AI-Powered Precision in Diagnosing Tomato Leaf Diseases by MD Jiabul Hoque, Md. Saiful Islam, Md. Khaliluzzaman

“…Correct detection of plant diseases is critical for enhancing crop yield and quality. Conventional methods, such as visual inspection and microscopic analysis, are typically labor-intensive, subjective, and vulnerable to human error, making them infeasible for extensive monitoring. …”
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Smart Agile Prioritization and Clustering: An AI-Driven Approach for Requirements Prioritization by Aya M. Radwan, Manal A. Abdel-Fattah, Wael Mohamed

“…Traditional prioritization methods often suffer from scalability limitations, lack of automation, and difficulty in handling dependencies. …”
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Spatial prediction based on Third Law of Geography by A‐Xing Zhu, Guonian Lu, Jing Liu, Cheng‐Zhi Qin, Chenghu Zhou

“…The prediction uncertainty associated with spatial prediction based on the Third Law of Geography is more indicative to quality of the prediction, thus more effective in allocating error reduction efforts. These properties make spatial prediction based on the Third Law of Geography more suitable for prediction over large and complex geographic areas.…”
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Mean-Field-Type Transformers by Hamidou Tembine, Manzoor Ahmed Khan, Issa Bamia

“…For instance, the variance reduction in error within generative machine intelligence is a mean-field-type problem and does not involve an infinite number of decision-makers. …”
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Damage Identification in Large-Scale Structures Using Time Series Analysis and Improved Sparse Regularization by Huihui Chen, Xiaojing Yuan

“…Furthermore, regarding the numerical example, the damage identification results show that the max identification errors of the proposed method are 6% among the three cases under noise-free and noise-polluted data, while the max identification errors for MFO and the regularization method are 15% and 10%, respectively. …”
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Enhanced Lightweight Quantum Key Distribution Protocol for Improved Efficiency and Security by Ashutosh Bhatia, Sainath Bitragunta, Kamlesh Tiwari

“…However, the classical post-processing steps in BB84, such as sifting, error correction, and key verification, often result in significant communication overhead, limiting its efficiency and scalability. …”
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Computational fluid dynamics and machine learning integration for evaluating solar thermal collector efficiency -Based parameter analysis by Xiaoyu Hu, Lanting Guo, Jiyuan Wang, Yang Liu

“…The study identifies a critical transition at 100–300 samples where error rates drop sharply, with optimal performance requiring more than 600 samples. …”
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Patient Safety in Medication Nomenclature: Orthographic and Semantic Properties of International Nonproprietary Names. by Rachel Bryan, Jeffrey K Aronson, Pius ten Hacken, Alison Williams, Sue Jordan

“…<h4>Background</h4>Confusion between look-alike and sound-alike (LASA) medication names (such as mercaptamine and mercaptopurine) accounts for up to one in four medication errors, threatening patient safety. Error reduction strategies include computerized physician order entry interventions, and 'Tall Man' lettering. …”
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Experimentally investigating the structural capacity of slender web tapered built up plate girder with web opening by Mohammed Taher, Ahmed M. Ebid, Sherif M. Ibrahim, Mohamed A. El-Aghoury

“…However, while design codes provide well-established methods for prismatic girders, the web behavior of tapered girders with web openings remains insufficiently investigated, leading to gaps in existing predictive models. …”
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Impact of worklist selection on point-of-care ultrasound workflow – a quality improvement project by Jonathan Rowland, Jessa Baker, Natassia Dunn, Matthew Whited, Soheil Saadat, J. Christian Fox

“…Implementation also resulted in a 36% reduction in database studies containing an MRN data entry error. …”
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An improved small object detection CTB-YOLO model for early detection of tip-burn and powdery mildew symptoms in coriander (Coriandrum sativum) for indoor environment using an edge... by Parwit Chutichaimaytar, Zhang Zongqi, Kriengkri Kaewtrakulpong, Tofael Ahamed

“…Early and accurate detection of these symptoms is critical for maintaining yield and quality, yet traditional visual inspection methods are subjective and prone to error. To address this, we developed an enhanced deep learning model, Coriander Tip-Burn YOLO (CTB-YOLO), specifically tailored for detecting small-object symptoms in coriander leaves, emphasizing the reduction of false-positive detections (FP), which could lead to erroneous alerts and unnecessary interventions. …”
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A systematic review of using clinical decision support systems in corneal diseases by Farzad Ebrahimi, Haleh Ayatollahi, Kimia Zeraatkar

“…Conclusion The use of clinical decision support systems in corneal diseases leads to improve timely diagnosis, error reduction, and user satisfaction. However, further research is recommended to expand the use of new technologies such as artificial intelligence in the diagnosis of corneal diseases.…”
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Analysis and Prediction of the Factors Influencing Postconstruction Surface Deformation of Pipe-Jacking Tunnel in Soft Clay Strata in China by Guo-jing Cui, Jiang-sheng Xie, Yin-hao Sun, Yong-ji Gao

“…The error between the formula and the measured data was 9.05%, which can be used as a reference for controlling design parameters to predict the settlement after construction of pipe-jacking engineering.…”
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Prediction Model of Household Carbon Emission in Old Residential Areas in Drought and Cold Regions Based on Gene Expression Programming by Shiao Chen, Yaohui Gao, Zhaonian Dai, Wen Ren

“…By combining data dimensionality reduction with adaptive evolutionary algorithms, this model overcomes the limitations of traditional methods in capturing complex nonlinear relationships. …”
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A Simple and Effective KAN-Based Architecture for Accurate Battery RUL Prediction by Guangzai Ye, Li Feng, Jianlan Guo, Yuqiang Chen, Shufei Li

“…Experimental results on two public battery datasets show that DCI-KANs substantially outperform existing state-of-the-art methods in RUL prediction accuracy, achieving a 43 % and 22 % reduction in Absolute Relative Error (ARE) on the NASA and CALCE datasets, respectively. …”
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Retinal and choroidal morphological changes in Huntington's disease by S. N. Svetozarskiy, S. V. Kopishinskaya, I. G. Smetankin

“…The groups had matching age, sex distribution, intraocular pressure and mean refractive error. In the study group, 21 patients had pre-manifest and 23, manifest HD stage. …”
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Research on the longitudinal end effect in eddy-current braking characteristic experiment by WANG Lichao, WANG Ke, WANG Lining, GAO Liqun

“…By correcting the braking force experimental data using a trailing pole contribution function, a notable reduction in the relative error between the correction results and the braking force derived from 3-D finite element simulations is observed. …”
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DRFW-TQC: Reinforcement Learning for Robotic Strawberry Picking with Dynamic Regularization and Feature Weighting by Anping Zheng, Zirui Fang, Zixuan Li, Hao Dong, Ke Li

“…The proposed approach achieves a 16.0% higher picking success rate and a 20.3% reduction in angular error with four target strawberries. …”
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Refraction changes in children with retinopathy of prematurity after transpupillary laser coagulation of the retina by A. V. Myagkov, P. V. Rozental

“…Regardless of the refractive error type, the axial length of the eye remained significantly below the age norm. …”
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Design and Application of an Energy Management System Based on Artificial Intelligence Technology by Hongye Lin, Xuanying Bai, Chun Li, Shenghan Xu, Haibin Xu, Zne-Jung Lee, Yun Lin, Qunshan Zhou, Jingxun Cai

“…In response to the increasingly severe energy consumption problem and to promote energy saving and emission reduction, this study aims to design and apply an energy management system platform based on artificial intelligence (AI) technology. …”
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