Maintenance techniques to increase solar energy production: A review by Fernando Martinez-Gil, Christopher Sansom, Aránzazu Fernández-García, Alfredo Alcayde-García, Francisco Manzano-Agugliaro

“…This review explores advanced maintenance techniques aimed at improving solar energy production efficiency. The study analyzes the rapid growth of solar energy and the challenges posed by environmental factors such as soiling, harsh climate conditions and hotspots, which reduce photovoltaic (PV) and concentrated solar power (CSP) system performance. …”
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Dataset for identifying paracentral acute middle maculopathy lesions in spectral-domain optical coherence tomography imagesMendeley Data by Tianqiao Zhang, Mengjiao Zhang, Dexun Zhang, Wenjing Meng, Zhenzhen Li, Zhengwei Zhang

“…Furthermore, it supports the improvement of diagnostic accuracy and the development of targeted therapeutic interventions for retinal diseases. …”
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GaussianMix: Rethinking Receptive Field for Efficient Data Augmentation by A. F. M. Shahab Uddin, Maryam Qamar, Jueun Mun, Yuje Lee, Sung-Ho Bae

“…GaussianMix achieves top-1 error rates of 21.26% and 20.09% on ResNet-50 and ResNet-101 for ImageNet classification, respectively, while also improving robustness against adversarial perturbations and enhancing object detection performance.…”
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Understanding lithium-ion battery management systems in electric vehicles: Environmental and health impacts, comparative study, and future trends: A review by R. Suganya, L.M.I. Leo Joseph, Sreedhar Kollem

“…By exploring these aspects, the review provides valuable information on improving BMS efficiency and battery technologies, supporting the future growth of cleaner and more sustainable electric transportation.…”
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Data-Efficient Reinforcement Learning Framework for Autonomous Flight Based on Real-World Flight Data by Uicheon Lee, Seonah Lee, Kyonghoon Kim

“…We compared the proposed framework against existing algorithms in actual quadcopter control. In the comparative experiment, we demonstrated an improvement of up to 70.59% in learning speed, clearly highlighting the impact of the environmental model. …”
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Deep Reinforcement Learning-Based Deployment Method for Emergency Communication Network by Bo Huang, Yiwei Lu, Hao Ma, Changsheng Yin, Ruopeng Yang, Yongqi Shi, Yu Tao, Yongqi Wen, Yihao Zhong

“…Experimental results demonstrate that the proposed method effectively accomplishes the planning tasks of emergency communication hub elements, significantly improving deployment efficiency while maintaining robustness in complex environments.…”
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An Innovative Priority-Aware Mission Planning Framework for an Agile Earth Observation Satellite by Guangtong Zhu, Zixuan Zheng, Chenhao Ouyang, Yufei Guo, Pengyu Sun

“…The proposed approach effectively maintains satellite maneuver constraints while achieving significant improvements in priority-based target acquisition and computational efficiency. …”
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Methods to achieve near-millisecond energy relaxation and dephasing times for a superconducting transmon qubit by Mikko Tuokkola, Yoshiki Sunada, Heidi Kivijärvi, Jonatan Albanese, Leif Grönberg, Jukka-Pekka Kaikkonen, Visa Vesterinen, Joonas Govenius, Mikko Möttönen

“…However, executing quantum algorithms of practical computational advantage requires further improvements in the fidelities of qubit operations, which are currently limited by the energy relaxation and dephasing times of the qubits. …”
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A probabilistic gap based condition prediction approach for desulfurization slurry circulating pump by Jiaxing Zhu, Buyun Sheng, Junlan Hu, Yanfei Li, Ruiping Luo, Yue Shi

“…Results show the proposed method meets ISO 10816-3 standards and improves accuracy over other methods that don’t account for biased datasets, effectively addressing the state prediction issue for primary WFGD equipment.…”
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Enhancing healthcare AI stability with edge computing and machine learning for extubation prediction by Kuo-Yang Huang, Ying-Lin Hsu, Che-Liang Chung, Huang-Chi Chen, Ming-Hwarng Horng, Ching-Hsiung Lin, Ching-Sen Liu, Jia-Lang Xu

“…Notably, the edge-based architecture reduced server data transmissions by 83.33%, while improving system stability, resilience, and sustainability. …”
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MoCoUTRL: a momentum contrastive framework for unsupervised text representation learning by Ao Zou, Wenning Hao, Dawei Jin, Gang Chen, Feiyan Sun

“…This paper presents MoCoUTRL: a Momentum Contrastive Framework for Unsupervised Text Representation Learning. This model improves two aspects of recently popular contrastive learning algorithms in natural language processing (NLP). …”
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A CFD Study of the Hydrodynamic Characteristics of an Autonomous Underwater Helicopter by Hoang-Phuong Vu, Thanh-Long Le, Tran-Hanh Phung, Thanh-Truong Nguyen, Thi-Hong-Nhi Vuong, Tran-Phu Nguyen

“…It has great potential for improving the AUH’s control algorithms.…”
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SIMSPIRE: A Simulator of the Respiratory System by Andrea Bombarda, Silvia Bonfanti, Angelo Gargantini, Elvinia Riccobene

“…It provides a highly accurate and customizable platform for improving the design of ventilation systems and optimizing patient outcomes. …”
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From Rough Mereology to Robust Navigation: Expanding Mobile Robot Strategies with Diverse Maps and Enhanced Goal–Targeting Mechanisms by Szpakowska Aleksandra, Artiemjew Piotr, Cybowski Wojciech

“…To this end, we are preparing and testing our own library for controlling mobile robots, improving the real-time path planning capability and implementing a set of algorithms for practical testing.…”
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Advancing Stability in Robot Manipulators: A Review of Recent Progress and Parameters by Shabnom Mustary, Mohammod Abul Kashem, Jannatul Mawya Sony, Nayem Hossain, Mohammad Asaduzzaman Chowdhury

“…Uses of Lyapunov and Passivity‐Based Control for key stability improvements incorporate robust solutions to nonlinear dynamics and uncertainties. …”
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KT-Deblur: Kolmogorov–Arnold and Transformer Networks for Remote Sensing Image Deblurring by Baoyu Zhu, Zekun Li, Qunbo Lv, Zheng Tan, Kai Zhang

“…Supported by the Fast Spatial Feature Module (FSFM), it effectively improves the model’s ability to handle complex blur patterns. …”
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Sparse Linear Discriminant Analysis With Constant Between-Class Distance for Feature Selection by Shuangle Guo, Yongxia Li, Jianguang Zhang, Yue Liu, Tian Tian, Mengchen Guo

“…The experimental results show that the proposed method has better performance compared to the baseline and six state-of-the-art relative methods, with improvements of over 1% on image datasets and over 2% on video datasets in most cases, while also demonstrating high stability, proving its effectiveness and advantage in practical applications.…”
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MapReduce based big data framework using associative Kruskal poly Kernel classifier for diabetic disease prediction by R. Ramani, S. Edwin Raja, D. Dhinakaran, S. Jagan, G. Prabaharan

“…The proposed AKW-MRPK framework achieves up to 92 % accuracy, reduces computational time to as low as 0.875 ms for 25 patients, and demonstrates superior speedup efficiency with a value of 1.9 ms using two computational nodes, consistently outperforming supervised machine learning algorithms and Hadoop-based clusters across these critical metrics. • The AKW-MRPK method selects attributes and accelerates computations for predictions. • Parallelizing polynomial kernels improves accuracy and speed in healthcare data analysis.…”
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Application of artificial intelligence in modern healthcare for diagnosis of autism spectrum disorder by Abdullah H. Al-Nefaie, Abdullah H. Al-Nefaie, Theyazn H. H. Aldhyani, Theyazn H. H. Aldhyani, Sultan Ahmad, Eidah M. Alzahrani

“…Due to the unique behavioral patterns shown by children with ASD, facial expression analysis has become an effective method for the early identification of ASD.MethodsHence, utilizing deep learning (DL) methodologies presents an excellent opportunity for improving diagnostic precision and efficacy. This study examines the effectiveness of DL algorithms in differentiating persons with ASD from those without, using a comprehensive dataset that includes images of children and ASD-related diagnostic categories. …”
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A systematic review of machine learning and deep learning approaches in plant species detection by Deepti Barhate, Sunil Pathak, Bhupesh Kumar Singh, Amit Jain, Ashutosh Kumar Dubey

“…The review and analysis indicated that there is scope for improvement in the case of multi-feature fusion, such as concatenation of shape, size, margin, texture, venation contour, etc. …”
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