Power System State Estimation through Optimal PMU Placement and Neural Network using Whale Algorithm by SeyedHamed MirMohammadAli Roudaki, Mehrdad Abedi, Iraj Pourkeivani

“…Finally, the minimum estimation error will be shown for IEEE 14 and 30 buses benchmark.…”
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Spectroscopic Quantification of Metallic Element Concentrations in Liquid-Propellant Rocket Exhaust Plumes by Siyang Tan, Song Yan, Xiang Li, Tong Su, Qingchun Lei, Wei Fan

“…Results show that the quantification error of metallic elements remains within 6%, and the method exhibits robust performance under conditions of spectral self-absorption, demonstrating its reliability for rocket engine health monitoring applications.…”
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A Strong Noise Reduction Network for Seismic Records by Tong Shen, Xuan Jiang, Wenzheng Rong, Lei Xu, Xianguo Tuo, Guili Peng

“…These results show that the proposed model significantly outperforms the comparative methods in terms of the SNR, correlation coefficient (r), and root mean square error (RMSE), delivering higher-quality seismograms. …”
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Efficient and Real-Time Compression Schemes of Multi-Dimensional Data from Ocean Buoys Using Golomb-Rice Coding by Quan Liu, Ziling Huang, Kun Chen, Jianmin Xiao

“…The energy supply of ocean monitoring buoys is a major challenge, especially for long-term, low-power applications. Data compression can reduce transmission energy and extend system lifespan. …”
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Feedforward–Feedback Fuzzy-PID Water Level Control using PLC and Node-RED IoT by Adhitya Sumardi Sunarya, Fitria Suryatini, Nuryanti Nuryanti, Abdur Rohman Harist M, Gailan Anaisabury

“…The results indicate that the combined control achieved a lower average steady-state error (0.67%) compared to feedback-only control (1.12%), faster recovery time (3 seconds vs. 6.3 seconds), and no overshoot. …”
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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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Estimation of 3D Ground Reaction Force and 2D Center of Pressure Using Deep Learning and Load Cells Across Various Gait Conditions by Junggil Kim, Ki-Cheon Kim, Gyerae Tack, Jin-Seung Choi

“…In slope conditions, particularly for vertical GRF, relatively higher root mean-square error (RMSE) values were observed. Despite some variation across gait types, predicted values showed high agreement with measurements. …”
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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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Learning Graph Structures With Autoregressive Graph Signal Models by Kyle Donoghue, Ashkan Ashrafi

“…Furthermore, GL-AR’s performance is optimized by a new automated parameter selection algorithm, which eliminates the need for computationally intensive trial-and-error methods.…”
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Innamark: A Whitespace Replacement Information-Hiding Method by Malte Hellmeier, Hendrik Norkowski, Ernst-Christoph Schrewe, Haydar Qarawlus, Falk Howar

“…Furthermore, we propose a specified structure for secret messages that enables configurable compression, encryption, hashing, and error correction. An experimental benchmark comparison on a dataset of 1 000 000 Wikipedia articles compares ten algorithms. …”
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Exact Formula for RX-Differential Probability Through Modular Addition for All Rotations by Alex Biryukov, Baptiste Lambin, Aleksei Udovenko

“…The formula comes with a rigorous proof and is also verified by extensive experiments. Our formula uncovers error in a recent work from 2022 proposing a formula for rotation amounts bigger than 1. …”
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RMDS: Ranging and multidimensional scaling–based anchor-free localization in large-scale wireless sensor networks with coverage holes by Qiyue Li, Baoyu Chu, Zhong Wu, Wei Sun, Liangfeng Chen, Jie Li, Zhi Liu

“…We use ranging and non-line-of-sight error mitigation techniques to estimate accurate distances between each node pair and attempt to find inflection nodes using a novel flooding protocol to correct transmission paths that have become deviated by a coverage hole. …”
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A Practical Short-Circuit Current Calculation Method for Renewable Energy Plants Based on Single-Machine Multiplication by Jianhua Li, Jianyu Lu, Po Li, Ying Huang, Guoteng Wang

“…The error in calculating SCC does not exceed 3.02%. Compared with the single-machine multiplication method, the accuracy is significantly improved, while the accuracy is roughly equivalent to that of the iterative method.…”
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Development of a machine learning-based surrogate model for friction prediction in textured journal bearings by Yujun Wang, Georg Jacobs, Shuo Zhang, Benjamin Klinghart, Florian König

“…Eventually, the average prediction accuracy is improved to 98.81% from 95.89%, with the maximum error reduced to 3.25% from 13.17%. These findings demonstrate the potential of ML in the performance prediction in textured journal bearings and provide a promising approach for broader applications in developing highly efficient and accurate ML-based surrogate models, particularly in cases with limited available training data sets.…”
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Light Energy Driven Nanocommunications With FRET in Photosynthetic Systems by Aleksandra Orzechowska, Joanna Fiedor, Pawel Kulakowski

“…Treating carotenoid molecules as transmitters, chlorophylls as receivers, and the energy transfer between them as a way to encode information, a throughput up to 1 Gbit/s is achievable with a bit error rate below 10^−3, average transmission delays about 20 ps, and energy consumption c.a. …”
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Rate of penetration prediction in drilling operations: a comparative study of AI models and meta-heuristic approaches by Fatemeh Mohammadinia, Ali Ranjbar, Fatemeh Ghazi, Seyyed Taha Hosseini

“…Among the tested models, the LSSVM-CSA framework achieved the best results, with a remarkable R-squared (R2) value of 92.55, a Root Mean Square Error (RMSE) of 2.98. These results underscore the superior accuracy, robustness, and adaptability of the proposed methodology. …”
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A method for phenotyping lettuce volume and structure from 3D images by Victor Bloch, Alexey Shapiguzov, Titta Kotilainen, Matti Pastell

“…Using a linear regression model, we estimated fresh weight for this dataset, achieving a root mean square error (RMSE) of 18.2 g when using only the estimated plant volume, and 17.3 g when both volume and geometric features were included. …”
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Optimization of a cylindrical heatsink with L-shaped fins to minimize thermal resistance variation by installation angle by Gihyun Song, Hak-Ho Nam, Seungmin Heo, Se-Jin Yook

“…A correlation equation to estimate the thermal resistance of an L-finned cylindrical heatsink was proposed, predicting thermal resistance with an error margin of up to 15 %. The cylindrical heatsink with L-shaped fins developed in this study is expected to be applicable in various LED lighting systems requiring both reduced heatsink mass and minimal thermal resistance variation with changes in installation angle.…”
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Motion Capture Technologies for Athletic Performance Enhancement and Injury Risk Assessment: A Review for Multi-Sport Organizations by Bahman Adlou, Christopher Wilburn, Wendi Weimar

“…Environmental factors substantially impact system performance, with aquatic settings introducing an additional orientation error of 2° versus terrestrial applications. Outdoor environments challenge GNSS-based tracking (±0.3–3 m positional accuracy). …”
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Hot Deformation Behavior and Optimization of Processing Parameters for 4Cr16MoCu Martensitic Stainless Steel by Jiayuan Li, Ling Li, Zhongchao Wu, Tianhao Zeng, Xiaochun Wu

“…The model demonstrated high accuracy, with a correlation coefficient (R²) of 0.9917 and an average absolute relative error (AARE) of 3.8%, providing a reliable theoretical foundation for practical production applications. …”
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