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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Multifrequency Subsurface Soil Moisture Retrieval for Forest Flows: A Case Study in Te Hiku, New Zealand by Yu-Huan Zhao, Delwyn Moller, Dean Meason, Mahta Moghaddam

“…In addition, comparing multifrequency and single P-band retrievals indicated a reduction in RMSE with the multifrequency approach, particularly noted during the Te Hiku dry season.…”
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Characteristics Analysis of Joint Acoustic Echo and Noise Suppression in Periodic Drillstring Waveguide by Li Cheng, Chang Jinfeng, Liu Zhao, Fan Shangchun, Ding Tianhuai

“…The results reveal that the proposed scheme can achieve a much lower error bit ratio over a specified acoustic isolation frequency range with a 30–40 dB reduction in the average noise level compared to traditional single-receiver scheme.…”
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Structural Response Evaluation of Krylov Subspace-Based Reduced-Order Model for Real-Time Structural Health Monitoring and Prediction of Container Ships by Kichan Sim, Byoung Wan Kim, Jeong Sam Han, Kangsu Lee

“…Thus, Krylov subspace-based model-order reduction is a valuable tool for predicting the structural responses of ships and offshore structures under real-time irregular waves. …”
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An Improved Orthogonal Frequency Division Multiplexing System-Based Image Steganography Technique by Ali Y. Jaber, Ammar Al-Khafaji, Ahmed Mahfodh Mkhelf

“…Moreover, the transmitted signal will be of high quality due to the ICI reduction, leading to channel normalization and reducing the receiving complexity. …”
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Ionospheric Time Series Prediction Method Based on Spatio-Temporal Graph Neural Network by Yifei Chen, Yang Liu, Kunlin Yang, Lanhao Li, Chao Xiong, Jinling Wang

“…For 2015, the experimental results show a 21.9% RMSE reduction at low latitudes compared to the results of the iTransformer model. …”
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3-D Moving Target Localization in Multistatic HFSWR: Efficient Algorithm and Performance Analysis by Xun Zhang, Jun Geng, Yunlong Wang, Yijia Guo

“…In this paper, we develop a two-stage localization algorithm that first derives a weighted least-squares (WLS) coarse estimate and then performs an algebraic error reduction (ER) procedure to enhance accuracy. …”
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Rapid Correction of Turbidity Interference on Chemical Oxygen Demand Measurements by Using Ultraviolet-Visible Spectrometry by Shihan Shan, Yihuan Ji, Hanjing Deng, Zhuohui Wu, Tinglong Yang, Xiaoping Wang

“…In our experiment, this method effectively eliminated the blue shift and peak height reduction caused by turbidity, especially in shorter wavelengths, which are more sensitive to interference. …”
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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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Research on 3D Building Individualization Technology Based on Spatial Constraints by Z. Liu, L. Huo, T. Shen, F. Kong

“…Experimental results show that the proposed method achieves an IoU of 91.5% in commercial dense areas (a 21.3% improvement over traditional methods), reduces directional error to 3.2° (a 74% decrease), increases recall rate in occlusion scenes to 89.4%, and processes a single scene in only 218 seconds (a 32% reduction). …”
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Catalyzing Supply Chain Evolution: A Comprehensive Examination of Artificial Intelligence Integration in Supply Chain Management by Sarthak Pattnaik, Natasya Liew, Ali Ozcan Kures, Eugene Pinsky, Kathleen Park

“…AI has become pivotal in tackling various Supply-Chain Management challenges, notably enhancing demand forecasting precision and automating warehouse operations for improved efficiency and error reduction. However, a critical debate arises concerning the choice between less accurate explainable models and more accurate yet unexplainable models in Supply-Chain Management applications. …”
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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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Wind speed prediction for trains on bridges using enhanced variational mode decomposition assisted feature extraction and physical auxiliary mechanism by Zhilan Zhu, Yuan Jiang, Haicui Wang, Shuoyu Liu

“…For example, the proposed method can realize the reduction of the average of mean absolute error from 1.08 to 0.73 in comparison with ARIMA-FCN-PAM. …”
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Accurate Location Method for Abnormal Line Losses in Distribution Network Considering Topology Matching and Parameter Estimation in Grid by Haiyun An, Qian Zhou, Qiuwei Wu, Yufang Liu, Cheng Huang, Jiaxun Li

“…The weighting coefficient is selected to minimize the solution error. Finally, by comparing the deviation between the estimated values of the branch parameters and the theoretical values, the aging degree of each branch is evaluated, and branches with abnormal line losses are accurately located. …”
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ADULT-ONSET STILL’S DISEASE: ASPECTS OF THE HEMATOLOGY CLINIC by M. M. Agakishiev, I. I. Mulina, A. M. Popova, I. N. Nechunaeva, L. M. Maslova, I. B. Kovynev, T. I. Pospelova

“…It is important for a hematologist not to miss a blood tumor and to prevent a diagnostic error. The authors showed the criteria for exclusion of myeloblastic hematosarcoma and malignant lymphoma in a patient with Still’s disease. …”
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Load frequency control resilience of hybrid power system with renewable energy sources and superconducting magnetic energy storage using FO-Fuzzy-PID controller by Misagh Jalilian, Abdollah Rastgou, Saeed Kharrati, Saman Hosseini-Hemati

“…In other Scenario, it achieved the lowest integral of time-weighted absolute error (ITAE) value of 0.0061, representing a 44.5% improvement over the PSO-PID controller's ITAE of 0.11. …”
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A novel graph modeling method for GNN-based hypersonic aircraft flow field reconstruction by Qiao Li, Xingchen Li, Xiaoqian Chen, Wen Yao

“…Furthermore, our approach has been validated in the reconstruction of hypersonic aircraft flow fields for at least 10% error reduction among all the situations.…”
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Hybrid optimization of thermally-enhanced Zn-Fe LDH catalysts for fenton-like reactions: Integrating design of experiments with machine learning models for optimisation by Ramadhan Muhammad Naufal, Nawwal Hikmah, Dessy Ariyanti

“…Among the models, GBR achieved the highest predictive accuracy (R² = 0.998, MAPE =,0.9 %, RMSE = 0.964), outperforming RSM by over 97 % in prediction error reduction. The improvement of prediction fidelity by introducing the use of ML models into the RSM framework resulted in precise optimization across complex, multi-dimensional surfaces. …”
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Numerical approach and experimental investigation of a stratified hot water storage tank for domestic hot water production by M. Reda Haddouche, F.J.S. Velasco, F. Illán, J.R. García Cascales

“…The present model provides a reduction of about 5 % of the error of the time of the water cooling process with respect to other models in the literature.…”
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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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