Disturbance rejection control of the agricultural quadrotor based on adaptive neural network by Wenxin Le, Pengyang Xie, Jian Chen

“…Therefore, this paper makes an attempt to use the Radial Basis Function (RBF) neural network adaptive method combined with sliding mode control to control its height channel. …”
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UNIFIED POWER FLOW CONTROLLER CONTROL STRATEGIES for POWER FLOW by Fahd Banakhr

“…The idea behind the UPFC technique proposed in this paper is to provide the unique functional capability of independently controlling both the real and reactive power flow in the line. …”
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Research on Sensorless Technology of a Magnetic Suspension Flywheel Battery Based on a Genetic BP Neural Network by Weiyu Zhang, Fei Guo

“…The experimental results show that the method can effectively reduce feedback errors, improve the control accuracy, and output optimal control parameters in real time under complex road conditions, which significantly improves the reliability and control performance of the vehicle flywheel battery system.…”
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A Dockerized Approach to Dynamic Endpoint Management for RESTful Application Programming Interfaces in Internet of Things Ecosystems by Ebenhezer Mabotha, Nkateko E. Mabunda, Ahmed Ali

“…An emulated IoT environment was used to measure significant performance parameters, including functionality, throughput, response time, and scalability. …”
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Modeling of working processes in the frequency-adjustable hydraulic drive of manipulation systems with separate movement of links during operation of mobile machines by Lagerev A.V., Lagerev I.A.

“…The program allows to calculate the change in time of movement, speed and acceleration of the moving link of the handling system, pressure and volumetric flow rate of the working fluid in the characteristic points of the hydraulic system and a number of other parameters. The operation of the hydraulic drive of the real manipulation system was simulated with different laws of variation of the rotational speed of the volumetric pump and the obtained results were analyzed. …”
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HGCS-Det: A Deep Learning-Based Solution for Localizing and Recognizing Household Garbage in Complex Scenarios by Houkui Zhou, Chang Chen, Zhongyi Xia, Qifeng Ding, Qinqin Liao, Qun Wang, Huimin Yu, Haoji Hu, Guangqun Zhang, Junguo Hu, Tao He

“…Moreover, some of the existing research suffer from shortcomings in either their precision or real-time performance, particularly when applied to complex garbage detection scenarios. …”
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Modelación matemática del funcionamiento de las coronas de molinos considerando la flotación de la maza superior // An equivalent mechanism for the kinetic and dynamic analysis of... by Mario Javier Cabello-Ulloa, Juan José Cabello-Eras, Jorge Moya-Rodríguez, Rafael Goytisolo-Espinosa, José Alberto Velásquez-Pérez, Juan Rafael Mestizo- Cerón

“…General<br />equations for the velocity and acceleration for any type of gear tooth profile with variable distance<br />between centers are proposed through parametric method. Plotted these parameters for real sugar<br />cane mill gear and it is concluded that the instantaneous speed ratio is variable and the profile shape<br />produced accelerations.…”
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Statistical Inference for the Heteroscedastic Partially Linear Varying-Coefficient Errors-in-Variables Model with Missing Censoring Indicators by Yuye Zou, Chengxin Wu

“…Based on regression calibration, imputation, and inverse probability weighted methods, we define a class of modified profile least square estimators of the parameter and local linear estimators of the coefficient function, which are applied to constructing estimators of the error variance function. …”
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Principles of creating a digital twin prototype for the process of alkylation of benzene with propylene based on a neural network by K. G. Kichatov, T. R. Prosochkina, I. S. Vorobyova

“…Data was acquired in order to describe the functioning of the isopropylbenzene production unit. …”
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Alpha Power Transformed Generalized Weibull Distribution With Its Detailed Properties and Applications by Merga Abdissa Aga, Ayele Taye Goshu

“…Key properties such as the quantile function, moments, and moment generating function (MGF) are derived, showcasing the distribution’s versatility in modeling both monotone and nonmonotone hazard rate functions common in reliability and lifetime data analysis. …”
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On Statistical Properties of a New Bivariate Modified Lindley Distribution with an Application to Financial Data by Ahmed Elhassanein

“…There is an increasing interest in expanding the one-parameter Lindley distribution to two-parameter, three-parameter, and five-parameter. …”
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Roller-integrated compaction monitoring and assessment of high and low liquid limit silt subgrades using the Green spline interpolation algorithm by Yuchen Yan, Yanwen Zhu, Xian Yang, Lan Qiao, Chuping Wu, Zaizhan An, Qinglong Zhang, Ren Liu, Wang Guo

“…Initially, the compaction meter value (CMV) and compaction power per unit volume (E) were chosen as the real-time monitoring indexes for assessing the quality of compaction. …”
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A novel lightweight YOLOv8-PSS model for obstacle detection on the path of unmanned agricultural vehicles by Zhijian Chen, Yijun Fang, Jianjun Yin, Shiyu Lv, Farhan Sheikh Muhammad, Lu Liu

“…Compared to the original base network, it reduces the number of parameters by 55.8%, decreases the model size by 59.5%, and lowers computational cost by 51.2%. …”
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USING REINFORCEMENT LEARNING ALGORITHMS FOR UAV FLIGHT OPTIMIZATION by O. Dutsiak, V. Yuzevych

“…Areas of interest include autonomous navigation, real-time path planning and object recognition. However, autonomous flight poses a number of challenges for UAVs, including the development of control strategies, parameter tuning, adaptive control, real-time trajectory planning, and object recognition in uncertain environments. …”
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Exploring Machine Learning and Deep Learning Approaches for Battery Management Systems in EVs: A Comprehensive Review by Sathish J., Ramash Kumar K., Saraswathi D.

“…By synthesizing insights from various studies, this article presents improved parameters and valuable inferences. This article aims to highlight the pivotal role of artificial intelligence (AI) and deep learning in improving the functionality of the BMS, ultimately contributing to the performance and longevity of EVs.…”
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YOLOv8-Scm: an improved model for citrus fruit sunburn identification and classification in complex natural scenes by Guoxun Cong, Guoxun Cong, Xinghong Chen, Xinghong Chen, Zongyu Bing, Zongyu Bing, Wenhuan Liu, Wenhuan Liu, Xiangling Chen, Qun Wu, Zheng Guo, Zheng Guo, Yongqiang Zheng, Yongqiang Zheng

“…YOLOv8-Scm enables accurate, real-time citrus sunburn monitoring, providing strong technical support for smart orchard management and practical deployment.…”
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Generation of Spatial Structure of Urban Parks Based on Spatial Analysis of Agent-Based Models by Huizi KONG, Tianming LIU, Jiajie LIAO, Liu CUI

“…By adjusting model parameters, the foraging paths of slime molds in the designed site are simulated, and their spatial function distribution is analyzed. …”
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Active Cancellation of the Tonal Component of Sound Using a Discrete Fourier Transform of Variable Length by Michał ŁUCZYNSKI, Andrzej DOBRUCKI, Stefan BRACHMAŃSKI

“…The tonal component is approximated by a sinusoidal signal of a given amplitude and frequency. As the parameters of this component: amplitude, frequency and initial phase may be variable, it is important to detect these parameters in subsequent analysis time intervals (frames). …”
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Orthogonal Components Forming of the Microprocessor-Based Protection Input Signals by F. A. Romaniuk, V. Yu. Rumiantsev, Yu. V. Rumiantsev, V. S. Kachenya

“…The OS shaper model is implemented in the MatLab-Simulink dynamic modeling environment. The model functioning was checked using two types of test actions, viz. a sinusoidal signal with a frequency of 50 Hz (idealized action) and a signal close to the real secondary current of a short-circuit current transformer. …”
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GLS-YOLO: A Lightweight Tea Bud Detection Model in Complex Scenarios by Shanshan Li, Zhe Zhang, Shijun Li

“…Compared to the original YOLOv8, the model size was reduced by 38.85%, and the number of parameters decreased by 39.95%. This study presents innovative advances in agricultural robotics by significantly improving the accuracy and efficiency of tea bud harvesting, simplifying the configuration process for harvesting systems, and effectively lowering the technological barriers for real-world applications.…”
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