Numerical model of the pneumatic diaphragm actuator by Aleksandr Kovalenko

“…The key point of the investigation was development of the diaphragm model and its key parameter - effective area. …”
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A new verification approach for nowcasting based on intensity and spatial-temporal feature correction by Jun Liu, Tong Zhang, Yuanzhao Chen, Rui Wang, Mingjie Wang, Shuxin Wang, Ting Xu, Chunyang Zhao, Xunlai Chen

“…By introducing spatial neighborhood probability, the strict spatial matching requirement is weakened. Based on the Gaussian membership function in fuzzy logic, the value of forecasting grid below the threshold is explored. …”
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Forecasting monthly residential natural gas demand in two cities of Turkey using just-in-time-learning modeling. by Burak Alakent, Erkan Isikli, Cigdem Kadaifci, Tonguc S Taspinar

“…For each test point, a kernel function, tailored for the NGD predictions, is used in GPR to predict the query point. …”
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fR Gravity Effects on Charged Accelerating AdS Black Holes Using Holographic Tools by Adil Belhaj, Hasan El Moumni, Karima Masmar

“…We find that both holographic entanglement entropy and two-point correlation functions decrease by increasing the acceleration parameter A, matching perfectly with literature. …”
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Features of simulation of operator control of unmanned aerial vehicle and its target load by P. I. Savelov, Penghao Gu, A. A. Lobaty

“…As a typical example of a human-machine control system, the ground control point of the multifunctional unmanned aerial complex “Busel” is considered, which includes two workplaces for the UAV control operator and the target load control operator, which is considered equipment designed to monitor objects located on the earth’s surface…”
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COMPARATIVE RESEARCH REGARDING THE DESIGN AND THE DEVELOPMENT OF THE G CODE PROGRAMMING LANGUAGE BETWEEN CASE R290-02IS AND THE CLASSIC VERSION, CONSTITUENTS OF THE GARLAND PRODUCT... by Valeria Victoria IOVANOV

“…The most important function of any CNC machine is precise and rigorous control of the movement. …”
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Research on the Magnetorheological Finishing Technology of a High-Steepness Optical Element Based on the Virtual-Axis and Spiral Scanning Path by Chihao Chen, Chaoliang Guan, Meng Liu, Yifan Dai, Hao Hu

“…Firstly, the distribution law of the magnetic induction intensity inside the polishing wheel is analyzed by simulation, the stability of the removal efficiency of the removal function within the ±7^∘ angle of the normal angle of the polishing wheel is determined, and MRF is expanded from traditional single-point processing to circular arc segment processing. …”
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Echoes in the Noise: Posterior Samples of Faint Galaxy Surface Brightness Profiles with Score-based Likelihoods and Priors by Alexandre Adam, Connor Stone, Connor Bottrell, Ronan Legin, Yashar Hezaveh, Laurence Perreaul-Levasseur

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Prognostic value of no-reflow phenomenon in myocardial infarction: the role of the severity of ischemic damage by A. A. Frolov, M. G. Kashtanov, A. V. Korotkikh, I. G. Pochinka, I. A. Frolov, K. V. Kuzmichev, A. S. Mukhin, E. G. Sharabrin

“…Severe ischemia — more than 3 points. Propensity score matching was used to correct differences between the groups. …”
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Research on detection and tracking methods of unmanned ship water targets based on light vision by LIU Yibo, QIU Xinyu, WANG Tianhao, GAOYAN Xiusong, WANG Yintao

“…In terms of target detection, the YOLOv7 algorithm is used, which effectively improves the accuracy and recall rate of target detection by optimizing the loss function. In order to achieve accurate multi-target tracking, combined with self-trained model weights and Sort algorithm, continuous tracking of targets and accurate annotation of center point trajectories are successfully implemented. …”
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Estimating Shape Parameters of Piecewise Linear-Quadratic Problems by Zheng, Peng, Ramamurthy, Karthikeyan Natesan, Aravkin, Aleksandr Y.

“…Properties of these estimators depend on the choice of penalty and its shape parameters, such as degree of asymmetry for the quantile loss, and transition point between linear and quadratic pieces for the Huber function.In this paper, we develop a statistical framework that can help the modeler to automatically tune shape parameters once the shape of the penalty has been chosen. …”
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KPMapNet: Keypoint Representation Learning for Online Vectorized High-Definition Map Construction by Bicheng Jin, Wenyu Hao, Wenzhao Qiu, Shanmin Pang

“…Moreover, a novel point-line matching loss function is introduced to further refine the training process. …”
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Discovering novel lead-free solder alloy by multi-objective Bayesian active learning with experimental uncertainty by Qinghua Wei, Yuanhao Wang, Guo Yang, Tianyuan Li, Shuting Yu, Ziqiang Dong, Tong-Yi Zhang

“…The feature-point-start forward method in multi-objective optimization adopts two Gaussian process regression (GPR) models, one for strength and one for elongation, and their outputs build up the acquisition-function-modified objective space of strength and elongation. …”
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Exploring feature sparsity for out-of-distribution detection by Qichao Chen, Kuan Li, Zhiyuan Chen, Tomas Maul, Jianping Yin

“…Abstract Out-of-distribution (OOD) detection is a crucial problem in practice, especially, for the safe deployment of machine learning models in industrial settings. Previous work has used free energy as a score function and proposed a fine-tuning method that utilized OOD data in the training phase of the classification model, which achieves a higher performance on the OOD detection task compared with traditional methods. …”
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Color image hybrid noise filtering algorithm based on deep convolution neural network by Yongfei Yu, Yuanjian Yan

“…Then, the probability density function and noise probability density function of Gaussian noise are calculated to determine the hybrid noise feature points of color image. …”
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SYK correlators from 2D Liouville-de Sitter gravity by Herman Verlinde, Mengyang Zhang

“…In [1] it was shown that the two-point function of physical operators in a doubled SYK model matches in the semi-classical limit with the Green’s function of a massive scalar field in 3D de Sitter space. …”
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Short-Term Wind Power Interval Forecasting Based on an EEMD-RT-RVM Model by Haixiang Zang, Lei Fan, Mian Guo, Zhinong Wei, Guoqiang Sun, Li Zhang

“…In order to solve the above problems, we propose a short-term wind power interval forecasting model based on ensemble empirical mode decomposition (EEMD), runs test (RT), and relevance vector machine (RVM). First, in order to reduce the complexity of data, the original wind power sequence is decomposed into a plurality of intrinsic mode function (IMF) components and residual (RES) component by using EEMD. …”
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Investigating the spatio-temporal risk of in-ground fungal wood decay over Europe using the 5th European reanalysis (ERA5-Land) by Philip B. van Niekerk, Brendan N. Marais, Gry Alfredsen, Christian Brischke

“…Soil moisture and temperature data from the ERA5-Land repository were extracted for Europe over a 9 × 9 km point grid, between January 1993 and December 2022. …”
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Multi-Robot Cooperative Simultaneous Localization and Mapping Algorithm Based on Sub-Graph Partitioning by Wan Xu, Yanliang Chen, Shijie Liu, Ao Nie, Rupeng Chen

“…To address the challenges in multi-robot collaborative SLAM, including excessive redundant computations and low processing efficiency in candidate loop closure selection during front-end loop detection, as well as high computational complexity and long iteration times due to global pose optimization in the back-end, this paper introduces several key improvements. First, a global matching and candidate loop selection strategy is incorporated into the front-end loop detection module, leveraging both LiDAR point clouds and visual features to achieve cross-robot loop detection, effectively mitigating computational redundancy and reducing false matches in collaborative multi-robot systems. …”
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Toward model-based individualized fitting of hip-flexion exosuits for persons with unilateral transfemoral amputation by Finn G. Eagen, Nicholas P. Fey

“…The device is simulated for 18 individuals of K2 and K3 Medicare functional classification levels. A user-specific device profile is generated via a three-axis moment-matching optimization using an interior-point algorithm. …”
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