Multi-Attribute Data-Driven Flight Departure Delay Prediction for Airport System Using Deep Learning Method by Yujie Yuan, Yantao Wang, Chun Sing Lai

“…The case study shows that the proposed method can significantly improve the accuracy of flight prediction delay. The Mean Absolute Error (MAE) can reach 0.26, which is a 14.47% reduction compared with 2D CNN+GCN+LSTM.…”
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Unsupervised Multimodal UAV Image Registration via Style Transfer and Cascade Network by Xiaoye Bi, Rongkai Qie, Chengyang Tao, Zhaoxiang Zhang, Yuelei Xu

“…This paper proposes a novel multi-scale cascaded registration network based on style transfer that achieves superior performance: up to 67% reduction in mean squared error (from 0.0106 to 0.0068), 9.27% enhancement in normalized cross-correlation, 26% improvement in local normalized cross-correlation, and 8% increase in mutual information compared to state-of-the-art methods. …”
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Optimized bio-signal reconstruction and watermarking via enhanced fractional orthogonal moments by Gaber Hassan, Khalid M. Hosny, Islam S. Fathi

“…The findings indicate that the proposed methodology exhibits significantly higher performance levels than current methodologies, with a 64.3% improvement in PSNR (reaching 147.08 dB compared to 89.74 dB in existing approaches), 89.7% reduction in MSE (0.0092 versus 0.09 average), and 84.1% decrease in bit error rate (0.25 versus 1.57) for watermarking applications. …”
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Model-based hierarchal control framework for frequency and voltage stability in islanded microgrids with low inertia by Girmaw Teshager Bitew, Teketay Mulu Beza, Muhammad Shahzad

“…The main results include frequency deviation below 0.04 Hz (versus 0.12 Hz for droop control), voltage regulation error within ±1.2% (versus ±4.2% for droop control), and a 50% reduction in communication traffic. …”
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A de-embedding method based on combining time and frequency domains by Wenwen Zeng, Yaoli Wang, Zhibin Wang

“…Abstract This paper proposes an automatic fixture removal (AFR) de-embedding method to address the embedding error introduced by the fixture in radio frequency (RF) chip parameter testing and the cumbersome calibration process of the short-open-load-thru de-embedding method. …”
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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

“…The equation was validated with the experimental results giving a maximum error of 8%. A comparative study was conducted using different methodologies of steel design standards and previous researches to evaluate their results with the experiments. …”
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Behavioural alterations induced by chronic exposure to 10 nm silicon dioxide nanoparticles by Bashir Jarrar, Amin Al‐Doaiss, Ali Shati, Mohammed Al‐Kahtani, Qais Jarrar

“…Treated mice demonstrated anxiety‐like effect, depression tendency, behavioural despair stress, exploration and locomotors activity reduction with error induction in both reference and working memories. …”
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An adaptive non-equidistant grey model with four parameters and its applications in deformation monitoring by Shuang Yang, Changchun Li, Jiao Fu, Huanqin Ma

“…Third, the optimal selection of initial value with the minimum relative error sum of squares as the objective function further enhances the model optimization. …”
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A reversible and robust hybrid image steganography framework using radon transform and integer lifting wavelet transform by B. M. El-den, Walid Raslan

“…The system exhibits exceptional robustness, with a Bit Error Rate (BER) as low as 0.0017 under scaling distortions, representing a 30% reduction compared to state-of-the-art methods. …”
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Laor Initialization: A New Weight Initialization Method for the Backpropagation of Deep Learning by Laor Boongasame, Jirapond Muangprathub, Karanrat Thammarak

“…This paper presents Laor Initialization, an innovative weight initialization technique for deep neural networks that utilizes forward-pass error feedback in conjunction with k-means clustering to optimize the initial weights. …”
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Phishing suspiciousness in older and younger adults: The role of executive functioning. by Brandon E Gavett, Rui Zhao, Samantha E John, Cara A Bussell, Jennifer R Roberts, Chuan Yue

“…A logistic regression, which accounted for a 22.7% reduction in error variance compared to the null model and predicted phishing suspiciousness with 73.1% (95% CI [66.0, 80.3]) accuracy, revealed three statistically significant predictors: the main effect of education (b = 0.58, SE = 0.27) and the interactions of age group with prior awareness of phishing (b = 2.31, SE = 1.12) and performance on the Neuropsychological Assessment Battery Mazes test (b = 0.16, SE = 0.07). …”
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A Study of Multi-distributed Resource Equalization Allocation for Virtual Power Plants Based on Genetic-heuristic Algorithm by Haifeng Li, Tao Jin, Xian Xu, Lin Shi

“…Under a comprehensive fluctuation scenario with 30% renewable energy fluctuation rate and 15% load forecasting error, the system stability index remains at 0.865, demonstrating the algorithm’s efficiency and robustness under complex conditions and providing an effective approach for optimizing virtual power plant resource allocation.…”
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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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Effects of digestate solid fraction fertilisation on yield and soil carbon dioxide emission in a horticulture succession by Carmelo Maucieri, Carlo Nicoletto, Caterina Caruso, Paolo Sambo, Maurizio Borin

“…Summer and spring crops did not show significantly different marketable yield among fertilisation treatments with an average value (±standard error) of 9.0±0.5, 9.9±1.2 and 51.3±6.4 Mg ha–1 for green bean, cauliflower and cabbage, respectively. …”
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Numerical analysis and design methodology for steel frames with fuse system by Xiaotong Peng, Zhen Wang, Chen Lin, Deshan Sun, Shengtao Lu, Tingting Wen

“…The proposed method for calculating lateral stiffness and ultimate load capacity shows an accuracy within a 10% margin of error compared to finite element analysis results.…”
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A Case Study on Integrating an AI System into the Fuel Blending Process in a Chemical Refinery by Abdul Gani Abdul Jameel

“…The results showed that the AI-integrated fuel blending system was able to produce fuel recipes with a mean absolute error (MAE) of 1.4 for the AKI. The obtained MAE is close to the experimental uncertainty of 0.5 octane. …”
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Experimental Study on Gas-Solid Heat Transfer Characteristics for the Vertical Waste Heat Recovery Using the Inverse Problem Method by Sizong Zhang, Zhi Wen, Yi Xing, Xunliang Liu, Hui Zhang, Yaxuan Xiong

“…Among them, the minimum value of the mean relative error is 26.81%. It is proved that the previous empirical correlations are no longer applicable, while the predicted value of this work is in good agreement with the measured value with the mean deviation of only 7.61%. …”
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NSEA: A Resilient ERP Framework Integrating Quantum-Safe Cryptography and Neuro-Symbolic Reasoning for Industrial Adaptability by Yong Lin, Yadi Lin

“…In demand forecasting tasks, the hybrid reasoning model reduced mean absolute percentage error (MAPE) to 6.8% and resolved 89% of inventory stockout alerts within 15 minutes. …”
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Inversion model of stress state reconstruction for geological hazard pipelines based on digital twin by Xue Luning, Tian Mingliang, Zhao Juncheng

“…The calculation time was 5.62 s, which was an average reduction of 18.95%. Under the three geological disasters of earthquakes, mudslides, and landslides, the root mean square error of the model’s predictions was below 3 GPa, and the accuracy remained above 94%. …”
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Combined compression and encryption of linear wireless sensor network data using autoencoders by N. Shylashree, Sachin Kumar, Hong Min

“…The proposed lossy compression has a mean square reconstruction error of less than 0.5 for compression ratios in the range of 5 to 10. …”
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