Breaking Through GNSS Outage: Advanced Stochastic Model for MEMS IMU in Navigation by Ahmed Shahrawy, Mahmoud A. Shawky, Adel M. Soliman, Wali Ullah Khan, Ahmad Almogren, Ahmed G. Abdellatif, Syed Tariq Shah

“…This article employs three techniques for modeling stochastic errors: the autocorrelation function (ACF), the Allan variance (AV), and the generalized method of wavelet moments (GMWM). Two different-grade inertial measurement units (IMUs) evaluate the effectiveness of ACF, AV, and GMWM in modeling inertial sensor noise: The ADIS low-cost microelectromechanical systems (MEMS) grade IMU and the Spatial MEMS tactical-grade IMU. …”
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Assessment of GOCI-II satellite remote sensing products in Lake Taihu by Min Zhao, Min Zhao, Huaming Li, Hao Li, Xuan Zhang, Xiaosong Ding, Xiaosong Ding, Fang Gong

“…The study also evaluated the accuracy of derived parameters, such as chlorophyll-a (Chl-a) concentration, total suspended matter (TSM) concentration, and phytoplankton absorption coefficient (aph), based on these atmospheric correction algorithms. …”
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Study on water quality analysis and early-warning technology based on rough set and evidence theory by ZHU Qiong-yao, ZHANG Guang-xin, FENG Tian-heng, HUANG Ping-jie, HOU Di-bo

“…As it is known to all, there are lots of monitoring parameters in water quality detection, monitoring and information management system, and the evolution principles and changing trends of water quality are difficult to be obtained. …”
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Quantifying Uncertainties in Solar Wind Forecasting due to Incomplete Solar Magnetic Field Information by Stephan G. Heinemann, Jens Pomoell, Ronald M. Caplan, Mathew J. Owens, Shaela Jones, Lisa Upton, Bibhuti Kumar Jha, Charles N. Arge

“…Further comparison with the thermodynamic Magnetohydrodynamic Algorithm outside a Sphere model indicates that uncertainties in the different models can lead to even larger variations in solar wind forecasts compared to those within a single model. …”
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Characteristic, relationship and impact of thermokarst lakes and retrogressive thaw slumps over the Qinghai-Tibetan plateau by Wenwen Li, Denghua Yan, Yu Lou, Baisha Weng, Lin Zhu, Yuequn Lai, Yunzhe Wang

“…We further employed the eXtreme gradient boosting algorithm and ICESat-2 ATL08 laser altimetry data to quantify changes in water storage due to TLs. …”
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An analysis of spatial changes in the manufacturing industry in china’s three major urban clusters from 2015 to 2019 using POI data by Chenxi Jin, Chenjing Fan, Yiwen Gong, Xinran Huang, Shiqi Li, Runhan Liu, Chunwei Guo, Yuxin Liu

“…The evolution of the manufacturing industry at the scale of 451 districts and counties in the urban clusters and the factors driving new entrants in the manufacturing industry were studied. …”
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High-precision deformation monitoring and intelligent early warning for wellbore based on BDS/GNSS. by Jiang Li, Lei Dai, Keke Xu, Xinyu Mei, Yifu Liu, Jianlin Shi, Hebing Zhang

“…A quantitative analysis was conducted on the performance of various combinations of BDS/GNSS in wellbore deformation monitoring, and the effects of different baseline lengths on the monitoring results were evaluated. …”
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Fault Diagnosis of Rolling-Element Bearing Using Multiscale Pattern Gradient Spectrum Entropy Coupled with Laplacian Score by Xiaoan Yan, Ying Liu, Peng Ding, Minping Jia

“…Results confirm the availability of our proposed algorithm in feature extraction and show that our method can recognize effectively different bearing fault categories and severities. …”
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A location-constrained crowdsensing task allocation method for improving user satisfaction by Huihui Chen, Bin Guo, Zhiwen Yu, Liming Chen

“…For the purpose of emulating real scenarios, different scales of maps, tasks, and workers are simulated to evaluate algorithms. …”
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Watershed Health Prediction based on Surface Water Quality Variables (Case Study: Taleghan Watershed) by Payam Ebrahimi, Ali Salajegheh, Mohsen Mohseni Saravi, Arash Malekian, Amir Sadoddin

“…First, the variables that had the most effect on the model were determined and then the gene expression algorithm was created. In order to evaluate the generated model, three factors of determination coefficient, mean error of absolute and root mean square error were used. 3-Results and Discussion Using the obtained results, it was found that during investigated time, the use of normalized data provides different results than normal data. …”
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Predicting forest above-ground biomass using SAR imagery and GEDI data through machine learning in GEE cloud by Chiranjit Singha, Kishore Chandra Swain, Satiprasad Sahoo, Ayad M. Fadhil Al-Quraishi, Joseph Omeiza Alao, Hussein Almohamad, Mohamed Fatahalla Mohamed Ahmed, Hazem Ghassan Abdo

“…The scatterplot analysis revealed a positive correlation between forest biomass and factors, such as forest canopy height, elevation, normalized differential vegetation index, normalized differential moisture index, and the ratio of VV/VH after the monsoon season. …”
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Identification of lipid metabolism related immune markers in atherosclerosis through machine learning and experimental analysis by Hang Chen, Biao Wu, Biao Wu, Kunyu Guan, Liang Chen, Kangjie Chai, Maoji Ying, Dazhi Li, Weicheng Zhao

“…The ssGSEA technique was first utilized to assess lipid metabolism scores in samples affected by atherosclerosis, thereby aiding in the discovery of important regulatory genes linked to lipid metabolism via WGCNA. Following this, differential expression analysis and functional evaluations were carried out, after which various machine learning approaches were employed to determine significant diagnostic genes for atherosclerosis. …”
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Hybrid data-driven and physics-informed regularized learning of cyclic plasticity with neural networks by Stefan Hildebrand, Sandra Klinge

“…An extendable, efficient and explainable Machine Learning approach is proposed to represent cyclic plasticity and replace conventional material models based on the Radial Return Mapping algorithm. High accuracy and stability by means of a limited amount of training data is achieved by implementing physics-informed regularizations and the back stress information. …”
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Vascular anomalies in childhood. Review and update by Juan Carlos López Gutiérrez, Jesús Pozo Losada, Manuel Gómez Tellado

“…They are completely different diseases, although they are often grouped under the umbrella term of vascular anomalies.The diagnostic algorithm used in the clinical evaluation of vascular anomalies should be based on a thorough history-taking and detailed physical examination.Future knowledge in this field will be based above all on genetic findings and therapeutic innovations. …”
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On the Impact of Labeled Sample Selection in Semisupervised Learning for Complex Visual Recognition Tasks by Eftychios Protopapadakis, Athanasios Voulodimos, Anastasios Doulamis

“…We propose and explore a variety of combinatory sampling approaches that are based on sparse representative instances selection (SMRS), OPTICS algorithm, k-means clustering algorithm, and random selection. …”
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Spectrum-Convertible BVWXC Placement in OFDM-Based Elastic Optical Networks by Mohammad Hadi, Mohammad Reza Pakravan

“…Finally, we use simulation results to evaluate the accuracy of the proposed method for calculating connection request blocking probability and the capability of the introduced algorithm for SCBVWXC placement.…”
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Application of convolutional neural networks in the intelligence security system subsystem by V. S. Demeshko, A. I. Фёдоров

“…The tasks of the intelligence subsystem for detecting and recognizing ground-based objects of observation in a complex phono-target environment are defined.The task of detecting an object of observation was solved on the basis of a previously proposed algorithm. The disadvantage of this algorithm was the presence of false positives from a flickering complex phono-target environment. …”
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Using S-Curve Transforms and Gamma Correction for MR Images Contrast Enhancement by Manar Al-Abaji, Zohair Al-Ameen

“…Moreover, it was compared with four different CE approaches and evaluated using three measures. …”
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Machine Learning Model for Construction Time Prediction: A Case of Selected Public Building Projects in Hosanna, Ethiopia by Demoze Wondimu Debero, Ephrem Girma Sinesilassie

“…A questionnaire survey is designed to collect data, and subsequently, the study was performed using the Python programming language for development and validation purposes with different libraries used. The study developed Bromilow’s time-cost model using a simple linear regression algorithm and Love et al.’s time-floor model using a multiple linear regression algorithm and proposed a parametric model using random forest, XGBoost, decision tree, K-nearest neighbor, and polynomial regression algorithms. …”
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Microwave Radar Sensing of Sea Waves: An Effective Reflection Coefficient by Karaev Vladimir, Panfilova Mariya Andreevna, Titchenko Yu., Meshkov Evgeniy Mihaylovich, Kovaldov Dmitry, Xiuzhong Li, Yijun He

“…SWIM data were used to evaluate the developed algorithm. Processing of the test data set confirmed the efficiency of the algorithm. …”
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