Evaluation of a High-Accuracy Indoor-Positioning System with Wi-Fi Time of Flight (ToF) and Deep Learning by Doan Perdana, I Made Arya Indra Tanaya, Abdul Aziz Marwan, Fityanul Akhyar

“…Our experimental results show that our IPS, DeepIndoor, can achieve an average positioning error or mean square error of 0.1749 m, and root mean square error of 0.5740 m in scenario 3, where 1–10 AP pairs or the raw dataset is used.…”
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Integration of UAV-derived digital elevation model and GNSS for orthometric height determination in urban mapping by Ibrahim O. RAUFU, Herbert TATA, Emmanuel B. ADEWOLE

“…The UAV-derived orthometric heights achieved a Root Mean Square Error (RMSE) of 0.514 m, while the GNSS-derived orthometric heights yielded a slightly lower RMSE of 0.470 m. …”
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SMRFR: A global multilayer soil moisture dataset generated using Random Forest from multi-source data by Yuhan Liu, Yuanyuan Zha, Gulin Ran, Yonggen Zhang, Liangsheng Shi

“…SMRFR achieved an unbiased root mean square error of 0.0339 m3/m3 on the validation set. …”
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Comparison of Machine-Learning Algorithms for Near-Surface Air-Temperature Estimation from FY-4A AGRI Data by Ke Zhou, Hailei Liu, Xiaobo Deng, Hao Wang, Shenglan Zhang

“…The results showed that the XGB model had better overall performance, with R2 of 0.902, bias of −0.087°C, and root-mean-square error of 1.946°C. The spatial variation characteristics of the Tair error of the XGB method were less obvious than those of the other methods. …”
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TSWS: An observation-based streamflow dataset of Tianshan Mountains watersheds (1901–2019) by Shuai Li, Wei Wei, Yaning Chen, Weili Duan, Gonghuan Fang

“…The dataset provides the first comprehensive simulation and its long time series will provide an important reference for climatic and hydrological studies.…”
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The ZiCOS-M CO₂ sensor network: measurement performance and CO₂ variability across Zurich by S. K. Grange, S. K. Grange, S. K. Grange, P. Rubli, A. Fischer, D. Brunner, C. Hueglin, L. Emmenegger

“…The hourly mean root mean squared error (RMSE) was 0.98 <span class="inline-formula">ppm</span> (range of 0.46 and 1.5 <span class="inline-formula">ppm</span>) and the mean bias ranged between <span class="inline-formula">−</span>0.72 and 0.66 <span class="inline-formula">ppm</span> when undergoing parallel measurements with a high-precision reference gas analyser for a period of 2 weeks or more. …”
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Continuous Estimation of Hand Kinematics From Electromyographic Signals Based on Power-and Time-Efficient Transformer Deep Learning Network by Chuang Lin, Chunxiao Zhao, Jianhua Zhang, Chen Chen, Ning Jiang, Dario Farina, Weiyu Guo

“…When tested on 38 subjects of the Ninapro DB2, the proposed model resulted in a correlation coefficient of <inline-formula> <tex-math notation="LaTeX">$0.82~\pm ~0.04$ </tex-math></inline-formula>, root mean squared error (RMSE) of <inline-formula> <tex-math notation="LaTeX">$10.77~\pm ~1.48$ </tex-math></inline-formula>, and normalized RMSE of <inline-formula> <tex-math notation="LaTeX">$0.11~\pm ~0.01$ </tex-math></inline-formula>, which were all similar to the results achieved by the state-of-the-art (SOTA) reference methods. …”
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Apexification in anterior tooth: case report by Maria Luiza Zamparoni Victorino, Gláucia Beatriz Gonçalves, Thais Cristina Vendrameto Borges, Marcelo Augusto Seron, Ricardo Sérgio Almeida, Fausto Rodrigo Victorino

“…Therefore, the objective of this study was to present a clinical case of endodontic treatment in tooth 21 with incomplete root formation. The patient was referred to the endodontic specialization clinic, an initial periapical radiograph was taken which revealed that tooth 21 had incomplete root formation and a periapical lesion, and a CT scan was requested. …”
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Impact of SLR long-term mean range biases on SLRF2020-based orbits of altimetry satellites by Sergei Rudenko, Mathis Bloßfeld, Alexander Kehm, Denise Dettmering, Julian Zeitlhöfler

“…This strategy leads to the research question, whether these RBs should and can be applied in SLR-observation-based precise orbit determination (POD) for any satellite to obtain the highest orbit quality possible while using an ITRS 2020 realization as a priori reference frame. In this paper, based on the POD results for four altimetry satellites (TOPEX/Poseidon, Jason-1, Jason-2, and Jason-3) over the total time interval 1992-2021 and single- as well as multi-satellite altimetry crossover analyses for Jason-2 (2008-2019), we show that the application of LAGEOS-1 long-term mean RBs and the estimation of RBs for certain stations and time spans according to the ILRS Data Handling File (DHF) for SLRF2020 (DHF2020) reduces the root-mean-square fits of SLR observations, scatter of estimated empirical accelerations in along- and cross-track directions, as well as standard deviations of single-satellite crossover differences, and thus improves the orbit quality of all tested altimetry satellites. …”
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Alpine Meadow Fractional Vegetation Cover Estimation Using UAV-Aided Sentinel-2 Imagery by Kai Du, Yi Shao, Naixin Yao, Hongyan Yu, Shaozhong Ma, Xufeng Mao, Litao Wang, Jianjun Wang

“…The performance of these estimates was evaluated against reference FVC values derived from centimeter-level UAV data. …”
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Lower Limb Torque Prediction for Sit-To-Walk Strategies Using Long Short-Term Memory Neural Networks by Chamalka Kenneth Perera, Alpha. A. Gopalai, Darwin Gouwanda, Siti. A. Ahmad, Pei-Lee Teh

“…Controllers in assistive technology require reference torque trajectories to set the level of assistance for a patient during rehabilitation or when aiding essential daily tasks such as sit-to-walk (STW). …”
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Non-Contact Oxygen Saturation Estimation Using Deep Learning Ensemble Models and Bayesian Optimization by Andrés Escobedo-Gordillo, Jorge Brieva, Ernesto Moya-Albor

“…As performance metrics for the SpO₂-estimation proposal, we calculated the Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and other parameters from the Bland–Altman (BA) analysis with respect to the reference. …”
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An Analytic Policy Gradient-Based Deep Reinforcement Learning Motion Cueing Algorithm for Driving Simulators by Xiaowei Huang, Xuhua Shi, Peiyao Wang, Hongzan Xu, Xiaojun Tang, Gaoran Zhang

“…This controller processes a sequence of vehicle motion reference signals over a future period, utilizing a multi-layer perceptron to generate the simulator&#x2019;s motion reference control signal sequences for the same duration. …”
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Fusing multiplatform topo-bathymetric point clouds based on a pseudo-grid model: A case study around Ganquan Island, South China sea by Fanlin Yang, Xiaolin Yu, Xiankun Wang, Xiaozheng Mai, Chunxiao Wang, Anxiu Yang, Dianpeng Su

“…The results show that the proposed algorithm can achieve ideal results in terms of the average root mean square error (RMSE) of the six reference samples, which is reduced from 0.41 m to 0.19 m. …”
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Morphological variations of mandibular first premolar on cone-beam computed tomography in a Saudi Arabian sub-population by Youssef A. Algarni, Muna J. Almufarrij, Ibrahim A. Almoshafi, Haneen H. Alhayaza, Nuha Alghamdi, Suheel Manzoor Baba

“…Considerable variation in the number of canals and roots found in these teeth has been reported. Aim: The purpose of this study is to investigate the root and root canal morphology of mandibular first premolar among Saudi Arabian subpopulation in Aseer using CBCT. …”
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Morphological variations of mandibular first premolar in a Saudi Arabian subpopulation evaluated using Cone Beam Computed Tomography CBCT by Youssef A. Algarni, Muna J. Almufarrij, Ibrahim A. Almoshafi, Haneen H. Alhayaza, Nuha Alghamdi, Suheel Manzoor Baba

“…Considerable variation in the number of canals and roots found in these teeth has been reported. Aim: The purpose of this study is to investigate the root and root canal morphology of mandibular first premolar among Saudi Arabian subpopulation in Aseer using CBCT. …”
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The Regulatory Effect of Se-Cd Interaction on Tea Plants (<i>Camellia sinensis</i> (L.) O. Kuntze) Under Cadmium Stress by Yanyun Sun, Yueling Zhao, Hongyu Zhou, Faxing Li, Yuanyuan Wang, Xiao Du

“…In root cells, Cd and Se were predominantly located in the cell wall, plasma membrane, and vacuole membrane; in stem cells, they were primarily found in the cell wall and cytoplasm adjacent to the cell wall; in leaf cells, they were mainly distributed in the plasma membrane, cytoplasm, and vacuole. …”
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Soil types create different rhizosphere ecosystems and profoundly affect the growth characteristics of ratoon sugarcane by Xiaoming Wang, Junjun Ma, Chaoxian Fang, Jinghuan Zhu, Shilong Wang, Zuli Yang

“…The study offers guidance for improving soil microbial community structure to enhance sugarcane growth and yield, serving as a valuable reference for soil management in sugarcane fields.…”
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Pemodelan Sistem Monitoring Kualitas Udara Pintar Berbasis Internet of Things dengan Pendekatan Machine Learning by Eddy Prasetyo Nugroho, Ani Anisyah, Deva Shofa Al Fathin, Muhammad Nur Yasin Amadudin, Muhammad Satria Ramadhani, Yosafat

“…Hasil evaluasi model menunjukkan nilai Root Mean Square Error (RMSE) sebesar 2,68 yang mencerminkan kinerja prediksi yang baik. …”
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Evaluation of the impact of COVID-19 on hepatitis B in Henan Province and its epidemic trend based on Bayesian structured time series model by Xinxiao Li, Yanyan Li, Shushuo Xu, Penghao Wang, Meng Hu, Haibin Li, Yongbin Wang

“…It was also found that the average absolute error, root mean square error, and root mean square percentage error generated by the BSTS model were smaller than ones generated by the ARIMA model. …”
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