Integrating Tiny Machine Learning and Edge Computing for Real-Time Object Recognition in Industrial Robotic Arms by Nian-Ze Hu, Bo-An Lin, Yen-Yu Wu, Hao-Lun Huang, You-Xin Lin, Chih-Chen Lin, Po-Han Lu

“…By utilizing the Edge Impulse platform for data collection, model training, and optimization, edge devices and models for use in resource-limited environments were successfully generated. …”
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A New Approach to ORB Acceleration Using a Modern Low-Power Microcontroller by Jorge Aráez, Santiago Real, Alvaro Araujo

“…This work also allows for future optimizations that will improve the results of this paper.…”
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Real time wire rope detection method based on Rockchip RK3588 by Mengpeng Qian, Yong Wang, Shaoqing Liu, Zhanghou Xu, Zhenshan Ji, Ming Chen, Hailong Wu, Zuchao Zhang

“…Abstract In the era of fully mechanized and automated coal mine production, the need for autonomous fault detection and intelligent identification of wire ropes has become increasingly critical. Conventional model training and algorithmic computations rely on server-based systems, requiring significant computational resources. …”
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Precise GNSS Positioning with Time-differenced Carrier Phases at Variable Sampling Rates by S. Guo, H. Yang, Y. Gao

“…However, variable sampling rates are required for optimal performance in different dynamic applications. …”
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Detection of Tomato Leaf Pesticide Residues Based on Fluorescence Spectrum and Hyper-Spectrum by Jiayu Gao, Xuhui Yang, Simo Liu, Yufeng Liu, Xiaofeng Ning

“…In order to improve the operating rate of discrimination, a continuous projection algorithm (SPA) was used to extract the characteristic wavelengths of the fluorescence spectra and hyperspectral data of pesticide residues, and algorithms such as the least-squares support vector machine (LSSVM) algorithm and least partial squares regression (PLSR) were used to build a quantitative model, while algorithms such as the convolutional neural network (BPNN) algorithm and decision tree algorithm (CART) were used to build a qualitative model. …”
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Control Adaptativo Fraccionario Optimizado por Algoritmos Genéticos, Aplicado a Reguladores Automáticos de Voltaje by Marco E. Ortiz-Quisbert, Manuel A. Duarte-Mermoud, Freddy Milla, Rafael Castro-Linares

“…The work is focused on tuning the adaptive gains and the derivation order of the adaptive laws of the FOMRAC, determined through the minimization of a criterion function defined for the simplified model of the AVR, by means of the genetic algorithm (GA) optimization technique. …”
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Experimental Validation of Adaptive Sliding Mode Fuzzy Controller for an Inertially Stabilized Platform by Mohammad Nikkhoo, HASSAN SAYYADI, Mohammad saeid Seif

“…Despite the existence of uncertainties in dynamic system modeling, the outcomes of the implementation of the control algorithm and experimental tests indicated that the adaptive fuzzy sliding mode algorithm stabilized the line of sight with acceptable accuracy and improved its performance .…”
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A multi-agent reinforcement learning approach for continuous battery cell-level balancing by Yasaman Tavakol-Moghaddam, Mehrdad Boroushaki

“…Trained with the trust region policy optimization (TRPO) algorithm, the approach ensures stability and partial observability. …”
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Developing an Efficient Calibration System for Joint Offset of Industrial Robots by Bingtuan Gao, Yong Liu, Ning Xi, Yantao Shen

“…Therefore, there are several lines in space parameterized by robot joint offsets only and all these lines were constrained by the same point, that is, the center of the PSD surface. Consequently, an optimization model was formulated and the Levenberg-Marquardt (LM) algorithm was employed to identify the joint offsets. …”
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Dynamic Water Scheduling in the Northwest River Delta Basin Based on Minimum Discharge Flow Control in Cross-section by WU Di, FANG Chunyan, SHANG Yunfei

“…On this basis, by taking into account both ecological water demand and socio-economic water demand, the minimum discharge flow control index of the cross-section was determined, and a fitness function was constructed. The whale optimization algorithm was used to find the optimal water allocation plan. …”
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Energy-Efficient Multi-Agent Deep Reinforcement Learning Task Offloading and Resource Allocation for UAV Edge Computing by Shu Xu, Qingjie Liu, Chengye Gong, Xupeng Wen

“…Extensive experiments demonstrate that the algorithm achieves improvements in system latency and energy efficiency compared to conventional approaches. …”
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A Method Adjusting Consistency and Consensus for Group Decision-Making Problems with Hesitant Fuzzy Linguistic Preference Relations Based on Discrete Fuzzy Numbers by Meng Zhao, Ting Liu, Jia Su, Meng-Ying Liu

“…Besides, an illustrative example and comparative analysis are conducted through the proposed calculation process and the optimization algorithm. Finally, the analysis on the threshold values is made to help the decision-maker determine critical consensus level. …”
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Neural Network-Based Imitation Learning for Approximating Stochastic Battery Management Systems by Andrea Pozzi, Alessandro Incremona, Daniele Toti

“…Lithium-ion batteries play a pivotal role in enabling eco-friendly mobility, particularly in electric vehicles, but optimizing their charging process to improve battery lifespan, safety, and overall efficiency remains a significant challenge. …”
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Laser SLAM Matching Localization Method for Subway Tunnel Point Clouds by Yi Zhang, Feiyang Dong, Qihao Sun, Weiwei Song

“…We propose a novel coarse-to-fine registration strategy that includes geometric feature extraction and a keyframe-based pose optimization model. The method involves initial feature point set acquisition through point distance calculations, followed by the extraction of line and plane features, and convex hull features based on the normal vector’s change rate. …”
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Design of LQG Controller for Active Suspension without Considering Road Input Signals by Hui Pang, Ying Chen, JiaNan Chen, Xue Liu

“…Firstly, the half-vehicle and road input mathematical models of an active suspension system are established, with the weight coefficients of each evaluating indicator optimized by using genetic algorithm (GA). …”
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A Hierarchical Control Framework for Coordinating CAV-Dedicated Lane Allocation and Signal Timing at Isolated Intersections in Mixed Traffic Environments by Feng Chen, Cunbao Zhang, Yu Cao

“…Compared with benchmark approaches, the model achieves an average improvement of 31.8% in traffic efficiency. …”
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Data and Knowledge Dual-Driven Creep Life Prediction for Austenitic Heat-Resistance Steel by Xiaochang Xie, Mutong Liu, Ping Yang, Zenan Yang, Chengbo Pan, Chenchong Wang, Xiaolu Wei

“…In this study, we collected 216 creep data of austenitic heat-resistant steel, selected a variety of different machine learning algorithms to establish creep life prediction models, calculated and introduced a large amount of physical metallurgy knowledge highly related to creep based on Thermo-Calc, and converted the creep life into the form of the Larson–Miller parameter to optimize the data distribution, which effectively improved the prediction accuracy and interpretability of the model. …”
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Thermal-aware resource allocation in earliest deadline first using fluid scheduling by Muhammad Naeem Shehzad, Qaisar Bashir, Ghufran Ahmad, Adeel Anjum, Muhammad Naeem Awais, Umar Manzoor, Zeeshan Azmat Shaikh, Muhammad A Balubaid, Tanzila Saba

“…Thermal issues in microprocessors have become a major design constraint because of their adverse effects on the reliability, performance and cost of the system. This article proposes an improvement in earliest deadline first, a uni-processor scheduling algorithm, without compromising its optimality in order to reduce the thermal peaks and variations. …”
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MC64-ClustalWP2: a highly-parallel hybrid strategy to align multiple sequences in many-core architectures. by David Díaz, Francisco J Esteban, Pilar Hernández, Juan Antonio Caballero, Antonio Guevara, Gabriel Dorado, Sergio Gálvez

“…The new parallelization approach has focused into the most time-consuming stages of this algorithm. In particular, the so-called progressive alignment has drastically improved the performance, due to a fine-grained approach where the forward and backward loops were unrolled and parallelized. …”
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Evaluation of stroke sequelae and rehabilitation effect on brain tumor by neuroimaging technique: A comparative study. by Xueliang Guo, Lin Sun

“…The development of the 3D CNN model utilizes the ADAM optimization algorithm to facilitate the training process. …”
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