Dual-Path Large Kernel Learning and Its Applications in Single-Image Super-Resolution by Zhen Su, Mang Sun, He Jiang, Xiang Ma, Rui Zhang, Chen Lv, Qiqi Kou, Deqiang Cheng

“…To enhance the performance of super-resolution models, neural networks frequently employ module stacking. …”
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Development of GUI-Driven AI Deep Learning Platform for Predicting Warpage Behavior of Fan-Out Wafer-Level Packaging by Ching-Feng Yu, Jr-Wei Peng, Chih-Cheng Hsiao, Chin-Hung Wang, Wei-Chung Lo

“…Traditional electronic engineers often face difficulties in implementing AI-driven models due to the specialized programming and algorithmic expertise required. …”
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Artificial Intelligence in Primary Malignant Bone Tumor Imaging: A Narrative Review by Platon S. Papageorgiou, Rafail Christodoulou, Panagiotis Korfiatis, Dimitra P. Papagelopoulos, Olympia Papakonstantinou, Nancy Pham, Amanda Woodward, Panayiotis J. Papagelopoulos

“…Innovative segmentation techniques and multimodal imaging models have further enhanced healthcare efficiency by reducing physician workload and improving diagnostic accuracy. …”
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Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

“…We enhance the model’s diagnostic capability through complex image preprocessing techniques, such as improved noise reduction and morphological approaches. …”
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Deep Learning in Defect Detection of Wind Turbine Blades: A Review by Katleho Masita, Ali N. Hasan, Thokozani Shongwe, Hasan Abu Hilal

“…The increasing adoption of wind turbines as a key component of renewable energy generation necessitates the development of efficient and reliable maintenance strategies to ensure their optimal performance and safety. Among the most critical aspects of turbine maintenance is detecting and classifying defects in wind turbine blades, which are constantly exposed to extreme environmental conditions. …”
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YouTube and Bilibili as sources of information on oral cancer: cross-sectional content analysis study by Qilei zhang, Zhe Li, Huiping Zhang, Ling Han, Shugang Zhao, Siyu Jia

“…In conclusion, YouTube videos exhibited higher audience engagement and video quality, yet improvements are needed on both platforms. In order to promote high-quality health information, it is essential to encourage the development of more professional content creators and to optimize platform algorithms.…”
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The Relationship Between Stiff Knee Gait Runner’s Dystonia and Musculoskeletal Knee Pathology: A Case Series by Jared A. Stowers, Derek S. Day, Steven Jow, Sarah Heins, Euan Forrest, Yonathan M. Assefa, Paige M. Lind, Afreen Mushtaheed, Frances T. Sheehan, Katharine E. Alter

“…Addressing both issues is essential for optimizing treatment outcomes, reducing pain, and improving function, especially since pain can trigger dystonia. …”
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Label semantics and image features aware remote sensing sample retrieval from multi-source datasets for AI-enabled remote sensing monitoring by XingTao Ren, XingTao Ren, Yan Ma, YiXin Zhou, YiXin Zhou

“…Future work may focus on further optimizing the retrieval algorithms and expanding the range of supported data platforms to enhance the robustness and scalability of the system.…”
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LimeSoDa: A dataset collection for benchmarking of machine learning regressors in digital soil mapping by Jonas Schmidinger, Sebastian Vogel, Viacheslav Barkov, Anh-Duy Pham, Robin Gebbers, Hamed Tavakoli, Jose Correa, Tiago R. Tavares, Patrick Filippi, Edward J. Jones, Vojtech Lukas, Eric Boenecke, Joerg Ruehlmann, Ingmar Schroeter, Eckart Kramer, Stefan Paetzold, Masakazu Kodaira, Alexandre M.J.-C. Wadoux, Luca Bragazza, Konrad Metzger, Jingyi Huang, Domingos S.M. Valente, Jose L. Safanelli, Eduardo L. Bottega, Ricardo S.D. Dalmolin, Csilla Farkas, Alexander Steiger, Taciara Z. Horst, Leonardo Ramirez-Lopez, Thomas Scholten, Felix Stumpf, Pablo Rosso, Marcelo M. Costa, Rodrigo S. Zandonadi, Johanna Wetterlind, Martin Atzmueller

“…All datasets were aligned to a tabular format and are ready-to-use for modeling. We demonstrated the use of LimeSoDa for benchmarking by comparing the predictive performance of four learning algorithms across all datasets. …”
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A semantic segmentation-based automatic pterygium assessment and grading system by Qingbo Ji, Qingbo Ji, Wanyang Liu, Wanyang Liu, Qingfeng Ma, Qingfeng Ma, Lijun Qu, Lin Zhang, Hui He

“…This study aims to develop an automated grading system combining deep learning and image processing techniques for precise pterygium evaluation.MethodsThe proposed system integrates two modules: 1) A semantic segmentation module utilizing an improved TransUnet architecture for pixel-level pterygium localization, trained on annotated slit-lamp microscope images from clinical datasets. 2) A severity assessment module employing enhanced curve fitting algorithms to quantify pterygium invasion depth in critical ocular regions. …”
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Deciphering microbial and metabolic influences in gastrointestinal diseases-unveiling their roles in gastric cancer, colorectal cancer, and inflammatory bowel disease by Daryll Philip, Rebecca Hodgkiss, Swarnima Kollampallath Radhakrishnan, Akshat Sinha, Animesh Acharjee

“…These models were then employed for cross-disease analysis, revealing that models trained on GC data successfully predicted IBD biomarkers, while CRC models predicted GC biomarkers with optimal performance scores. …”
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Role of Roadside Units in Cluster Head Election and Coverage Maximization for Vehicle Emergency Services by Ravneet Kaur, Robin Doss, Lei Pan, Chaitanya Singla, Selvarajah Thuseethan

“…The proposed scheme mandates selecting an optimal number of cluster heads to maximize information coverage and prevent traffic congestion, thereby enhancing the quality of service through improved cluster head duration, reduced cluster formation time, expanded coverage area, and decreased overhead. …”
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Post-Quantum Cryptography Resilience in Telehealth Using Quantum Key Distribution by Don Roosan, Rubayat Khan, Saif Nirzhor, Fahmida Hai

“…Methods A multi-layered design approach was adopted. PQC algorithms (e.g., CRYSTALS-Dilithium) were integrated at the blockchain consensus layer to resist quantum attacks. …”
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The potential & limitations of monoplotting in cross-view geo-localization conditions by Bradley J. Koskowich, Michael J. Starek, Scott A. King

“…Monoplotting only requires three inputs, which are a target terrestrial camera image, a nadir-oriented image, and an underlying digital surface model. 2D-3D point correspondences are derived from the inputs to optimize for the target terrestrial camera pose. …”
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Intelligent collaborative management and control platform for continuous mining equipment in open-pit mines by Zhiyong LEI, Xiaolong MA, Shujun ZHAO, Shiming ZHANG, Bin YAN

“…The platform integrates advanced technologies, including dual-ring network transmission, network security protocols, multi-machine cooperative control, digital twin modeling, and big data analytics, facilitating effective coordination among coal miners, transfer machines, unloaders, and conveyors for seamless continuous mining operations.Three critical technical challenges are addressed: ① The implementation of dual-ring network transmission technology reduces data transmission latency and enhances network stability. ② A secure network transmission framework has been developed to safeguard data confidentiality and integrity. ③ The multi-machine cooperative control system incorporates data acquisition, process control, and 3D visualization modules, employing real-time monitoring and optimized control algorithms to boost mining and transportation efficiency while ensuring the continuity of multi-machine operations. …”
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CPFD Simulation of Operation Characteristics of a 10t/d Sludge and Biomass Co-incineration Fluidized Bed Reactor by REN Shaohui, YU Qiao, LIN Li, XIANG Jiatao, MA Lun, ZHANG Shihong

“…ObjectiveThis research aims to comprehensively investigate the operational dynamics of a 10t/d sludge and biomass co-incineration fluidized bed reactor through Computational Particle Fluid Dynamics (CPFD) modeling, addressing critical gaps in industrial-scale waste valorization. …”
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The Emergence of AI-Driven Virtual Hospitals: Redefining Patient Care Beyond Physical Boundaries by Ifrah Hameed, Hafiz Muhammad Haseeb Khaliq

“…For example, AI-based support systems offer data-driven insights that improve diagnostic accuracy and patient outcomes thus transforming healthcare delivery 3. …”
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Enhancing Crop Type Mapping in Data-Scarce Regions Through Transfer Learning: A Case Study of the Hexi Corridor by Jingjing Mai, Qisheng Feng, Shuai Fu, Ruijing Wang, Shuhui Zhang, Ruoqi Zhang, Tiangang Liang

“…As target domain data were gradually incorporated, the total accuracy for all models ranged from 0.77 to 0.92, with F1-scores ranging from 0.76 to 0.92, showing a consistent improvement in model performance. …”
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CTAB modified SnO₂ PEDOT PSS heterojunction humidity sensor with enhanced sensitivity stability and machine learning evaluation by Poundoss Chellamuthu, Kirubaveni Savarimuthu, M Gulam Nabi Alsath, R. Krishnamoorthy, Yuvaraj T, Feras Alnaimat, Mohammad Shabaz

“…Furthermore, to validate real-time application feasibility, machine learning (ML) algorithms were implemented to model and predict sensor behavior. …”
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TELEPROM Psoriasis: Enhancing patient-centered care and health-related quality of life (HRQoL) in moderate-to-severe plaque psoriasis by Gabriel Mercadal-Orfila, Gabriel Mercadal-Orfila, Piedad López Sánchez, Aranzazu Pou Alonso, Olatz Ibarra-Barrueta, Emilio Monte-Boquet, Joaquin Borrás Blasco, Nuria Padullés Zamora, Patricia Sanmartin-Fenollera, Cristina Capilla Montes, M. Ángeles Bernabéu Martínez, Salvador Herrera-Pérez

“…Regression analysis explained only 13.2% of the variance in PROMs scores, identifying Employment Status and BMI Range as key contributors.ConclusionThis study demonstrates the efficacy of biologic treatments in significantly improving HRQoL for psoriasis patients. Addressing demographic variables, such as gender, is key for optimizing treatment outcomes and improving ePROMs response rates. …”
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