A Distributed Cooperative Anti-Windup Algorithm Improving Voltage Profile in Distribution Systems with DERs’ Reactive Power Saturation by Giovanni Mercurio Casolino, Giuseppe Fusco, Mario Russo

“…If the reference reactive current output by the PI exceeds the maximum reactive power capacity of the DER, the control unit saturates, preventing the optimal voltage regulation at the connection node of the Active Distribution Network (ADN). …”
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Research on an intelligent coagulant dosing system based on alum floc image recognition by FU Yuan, LEI Zhifeng, CUI Dongfeng, GUO Zhongquan, CAI Bohan, XIAO Yan, ZHOU Aijiao*

“…And on this basis, a 7-dimensional fully connected BP neural network was added for training through a sample set of (563, 7) (563 samples containing 7 parameters such as the number of alum flocs, the average equivalent diameter of alum flocs, and the inflow flow rate). …”
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Coordinated Variable Speed Limit Control for Consecutive Bottlenecks on Freeways Using Multiagent Reinforcement Learning by Si Zheng, Meng Li, Zemian Ke, Zhibin Li

“…More specifically, the MARL-VSL significantly improved the average driving speed and speed homogeneity across the entire freeway.…”
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Intelligent text analysis for effective evaluation of english Language teaching based on deep learning by Yuan Ren, Wenjuan Fan, Jinhai Wang

“…Building on traditional deep neural networks (DNNs), the model incorporates text structure features and attention mechanisms, while adversarial training is employed to optimize feature extraction and enhance cross-prompt adaptability. …”
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PREDICTION SYSTEM FOR THE AMOUNT OF SUGAR PRODUCTION USING ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM by Ahmad Kamsyakawuni, Walidatush Sholihah, Abduh Riski

“…ANFIS is a combined method of two systems, namely a fuzzy logic system and an artificial neural network system. This research consists of data collection, ANFIS system design, ANFIS training, ANFIS testing, accuracy calculation, and result analysis. …”
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A Configurable Accelerator for CNN-Based Remote Sensing Object Detection on FPGAs by Yingzhao Shao, Jincheng Shang, Yunsong Li, Yueli Ding, Mingming Zhang, Ke Ren, Yang Liu

“…The results show that, under INT16 or INT8 precision, the system achieves remarkable throughput in most convolutional layers of the network, with an average performance of 153.14 giga operations per second (GOPS) or 301.52 GOPS, which is close to the system’s peak performance, taking full advantage of the platform’s parallel computing capabilities.…”
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Preparation of high-flowability ultra-early-strength grouting material and investigation of its mechanical properties in reinforcing fractured sandstone. by Yijiang Zong, Dong Zhu, Liang Yue, Xiangling Tao, Min Chen

“…Using a five-level orthogonal experimental, the optimal mix ratio was determined: 5.00 wt.% modified ultrafine fly ash, 10.00 wt.% ultrafine silica fume, 9.00 wt.% nano-SiO2, and 0.05 wt.% polycarboxylate superplasticizer. …”
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An Efficient Evolutionary Task Scheduling/Binding Framework for Reconfigurable Systems by A. Al-Wattar, S. Areibi, G. Grewal

“…The framework utilizes an Island Based Genetic Algorithm flow that optimizes several objectives including performance, area, and power consumption. …”
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A Multimodal Approach of Machine and Deep Learnings to Enhance the Fall of Elderly People by Saleh Al meraikhi, Murad Al-Rajab

“…The working system achieved results were 97% accurate, with the highest being achieved by the Convolutional Neural Network algorithm. These results were higher than other state-of-the-art research conducted in the field.…”
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Potato Disease and Pest Question Classification Based on Prompt Engineering and Gated Convolution by Wentao Tang, Zelin Hu

“…The GF-CNN combines outputs from convolutional kernels of varying sizes, and after processing with max-pooling and average-pooling, a gating mechanism is employed to regulate the flow of information, thereby optimizing the text feature extraction process. …”
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Application of Machine Learning to Statistical Evaluation of Artificial Rainfall Enhancement by Li Dan, Lin Wen, Liu Qun, Feng Hongfang, Hu Shuping, Wang Zhihai

“…In order to further overcome the time asynchronization and uneven spatial distribution of rainfall in the two regions, the convolutional neural network CNN optimizers (RMSP, ADAM and SGD) are used to establish the contrast-target region rainfall relationship model based on the grid data of natural rainfall plane. …”
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Use of the theory of central places for the improvement of the administrative-territorial device of the Kharkiv region by Artur Golikov, Pavlо Chernomaz

“…After the application of the Kristaller grid, the calculation of the index of the measure of dissimilarity for the Kharkiv region showed a value close to the average, which indicates the optimality of the model. …”
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Real-time Detection Algorithm of Expanded Feed Image on the Water Surface Based on Improved YOLOv11 by ZHOU Xiushan, WEN Luting, JIE Baifei, ZHENG Haifeng, WU Qiqi, LI Kene, LIANG Junneng, LI Yijian, WEN Jiayan, JIANG Linyuan

“…[Methods]The YOLOv11-AP2S model enhanced the YOLOv11 algorithm by incorporating a series of improvements to its backbone network, neck, and head components. Specifically, an attention for fine-grained categorization (AFGC) mechanism was introduced after the 10th layer C2PSA of the backbone network. …”
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Proactive Data Placement in Heterogeneous Storage Systems via Predictive Multi-Objective Reinforcement Learning by Suchuan Xing, Yihan Wang

“…Our method employs Long Short-Term Memory networks and Transformer architectures to model complex temporal dependencies in I/O traces, generating predictive access probability distributions for data blocks. …”
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Monitoring Canopy Height in the Hainan Tropical Rainforest Using Machine Learning and Multi-Modal Data Fusion by Qingping Ling, Yingtan Chen, Zhongke Feng, Huiqing Pei, Cai Wang, Zhaode Yin, Zixuan Qiu

“…Four advanced machine-learning algorithms—random forest (RF), gradient boosting decision tree, convolutional neural network, and backpropagation neural network—were compared in terms of forest canopy height in the Hainan Tropical Rainforest National Park. …”
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Category semantic and global relation distillation for object detection by Yanpeng LIANG, Zhonggui MA, Zongjie WANG, Zhuo LI

“…To address this challenge, various model compression techniques have been developed, including network pruning, lightweight architecture design, neural network quantization, and knowledge distillation. …”
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Maximizing YOLOv2 efficiency: A study on multiclass detection of indoor objects by G Divya Deepak, Subraya Krishna Bhat

“…Based on an indoor object detection dataset containing 2213 images covering varying lighting conditions, backgrounds, occlusion and high inter-class differences, the YOLOv2 network is refined to enhance detection performance by examining the impact of different deep CNN architectures (Tiny-Coco, DarkNet-19-Coco), solvers (SGDM, RMSProp, Adam), learning rates (10−5, 10−4, 10−3), and detection thresholds (0.1, 0.2, 0.3) on mean average precision (mAP) and detection scores. …”
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Adherence and intensity in multimodal lifestyle-based interventions for cognitive decline prevention: state-of-the-art and future directions by Natalia Soldevila-Domenech, Amaia Ayala-Garcia, Mariagnese Barbera, Jenni Lehtisalo, Laura Forcano, Ana Diaz-Ponce, Marissa Zwan, Wiesje M. van der Flier, Tiia Ngandu, Miia Kivipelto, Alina Solomon, Rafael de la Torre

“…Adjusting the expected dose by average adherence enables estimation of the observed dose and intensity, which could be informative for identifying optimal dosage thresholds that maximize cognitive benefits across different populations. …”
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Space-Time Line Code Aided Offset Spatial Modulation by Yashan Pang, Yue Xiao, Xia Lei, Yong Liang Guan, Jingon Joung

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Insulator Defect Detection Algorithm Based on Improved YOLOv11n by Junmei Zhao, Shangxiao Miao, Rui Kang, Longkun Cao, Liping Zhang, Yifeng Ren

“…This paper proposes an enhanced defect detection approach based on a lightweight neural network derived from the YOLOv11n architecture. Key innovations include a redesigned C3k2 module that incorporates multidimensional dynamic convolutions (ODConv) for improved feature extraction, the introduction of Slimneck to reduce model complexity and computational cost, and the application of the WIoU loss function to optimize anchor box handling and to accelerate convergence. …”
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