Improved Sliding Mode Active Disturbance Rejection Control for Single-inductance Dual-output Buck Converter by HUANG Jinfeng, ZHOU Jie

“…Additionally, the steady-state error bounds of CRESO and the convergence time of the enhanced TSMC are derived.Results and DiscussionsA simulation and experimental platform for the SIDO Buck converter is established. …”
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Ultra-Wideband Analog Radio-over-Fiber Communication System Employing Pulse-Position Modulation by Sandis Migla, Kristaps Rubuls, Nikolajs Tihomorskis, Toms Salgals, Oskars Ozolins, Vjaceslavs Bobrovs, Sandis Spolitis, Arturs Aboltins

“…To enhance the reliability of transmitted reference PPM (TR-PPM) signals, the transmission system integrates Gray coding and Consultative Committee for Space Data Systems (CCSDS)-standard-compliant Reed-Solomon (RS) error correcting code (ECC). System performance was evaluated by transmitting pseudorandom binary sequences (PRBSs) and measuring the bit error ratio (BER) across a 5-m wireless link between two 20 <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="normal">d</mi><mi mathvariant="normal">B</mi><mi mathvariant="normal">i</mi></mrow></semantics></math></inline-formula> gain horn (Ka-band) antennas, with and without a 20 <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="normal">k</mi><mi mathvariant="normal">m</mi></mrow></semantics></math></inline-formula> single-mode optical fiber (SMF) link in transmitter side and ECC at the receiver side. …”
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Three-dimensional omnidirectional characterization methods of rock anisotropic wave velocity and acoustic emission location optimization by Shengjun MIAO, Wenxuan YU, Mingchun LIANG, Pengjin YANG, Conghao LI, Zejing LIU

“…The location error for siltstone is greater than that for marble due to three primary reasons. …”
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Research on the method of weight calculation and equipment arrangement optimization of tramcar by DUAN Huadong, LIU Xiaofeng, JIANG Zhongcheng, ZHANG Bo

“…Compared with the calculated results based on FE finite element model, the error was less than 4%, which proved that the weight calculation accuracy was high. …”
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A networked station system for high-resolution wind nowcasting in air traffic operations: A data-augmented deep learning approach. by Décio Alves, Fábio Mendonça, Sheikh Shanawaz Mostafa, Diogo Freitas, João Pestana, Dinarte Vieira, Marko Radeta, Fernando Morgado-Dias

“…For the most challenging task, the 30-minute ahead forecasts, the model achieved a wind speed Mean Absolute Error (MAE) of 0.78 m/s and a wind direction MAE of 33.06°. …”
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Deep Learning Based Channel Estimation for UAVs: A Modified U-Net Approach by GUPTA, C., YADAV, S. S.

“…A stable and reliable communication link is crucial for unmanned aerial vehicle (UAV) applications. Key challenges include the UAV's high mobility (10-100 km/h) and an unstable data link. …”
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Statistical Analysis of Novel Ensemble Recursive Radial Basis Function Neural Network Performance on Global Solar Irradiance Forecasting by Manoharan Madhiarasan, Mohamed Louzazni, Brahim Belmahdi

“…Furthermore, the proposed ERRBFNN lowers the forecasting error to the least compared to other state-of-the-art forecasting models.…”
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Personalized trajectory inference framework integrating driving behavior recognition and temporal dependency learning. by Jinhao Yang, Junwen Cao, Mingyu Fang

“…The model achieves a mean RMSE of 4.46 and NLL of 3.89 across varying prediction horizons, with 35.8% error reduction attained after 100 hyperparameter optimization iterations. …”
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Combination of dynamic TOPMODEL and machine learning techniques to improve runoff prediction by Pin‐Chun Huang

“…The research findings show that the proposed methodology achieves the lowest mean relative error (MRE) at 0.106, the highest Pearson correlation coefficient (PC) at 0.938, and the highest coefficient of determination (R2) at 0.906 among the three dynamic TOPMODEL types adopted in this study. …”
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An Optimal Algorithm for Renewable Energy Generation Based on Neural Network by Weihua Zhao, Imran Khan, Shelily F. Akhtar, Mujahed Al-Dhaifallah

“…Then, to increase forecast accuracy, build an error correcting model. For verification, data from a centralized solar power station was used. …”
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Response Characteristics of Steppe Inland River Basins under Climate Change and Its Impact on Runoff from 1982—2020 by CHEN Hongguang, MENG Fanhao, SA Chula, LUO Min, WANG Mulan

“…Based on hydro-meteorological data and normalized difference vegetation index (NDVI) from 1982 to 2020,this paper studies the Wulagai River basin in Inner Mongolia and analyzes the vegetation response characteristics of the basin under climate change and its impact on runoff by adopting a hydrological model of soil and water assessment tool (SWAT) and statistical analysis method.The results show that the SWAT model has good applicability in the basin.The Nash-Sutcliffe efficiency coefficient (NSE) and coefficient of determination (R²) are larger than 0.62 in both regular and validation periods,and the relative error (PBLAS) is less than 18.8%.In the last 40 years,precipitation in the basin decreased slowly at a rate of 8.9 mm/10a,while temperature and actual evapotranspiration increased at a rate of 0.43°C/10a and 2.8 mm/10a,respectively,which indicates that the basin is becoming warm and dry.As the basin climate gets warm and dry,the vegetation recovers and grows vigorously.As a result,climate change and vegetation recovery lead to a reduced runoff depth of the basin.The study results can provide a reference for ecological conservation and sustainable utilization of water resources of inland river basins in arid and semi-arid regions.…”
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Hybrid Fuzzy Centroid with MDV-Hop BAT Localization Algorithms in Wireless Sensor Networks by Chakchai So-In, Weerat Katekaew

“…Many applications employing wireless sensor networks have been available in real-world scenarios. …”
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Machine learning in dentistry: a scoping review. by Shrey Lakhotia, Hormazd Godrej, Amandeep Kaur, Chaitanya Sai Nutakki, Michelle Mun, Pascal Eber, Leo Anthony Celi

“…Future research should prioritize error explainability, outlier reporting, reproducibility, fairness, and prospective validation.…”
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Smooth-pursuit performance during eye-typing from memory indicates mental fatigue by Tanya Bafna-Rührer, Per Bækgaard, John Paulin Hansen

“…Gaze tracking has wide-ranging applications, with the technology becoming more compact and processing power reducing. …”
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Comparative Analysis of Oversampling and SMOTEENN Techniques in Machine Learning Algorithms for Breast Cancer Prediction by Tri Yulian, Erliyan Redy Susanto

“…SVM proved more effective in identifying both classes with minimal error, particularly when combined with oversampling. …”
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Improved trilateration for indoor localization: Neural network and centroid-based approach by Satish R Jondhale, Amruta S Jondhale, Pallavi S Deshpande, Jaime Lloret

“…In addition, the significant localization error is induced during each iteration step during trilateration, which gets propagated in the next iterations. …”
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A Novel Methodology for the Stochastic Integration of Geophysical and Hydrogeological Data in Geologically Consistent Models by Alexis Neven, Philippe Renard

“…This paper presents a methodology to integrate such data within a geologically consistent model with robust error estimation. The methodology combines the Ensemble Smoother with Multiple Data Assimilation (ESMDA) algorithm with a hierarchical geological modeling approach (ArchPy). …”
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Study on Gas-liquid Two-phase Flow in Parallel Rectangular Sudden Expansion Micro-channels by Liu Shuangting, Jiao Yonggang, Gao Bo, Wang Haihua

“…error is 18.56%, which is superior to the prediction accuracy in classical literature. …”
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Photogrammetric approach to detect road pavement friction. by Zdeneˇk Svatý, Pavel Vrtal, Roman Shults, Tomáš Kohout, Luboš Nouzovský, Tomáš Blodek, Karel Kocián

“…Additionally, the goal was to introduce and define limits for camera calibration applicable to similar cases of object measurements at close distances. …”
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Feature fusion and selection using handcrafted vs. deep learning methods for multimodal hand biometric recognition by Saliha Artabaz, Layth Sliman

“…Using the minimal optimal feature set, we achieve an equal error rate (EER) of 0.71%, demonstrating superior efficiency and accuracy.…”
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