Quality-related and Quality-irrelevant Fault Detection and Diagnosis in Batch Fermentation Process Based on NSSAE by Zhong LIU, Zheng ZHANG, Xuyang LOU, Jinlin ZHU

“…Based on the results of numerical simulations and lactic acid bacteria batch fermentation experiments, the NSSAE algorithm proposed in this paper demonstrated the ability to accurately distinguish between quality-related and quality-irrelevant faults. …”
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A method for mining over-limit patterns of low voltage in users based on hierarchical affinity propagation clustering by SHEN Shuhao, ZHONG Qing, XU Zhong, WANG Gang, LI Haifeng, WANG Longjun

“…Firstly, large-scale voltage data is clustered into several clusters using the HAP clustering algorithm, and these clusters are regarded as the different over-limit patterns of low voltage. …”
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Dual FOPID-neural network controller based on fast grey wolf optimizer: application to two-inputs two-outputs helicopter by Amar Rezoug, Jamshed Iqbal, Abdelkrim Nemra

“…The DRF-FG showed robustness in trajectory tracking compared to the controllers based on the Ant Lion Optimizer (DRF-A) and the Whale Optimization Algorithm (DRF-W). DRF-FG improved the average regulation performance by 1.702% and trajectory tracking by 0.152% compared with DRF-G.…”
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Modelling and Estimation of Interior Orientation of Non-Metric Cameras using Artificial Intelligence by Hasanain A. Ajjah, Ahmed H H Alboabidallah, Mamoun U. Mohammed, Awesar A. Hussain

“…Optimization was performed by Utilizing the Simulated Annealing algorithm based on stereo calibration to obtain the best possible values of these parameters that produce the minimum RMS-reprojection error attained. …”
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Deep learning improves physician accuracy in the comprehensive detection of abnormalities on chest X-rays by Pamela G. Anderson, Hannah Tarder-Stoll, Mehmet Alpaslan, Nora Keathley, David L. Levin, Srivas Venkatesh, Elliot Bartel, Serge Sicular, Scott Howell, Robert V. Lindsey, Rebecca M. Jones

“…Here, we present an FDA-cleared, artificial intelligence (AI) system which uses a deep learning algorithm to assist physicians in the comprehensive detection and localization of abnormalities on chest X-rays. …”
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A Driver Behavior Detection Model for Human-Machine Co-Driving Systems Based on an Improved Swin Transformer by Junhua Cui, Yunxing Chen, Zhao Wu, Huawei Wu, Wanghao Wu

“…The results show that the proposed model algorithm has a better performance in 10 classifications of driver behavior detection, with an accuracy of 99.42%, which is improved by 3.8% and 1.68% compared to Vgg16 and MobileNetV2, respectively. …”
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SVDD: SAR Vehicle Dataset Construction and Detection by Dan Gao, Xiaofang Wu, Zhijin Wen, Yue Xu, Zhengchao Chen

“…With the advent of high-quality SAR images and the rapid development of computing technology, the object detection algorithms based on convolution neural network have attracted a lot of attention in the field of SAR object detection. …”
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A Recognition Methodology for the Key Geometric Errors of a Multi-Axis Machine Tool Based on Accuracy Retentivity Analysis by Shijie Guo, Shufeng Tang, Dongsheng Zhang

“…Then, the fruit fly optimization algorithm (FOA) is adopted to determine the compensation values through multiobjective tradeoffs between accuracy retentivity and fluctuation in the geometric errors. …”
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Analysis and Simulation of the Early Warning Model for Human Resource Management Risk Based on the BP Neural Network by Xue Yan, Xiangwu Deng, Shouheng Sun

“…The back propagation (BP) neural network is an information analysis and processing system formed by using the error back propagation algorithm to simulate the neural function and structure of the human brain, which can handle complex and changeable things that do not have an obvious linear relationship between output results and input factors, so as to find the objective connection between the two. …”
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Large-Scale Survey of Unselected Automated Visual Fields in a Major Reading Center: Patterns and Data Analysis by Lilly Zborowski-Naveh, Rita Ehrlich, Moshe Luski, Dov Weinberger, Mona Boaz, Dan D. Gaton

“…The Swedish Interactive Testing Algorithm (SITA) was applied in 1.0% of cases. More than half (56.8%) of the population had a reliability score of 1, and 22.7% had a score of 2, indicating a valid result for 79.4% of patients, providing clinically useful information. …”
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Evaluation of Failure Probability in Series System of Three-Axle Trucks under Strong Crosswind by Yahui Hu, Yingshi Guo, Rui Fu, Qingjin Xu

“…An advanced Monte Carlo simulation algorithm based on importance sampling is used to determine the probability of a three-axle truck with FPSS under strong crosswinds; the given acceptable probability of failure (accident) is used to obtain the critical safety speed. …”
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A VHDL Code for Offset Pulse Position Modulation Working with Reed Solomon System by Using ModelSim by Ahmed H. Albatoosh, Mohamed Ibrahim Shuja'a, Basman M. Al-Nedawe

“…The simulation was carried out in very high-speed integrated circuit hardware description language (VHDL), and a field-programmable gate array was used (FPGA) It made use of a Boolean function to function to program code for an algorithm that is working. Because of its performance, time to market, cost, reliability, and long-term maintenance benefits, FPGA is an appropriate platform for implementing error correction code (ECC). …”
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Designing Load-Bearing Bio-Inspired Materials for Simultaneous Static Properties and Dynamic Damping: Multi-Objective Optimization for Micro-Structure by Bo Dong, Yunfei Jia, Wei Wang

“…Using the NSGA-II optimization algorithm, a set of optimal solutions were solved. …”
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Loss shaping enhances exact gradient learning with Eventprop in spiking neural networks by Thomas Nowotny, James P Turner, James C Knight

“…Here, we investigate how the recently discovered Eventprop algorithm for gradient descent on exact gradients in spiking neural networks (SNNs) can be scaled up to challenging keyword recognition benchmarks. …”
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A Correlation Analysis-Based Structural Load Estimation Method for RC Beams Using Machine Vision and Numerical Simulation by Chun Zhang, Yinjie Zhao, Guangyu Wu, Han Wu, Hongli Ding, Jian Yu, Ruoqing Wan

“…The validation results of RC beams under four-point bending loads show that the proposed algorithm can quickly estimate load levels based on numerical simulation results, and the mean absolute percentage error (MAPE) for load estimation based solely on a single measured structural crack image is 20.68%.…”
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Integration of a Heterogeneous Battery Energy Storage System into the Puducherry Smart Grid with Time-Varying Loads by M A Sasi Bhushan, M. Sudhakaran, Sattianadan Dasarathan, Mariappane E

“…Adopting an MPC-based algorithm design framework enables the development of an effective control strategy for complex systems. …”
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Parallelizing Quantum Simulation With Decision Diagrams by Shaowen Li, Yusuke Kimura, Hiroyuki Sato, Masahiro Fujita

“…Based on the experiment results, our proposed strategy achieves a 2–3 times faster simulation of Grover's algorithm and random circuits than the state-of-the-art single-thread DD-based simulator DDSIM.…”
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Deep Learning for Spectroscopic X‐ray Nano‐Imaging Denoising by Tianyu Fu, Kai Zhang, Qingxi Yuan, Jizhou Li, Piero Pianetta, Yijin Liu

“…To address this issue, a deep learning‐based algorithm is developed for suppressing the image noise, grounded in self‐supervised learning principles. …”
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Problematic Issues of the Development and Implementation of the Code of Ukraine on Administrative Offenses by O. Yu. Kyrychenko

“…The author has suggested own vision of the structure of the new Code and its content, has emphasized the necessity of determining the legal entity as a subject of administrative liability, as well as the introduction of the algorithm of bringing MPs, deputies of local councils and judges to administrative liability. …”
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Collaborative Knowledge Infusion for Low-Resource Stance Detection by Ming Yan, Tianyi Zhou Joey, W. Tsang Ivor

“…Additionally, we also introduce the parameter-efficient collaborative adaptor with a staged optimization algorithm, which collaboratively addresses the challenges associated with low-resource stance detection tasks from both network structure and learning perspectives. …”
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