CE- and FDA-approved software solutions showed significantly higher performance for our ANN with improvements of 25–45% for sensitivity and 4–11% for NPV (p ≤ 0.003 each). …”
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Ensemble Machine Learning Model Prediction and Metaheuristic Optimisation of Oil Spills Using Organic Absorbents: Supporting Sustainable Maritime by Le Quang Dung, Pham Duc, Bui Thi Anh Em, Nguyen Lan Huong, Nguyen Phuoc Quy Phong, Dang Thanh Nam

“…To close this gap, our work combines metaheuristic algorithms with ensemble machine learning and suggests a hybrid technique for the precise prediction and improvement of oil removal efficiency. …”
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Stochastic Parameter Identification Method for Driving Trajectory Simulation Processes Based on Mobile Edge Computing and Self-Organizing Feature Mapping by Jingfeng Yang, Zhiyong Luo, Nanfeng Zhang, Jinchao Xiao, Honggang Wang, Shengpei Zhou, Xiaosong Liu, Ming Li

“…The proposed methods can provide significant practical information for improving the data processing efficiency in automated driving applications, for solving single-vehicle lane-change applications, and for promoting the formation of a closed loop from sensing to service.…”
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Hybrid Tunnel Entrance Detection via Multiple Morphological Component-Based Texture Enhancement by Heng Huang, Jia Chen, Tao Chen, Jun Li, Antonio Plaza

“…Finally, a voting strategy is employed for postprocessing, aimed at improving the efficacy of tunnel entrance detection. …”
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Knowledge graph-based intelligent control systems for real-time machine tool optimization by Hailong YANG, Jun YAO, Baorui DU

“…In addition, for further details, the data is classified into different groups by using clustering algorithms resulting in corresponding decision-making outcomes. …”
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An Analysis of the Design and Kinematic Characteristics of an Octopedic Land–Air Bionic Robot by Jianwei Zhao, Jiaping Gao, Mingsong Bao, Hao Zhai, Xu Pei, Zheng Jiang

“…The effectiveness of the design and control strategy is verified through the construction of an experimental platform and field tests, significantly improving the robot’s adaptability and mobility in complex terrain. …”
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Analyzing Public Transport Wait Times and Identifying the Most Affected Users in the Metropolitan Area of Valparaíso, Chile by Felipe González, Vicente Aprigliano, Sebastian Seriani, Alvaro Peña

“…This study provides insights for improving transportation planning by identifying patterns and user groups that experience extended wait times, which can guide decisions to enhance user satisfaction and promote the use of public transportation.…”
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Realistic in silico generation and augmentation of single-cell RNA-seq data using generative adversarial networks by Matteo Marouf, Pierre Machart, Vikas Bansal, Christoph Kilian, Daniel S. Magruder, Christian F. Krebs, Stefan Bonn

“…Augmenting sparse cell populations with cscGAN generated cells improves downstream analyses such as the detection of marker genes, the robustness and reliability of classifiers, the assessment of novel analysis algorithms, and might reduce the number of animal experiments and costs in consequence. cscGAN outperforms existing methods for single-cell RNA-seq data generation in quality and hold great promise for the realistic generation and augmentation of other biomedical data types.…”
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Coding for Young Learners: Enhancing Computational Thinking and Creativity in Elementary Education by Hilmiyah, Abd Muhith, Syamsul Bahri

“…Findings revealed increased computational thinking scores from 56.3 to 74.8 after Scratch-based coding lessons. Significant improvements were observed in decomposition, pattern recognition, and algorithmic thinking, although abstraction remained challenging. …”
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Machine learning model for predicting in-hospital cardiac mortality among atrial fibrillation patients by Huasheng Lv, Xuehua Bi, Shuai Shang, Meng Wei, Xianhui Zhou, Kai Wang, Baopeng Tang, Yanmei Lu

“…This interpretable model holds promise for improving early risk stratification and individualized care in AF patients. …”
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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

“…The experimental findings demonstrate that the proposed model enhances the IoU index by 13% compared to the leading algorithms. Additionally, it can accurately detect multiple tampering types from a single image.…”
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Machine Learning-Based Analysis of Travel Mode Preferences: Neural and Boosting Model Comparison Using Stated Preference Data from Thailand’s Emerging High-Speed Rail Network by Chinnakrit Banyong, Natthaporn Hantanong, Supanida Nanthawong, Chamroeun Se, Panuwat Wisutwattanasak, Thanapong Champahom, Vatanavongs Ratanavaraha, Sajjakaj Jomnonkwao

“…Practical implications include optimizing fare structures, enhancing service quality, and improving station accessibility to support sustainable adoption.…”
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