Automatic Pairwise Coarse Registration of Terrestrial Point Clouds Using 3D Line Features by Yongjian Fu, Zongchun Li, Feng Xiong, Hua He, Yong Deng, Wenqi Wang

“…The rotation and translation errors of aligning the nine experimental pairwise point clouds were all less than 0.50° and 0.55m, respectively. …”
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An evaluation methodology for machine learning-based tandem mass spectra similarity prediction by Michael Strobel, Alberto Gil-de-la-Fuente, Mohammad Reza Zare Shahneh, Yasin El Abiead, Roman Bushuiev, Anton Bushuiev, Tomáš Pluskal, Mingxun Wang

“…We especially highlight the role that collision energy plays in prediction errors. Finally, we release a continually updated version of our dataset online along with our data cleaning and splitting pipelines for community use. …”
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Integrated real-time precise point positioning system with B2b/B2a/B1C services by Zhetao Zhang, Hao Wang, Yuanxi Yang

“…Specifically, the satellite orbit and clock errors are corrected by the B2b and B2a services, and the ionospheric delays by the B1C services. …”
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Resilience in the Internet of Medical Things: A Review and Case Study by Vikas Tomer, Sachin Sharma, Mark Davis

“…The first step in these situations is to recover from failure as quickly as possible, resume the data transfer, and detect the cause of faults, failures, and errors. Several solutions exist in the literature to make the IoMT resilient to failure. …”
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Predicting trajectories of the north star ambulatory assessment total score in Duchenne muscular dystrophy. by Francesco Muntoni, James Signorovitch, Nathalie Goemans, Adnan Y Manzur, Nicolae Done, Gautam Sajeev, Jiayang Li, Hanane Akbarnejad, Aarushi Sharma, Susan J Ward, Erik H Niks, Laurant Servais, Eugenio Mercuri, Michela Guglieri, Volker Straub, Imelda de Groot, Deborah Ridout, PRO-DMD-01 study investigators, Association Française contre les Myopathies, NorthStar Clinical Network, Craig McDonald

“…The best-fitting model in the full study sample explained 39% of the variation in NSAA total score changes, with prediction errors of ±3.6, 5.1, 5.9, 7.5, 9.5 NSAA units during follow-up years 1-5, respectively. …”
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Detection of Invasive Species (Siam Weed) Using Drone-Based Imaging and YOLO Deep Learning Model by Deepak Gautam, Zulfadli Mawardi, Louis Elliott, David Loewensteiner, Timothy Whiteside, Simon Brooks

“…False positives often originated from foliage and bark under high solar illumination, and low exposure images reduced these errors considerably. The study demonstrates the feasibility of using YOLO models to detect invasive species in natural landscapes, providing a safe alternative to the current method involving human spotters in helicopters. …”
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Classification of maize seed hyperspectral images based on variable-depth convolutional kernels by Yating Hu, Hongchen Zhang, Hongchen Zhang, Changming Li, Qianfu Su, Wei Wang

“…Traditional manual classification methods are labor-intensive and prone to errors. In contrast, machine learning techniques—particularly convolutional neural networks (CNNs)—have demonstrated superior performance in terms of classification accuracy, robustness, and generalization. …”
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An Improved Artificial Neural Network Model for Effective Diabetes Prediction by Muhammad Mazhar Bukhari, Bader Fahad Alkhamees, Saddam Hussain, Abdu Gumaei, Adel Assiri, Syed Sajid Ullah

“…The revolution of artificial neural networks (ANNs) in the medical discipline emerged for data-driven applications, particularly in the healthcare domain. …”
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Generative adversarial network–enabled microstructural mapping from surface profiles for laser powder bed fusion by Jingwen Gao, Chenyang Zhu, Shubo Gao, Weiming Ji, Ming Xue, Kun Zhou

“…However, conventional quality control of LPBF-fabricated parts, including microstructure characterisation, often relies on trial-and-error experiments. These methods can be time-consuming, resource-intensive, and potentially destructive to specimens. …”
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Impact of Parameters and Tree Stand Features on Accuracy of Watershed-Based Individual Tree Crown Detection Method Using ALS Data in Coniferous Forests from North-Eastern Poland by Marcin Kozniewski, Łukasz Kolendo, Szymon Chmur, Marek Ksepko

“…Consequently, adjusting the pixel size of a canopy height model in the context of tree stand features is necessary to minimize error. Additionally, our findings show that there is a need to carefully assess the criterion of membership of a detected tree crown in a circular sample plot, which we based on the point cloud.…”
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A Comprehensive Analysis of Dropout Assisted Regularized Deep Learning Architectures for Dynamic Electricity Price Forecasting by Pooja Joshi, Stale Stordal, Gudbrand Lien, Deepti Mishra, Erik Haugom

“…The performance of model is assessed against regression-based models and benchmark DL architectures in terms of error matrices and computational time. The results demonstrate that the presented methodology enables the identification of the most appropriate DL architecture and demonstrates improved forecasting performance for electricity markets when compared against benchmarks.…”
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Prediction of Lithium-Ion Battery State of Health Using a Deep Hybrid Kernel Extreme Learning Machine Optimized by the Improved Black-Winged Kite Algorithm by Juncheng Fu, Zhengxiang Song, Jinhao Meng, Chunling Wu

“…The results show that IBKA-DHKELM achieves the smallest error, with an RMSE of only 0.0062, demonstrating exceptional non-linear fitting capability, high predictive accuracy, and good robustness.…”
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A student academic performance prediction model based on the interval belief rule base by Wenkai Zhou, Yunsong Li, Jiaxing Li, Tianhao Zhang, Xiping Duan, Ning Ma, Yuhe Wang

“…Finally, case studies on graduate applications and GPA of students demonstrate that the mean squared error (MSE) of the IBRB-C is 0.0024 and 0.1014, respectively. …”
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Geo-referencing Autonomous Vehicles Using LoD2 and HD Maps: Performance Assessment in Simulated Urban Environments by M. Wahbah, L. Ramme, D. Ernst, S. Vogel, I. Neumann, H. Alkhatib

“…We perform a comparative analysis between HD and LoD2 maps in a simulated CARLA environment, employing an Error State Kalman Filter (ESKF) to estimate the position, velocity, and orientation of an AV. …”
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TRUSTED: The Paired 3D Transabdominal Ultrasound and CT Human Data for Kidney Segmentation and Registration Research by William Ndzimbong, Cyril Fourniol, Loic Themyr, Nicolas Thome, Yvonne Keeza, Benoît Sauer, Pierre-Thierry Piéchaud, Arnaud Méjean, Jacques Marescaux, Daniel George, Didier Mutter, Alexandre Hostettler, Toby Collins

“…Four IMIR methods were benchmarked, and Coherent Point Drift performed best with an average Target Registration Error of 4.47 mm and Dice score of 84.10%. The TRUSTED dataset may be used freely to develop and validate segmentation and IMIR methods.…”
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An Adaptive Three-Dimensional Self-Masking Strategy for the Micro-Fabrication of Quartz-MEMS with Out-of-Plane Vibration Units by Yide Dong, Chunyan Yin, Guangbin Dou, Litao Sun

“…The unit exhibited a repeatability error below 1.13%, confirming the precision and reliability of the proposed fabrication strategy.…”
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Effect of Key Parameters on Ploughing Force Performance of Planing-Type Anti-Climbers by Zhuyao Li, Jiyou Fei, Dongxue Song, Hong He, Chang Liu, Chong Zhang

“…The results demonstrate that the model achieves ≤15% relative error compared with the simulation data and ≤5% deviation from the experimental measurements, confirming its engineering applicability. …”
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Distance and Velocity Characterizations Through Sampling Rate-Limited Main Interferometer in a Silicon Platform by Ting-Qing Liao, Ting-Chia Chang, Jhih-Jia Kang, Shih-Hsiang Hsu

“…Instead of an additional auxiliary interferometer, the direct Hilbert-transform resampling on the main interferograms of a silicon platform could correct the optical-source phase error to form compact light detection and ranging (LiDAR) systems in the characterizations of distances and velocities. …”
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Vibrator Rack Pose Estimation for Monitoring the Vibration Quality of Concrete Using Improved YOLOv8-Pose and Vanishing Points by Bingyu Ren, Xiaofeng Zheng, Tao Guan, Jiajun Wang

“…The results demonstrate that the improved YOLOv8-Pose achieved a 1.4% increase in accuracy compared with YOLOv8-Pose, and the proposed method monitored the rotation angle with an average error of 6.97° while maintaining a working efficiency of over 35 frames per second. …”
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Feasibility of Conoscopic Holography Measurement in the Stereolithography (SLA) Process with Alumina by Lorenzo Meana, Víctor Meana, Eduardo Cuesta, Pedro Fernández, Gonzalo Valiño, Braulio J. Álvarez

“…As additive manufacturing technologies continue to gain ground in industrial applications, the need for the accurate metrological evaluation of parts produced with advanced materials becomes increasingly critical. …”
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