GeoAT: Geometry-Aware Attention Feature Matching Network by Yan Li, Yingdan Wu, Yang Ming, Yong Zhang, Zhesheng Cheng

“…We evaluated GeoAT on two well-known datasets, HPatches and MegaDepth, where it outperformed the current state-of-the-art algorithm, LoFTR, with improvements of 3-5% across various metrics. …”
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Energy Efficient Design for Two-Way AF Relay Networks by Yong Li, Zhengguang Zheng, Mingyue Zhao, Yunli Chen, Chuanyong Liu

“…In this paper, we consider a system where two source nodes communicate with each other via an amplify-and-forward (AF) relay node and study the power allocation schemes to maximize EE while ensuring a certain data rate. We propose an optimal energy-efficient power allocation algorithm based on iterative search technique. …”
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Development and validation of a quick screening tool for predicting neck pain patients benefiting from spinal manipulation: a machine learning study by Changxiao Han, Guangyi Yang, Haibao Wen, Minrui Fu, Bochen Peng, Bo Xu, Xunlu Yin, Ping Wang, Liguo Zhu, Minshan Feng

“…Results The combined LASSO and Boruta algorithms identified nine optimal predictors, with the union feature set achieving superior performance. …”
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Exploration and Construction of Personalized Customization Mode in Modern Fashion Design by Sun Huaiqun

“…By analyzing the advantages of this model in meeting personalized consumer needs, improving production efficiency, and promoting green design and sustainable development, this article further proposes specific suggestions for technology optimization, process simplification, and user experience improvement. …”
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Enhanced deep learning model for apple detection, localization, and counting in complex orchards for robotic arm-based harvesting by Tantan Jin, Xiongzhe Han, Pingan Wang, Zhao Zhang, Jie Guo, Fan Ding

“…This study presents an enhanced deep learning model designed to improve the accuracy and adaptability of recognition algorithms for robotic arm-based harvesting. …”
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Artificial intelligence (AI) in restorative dentistry: current trends and future prospects by Mariya Najeeb, Shahid Islam

“…Conclusion The review discussed trends, challenges, and future research directions in AI-driven dentistry, highlighting the transformative potential of AI in optimizing dental care. Key challenges include data privacy concerns, algorithmic bias, interpretability of AI decision-making processes, and the need for standardized AI training programs in dental education. …”
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AI-Driven Robotics: Innovations in Design, Perception, and Decision-Making by Lei Li, Li Li, Mantian Li, Ke Liang

“…Artificial intelligence (AI), driven by large datasets and advanced algorithms, plays a pivotal role in addressing these challenges and advancing robotics. …”
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Adaptive sequential estimator for InSAR time series phase estimation by Guanya Wang, Zhiwei Li, Han Gao, Jun Hu, Mi Jiang, Peng Ren, Jie Zhang

“…Based on these, the ASE method adaptively prioritizes coherent information while minimizing the impact of decorrelation noise, thereby improving phase estimation accuracy. …”
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Machine Learning Based Flexible Transmission Time Interval Scheduling for eMBB and uRLLC Coexistence Scenario by Jingxuan Zhang, Xiaodong Xu, Kangjie Zhang, Bufang Zhang, Xiaofeng Tao, Ping Zhang

“…Compared with the existing ML methods, the proposed algorithm has a performance improvement in selecting TTI, especially for the uRLLC services. …”
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Impact of summer heat and mitigation strategies on apple (Cosmic Crisp®) fruit color dynamics quantified using crop physiology sensing system by Basavaraj R. Amogi, Lav R. Khot, Bernardita V. Sallato

“…CPSS with integrated RGB imaging data were contrasted with ambient air temperature (Tair) within each treatment using a custom developed algorithm. The algorithm allowed automated and daily quantification of fruit color metrics, including hue angle (h°), color transition from green to red (a∗), and chroma. …”
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Proactive Data Placement in Heterogeneous Storage Systems via Predictive Multi-Objective Reinforcement Learning by Suchuan Xing, Yihan Wang

“…Through comprehensive evaluation using both synthetic and real-world traces from deep learning training workloads, our method demonstrates substantial improvements over state-of-the-art algorithms: achieving up to 45.1% reduction in average I/O latency, 32.5% improvement in throughput for critical applications, and 28.8% reduction in storage costs. …”
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An End-to-End Solution for Large-Scale Multi-UAV Mission Path Planning by Jiazhan Gao, Liruizhi Jia, Minchi Kuang, Heng Shi, Jihong Zhu

“…Additionally, we integrate a Multi-Start Greedy Rollout Baseline to evaluate diverse trajectories via parallelized greedy searches, thereby reducing policy gradient variance and improving training stability. Experiments demonstrated significant improvements in scalability, particularly in 100-node scenarios, where our method drastically reduced inference time compared to conventional methods, while maintaining a competitive path cost efficiency. …”
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Predicting antimicrobial mechanism-of-action from transcriptomes: A generalizable explainable artificial intelligence approach. by Josh L Espinoza, Chris L Dupont, Aubrie O'Rourke, Sinem Beyhan, Pavel Morales, Amy Spoering, Kirsten J Meyer, Agnes P Chan, Yongwook Choi, William C Nierman, Kim Lewis, Karen E Nelson

“…Here we describe an explainable artificial intelligence classification methodology that emphasizes prediction performance and human interpretability by using a Hierarchical Ensemble of Classifiers model optimized with a novel feature selection algorithm called Clairvoyance; collectively referred to as a CoHEC model. …”
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Prioritising explainable AI-driven recommendations with knowledge graphs and reinforcement learning by Neeraj Tiwary, Shahrul Azman Mohd Noah, Fariza Fauzi

“…By applying optimisation techniques that consider rewards, probabilities, information values, and affinity scores while minimising traversal hops within KG paths, XAIRec learns user preferences from historical data, determines optimal reasoning paths, and enhances recommendation quality by prioritising products with higher relevance. …”
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Spatiotemporal Analysis of Eco-Geological Environment Using the RAGA-PP Model in Zigui County, China by Xueling Wu, Jiaxin Lu, Chaojie Lv, Liuting Qin, Rongrui Liu, Yanjuan Zheng

“…It utilized the Analytic Hierarchy Process (AHP), coefficient of variation (CV), and the Real-Coded Accelerating Genetic Algorithm-Projection Pursuit (RAGA-PP) model for evaluation, the latter of which optimizes the projection direction and utilizes PP to transform high-dimensional data into a low-dimensional space, thereby obtaining the values of the projection indices. …”
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Monolayer graphene/platinum-modified 3D origami microfluidic paper-based biosensor for smartphone-assisted biomarkers detection by Arda Fridua Putra, Annisa Septyana Ningrum, Suyanto Suyanto, Vania Mitha Pratiwi, Muhammad Yusuf Hakim Widianto, Irkham Irkham, Wulan Tri Wahyuni, Isnaini Rahmawati, Fu-Ming Wang, Chi-Hsien Huang, Ruri Agung Wahyuono

“…Conclusion: The 3D origami structure facilitates efficient fluid handling and multiplex detection, while the nanocatalyst modification improves pore infiltration and sensitivity. …”
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Intelligent Energy Management in an Isolated DC Microgrid using Fuzzy Logic by Youssfi Abdelaziz, El Kadi Youssef Ait

“…The PV system is controlled by a MPPT method implementing the INC algorithm, while the storage system is managed by a PI controller to control battery charging and discharging. …”
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Construction and application of a drought classification model for tea plantations based on multi-source remote sensing by Yang Xu, Yilin Mao, He Li, Xiaojiang Li, Litao Sun, Kai Fan, Zhipeng Li, Shuting Gong, Zhaotang Ding, Yu Wang

“…To address this gap, we propose RSDCM (Remote Sensing-based Drought Classification Model), an improved Genetic Algorithm-Backpropagation (GA-BP) combined with MS + TIR framework that optimizes initial weights and thresholds via GA's global search (hidden layer=1, neurons in the hidden layers=5, 50 generations, population size=5, NonUnifMutation operators) to escape local minima and accelerate convergence. …”
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DeepLabV3+-Based Semantic Annotation Refinement for SLAM in Indoor Environments by Shuangfeng Wei, Hongrui Tang, Changchang Liu, Tong Yang, Xiaohang Zhou, Sisi Zlatanova, Junlin Fan, Liping Tu, Yaqin Mao

“…Experimental results demonstrate that our approach achieves significant improvements in annotation efficiency while preserving high accuracy, thereby providing reliable technical support for enhanced environmental understanding and navigation capabilities in indoor robotic applications.…”
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Development of an Intelligent System for Processing Semistructured Data: Industry Structuring and Advanced Analysis of Information Extracted from Comments to Video Clips in Social... by A. A. Poguda, H. Tape

“…The development of an intelligent system for processing semistructured data has improved the analysis of comments on videos in social networks through a combination of various machine learning models and algorithms. …”
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