Modeling and control of automatic voltage regulation for a hydropower plant using advanced model predictive control by Ebunle Akupan Rene, Willy Stephen Tounsi Fokui

“…The findings were compared with those derived from an optimal proportional integral derivative (PID) controller designed using the artificial bee colony (ABC) algorithm. …”
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An Empirical Configuration Study of a Common Document Clustering Pipeline by Anton Eklund, Mona Forsman, Frank Drewes

“…The results suggest that BERT embeddings combined with UMAP dimension reduction to no less than 15 dimensions provides a good basis for clustering, regardless of the specific clustering algorithm used. Moreover, while UMAP performed better than PCA in our experiments, tuning the UMAP settings showed little impact on the overall performance. …”
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Adaptive rumor propagation and activity contagion in higher-order networks by Yafang Dong, Liang’an Huo, Matjaž Perc, Stefano Boccaletti

“…We also apply a sequential quadratic programming algorithm to optimize the parameters of our model and validate its accuracy and applicability on real-world data. …”
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Client grouping and time-sharing scheduling for asynchronous federated learning in heterogeneous edge computing environment by Qianpiao MA, Qingmin JIA, Jianchun LIU, Hongli XU, Renchao XIE, Tao HUANG

“…., edge heterogeneity, data Non-IID, and communication resource constraints, a grouping asynchronous federated learning (FedGA) mechanism was proposed.Edge nodes were divided into multiple groups, each of which performed global updated asynchronously with the global model, while edge nodes within a group communicate with the parameter server through time-sharing communication.Theoretical analysis established a quantitative relationship between the convergence bound of FedGA and the data distribution among the groups.A time-sharing scheduling magic mirror method (MMM) was proposed to optimize the completion time of a single round of model updating within a group.Based on both the theoretical analysis for FedGA and MMM, an effective grouping algorithm was designed for minimizing the overall training completion time.Experimental results demonstrate that the proposed FedGA and MMM can reduce model training time by 30.1%～87.4% compared to the existing state-of-the-art methods.…”
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A framework for detecting and predicting highway traffic anomalies via multimodal fusion and heterogeneous graph neural networks. by Shaowei Sun, Mingzhou Liu

“…To address these limitations, we propose a framework based on multimodal deep fusion and heterogeneous graph neural networks (HGNNs), incorporating an Ensemble Contrastive Pessimistic Likelihood Estimation (CPLE) algorithm to optimize performance. The framework integrates static and dynamic traffic data, such as video images, traffic flow, vehicle speed, and tunnel weather conditions. …”
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Computing mutual similarity of 3D human faces in nearly linear time. by Radek Ošlejšek, Petra Urbanová, Jiří Sochor

“…Our solution utilizes properties of facial scan geometry to optimize individual steps. Moreover, the algorithm deals with possible holes and other artifacts in polygonal meshes automatically. …”
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The Role of Misclassification and Carbon Tax Policies in Determining Payment Time and Replenishment Strategies for Imperfect Product Shipments by Chun-Tao Chang, Yao-Ting Tseng

“…Theoretical analysis showed that profit exhibited joint concavity with respect to both payment time and replenishment time. An algorithm was also formulated to derive optimal solutions. …”
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Big Data-Driven 3D Visualization Analysis System for Promoting Regional-Scale Digital Geological Exploration by Yiping Tian, Jiongqi Wu, Genshen Chen, Gang Liu, Xialin Zhang

“…Experimental validation shows the improved CMMN algorithm reduces cloud task completion time by 2.37% while increasing resource utilization by 0.652% compared with conventional methods. …”
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Energy-Efficient User Association Strategy for Hyperdense Heterogeneous Networking in the Fifth Generation Systems by Lei Li, Hao Jin, Zhipeng Yan, Changqing Yang, Yong Wu

“…We focus on the solution of the biconcave framework, and, by exploiting the biconcave structure, a novel iterative algorithm based on dual theory is proposed, where a partially optimal solution can be achieved. …”
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LCDDN-YOLO: Lightweight Cotton Disease Detection in Natural Environment, Based on Improved YOLOv8 by Haoran Feng, Xiqu Chen, Zhaoyan Duan

“…A Focal-EIoU loss function is also integrated to optimize the model’s training process. Experimental results show that compared to YOLOv8, the LCDDN-YOLO model reduces the number of parameters by 12.9% and the floating-point operations (FLOPs) by 9.9%, while precision, mAP@50, and recall improve by 4.6%, 6.5%, and 7.8%, respectively, reaching 89.5%, 85.4%, and 80.2%. …”
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Protein structural domain-disease association prediction based on heterogeneous networks by Jingpu Zhang, Lianping Deng, Lei Deng

“…Small proteins are often found to be composed of only a single domain, while most large proteins consist of multiple domains for achieving various composite cellular functions. …”
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Multi task detection method for operating status of belt conveyor based on DR-YOLOM by Yongan LI, Tengjie CHEN, Hongwei WANG, Zhihao ZHANG

“…Secondly, as the model requires target recognition and segmentation of different types of tasks, an efficient layer aggregation network (RepGFPN) with skip layer connection structure is adopted to optimize the feature fusion part, greatly improving the detection accuracy of the model for different detection tasks while controlling the number of model parameters and inference speed; Finally, to address the detection tasks of three different label shapes, the Inner CIOU loss function is introduced to compensate for the weak generalization ability of the CIoU loss function in different detection tasks. …”
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Wide-Range Variable Cycle Engine Control Based on Deep Reinforcement Learning by Yaoyao Ding, Fengming Wang, Yuanwei Mu, Hongfei Sun

“…To solve this problem, this paper adopts a deep reinforcement learning method based on a deep deterministic policy gradient algorithm, and it applies an action space pruning technique to optimize the controller, which significantly improves the convergence speed of network training. …”
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A mathematical model for hybrid-electric propulsion system for regional propeller-driven aircraft by Giuseppe Grazioso, Mario Di Stasio, Fabrizio Nicolosi, Salvatore Trepiccione

“…A powerplant management algorithm enhances adaptability to varying power demands while ensuring a physically consistent solution. …”
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ApproximateSecret Sharing in Field of Real Numbers by Jiaqi Wan, Ziyue Wang, Yongqiang Yu, Xuehu Yan

“…To address these issues, this paper proposes an innovative algorithm to optimize SSS via type-specific coding for real numbers. …”
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Integrating distributed photovoltaic and energy storage in 5G networks for sustainable IoT applications by Yi Zhong, Yiting Wu, Yi Zheng, Xiaohu Ge

“…This paper explores the integration of distributed photovoltaic (PV) systems and energy storage solutions to optimize energy management in 5G base stations. By utilizing IoT characteristics, we propose a dual-layer modeling algorithm that maximizes carbon efficiency and return on investment while ensuring service quality. …”
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A Hybrid CT-DEWCA-Based Energy-Efficient Routing Protocol for Data and Storage Nodes in Underwater Acoustic Sensor Networks by Imran Khan, Muhammad Rauf, Atif Jamil

“…This research proposes an energy-aware deployment approach and introduces the Controlled Transmission enhanced by hybrid model scheme with Differential Evolution, Whale Optimization, and Chaotic Adaptation (CT-DEWCA) for relay selection. …”
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The Effectiveness of Peyton’s 4-Step Approach to Teach Resuscitation Skills: A Randomized Controlled Clarification Study by Denisa Cenaj, Leonie Schulte-Uentrop, Leonie Fee Laura Kröger, Josephine Küllmei, Jan-Marcus Haus, Parisa Moll-Khosrawi

“…While the method shows limited benefit for teaching discrete tactile skills in earlier stages, its strategic inclusion in later phases can optimize curriculum design by aligning advanced teaching methods with learners’ developmental needs. …”
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FEXGBIDS: Federated XGBoost-Based Intrusion Detection System for In-Vehicle Network by Jie Li, Yuanyuan Song, Ming-Gang Zheng, Shuo Zhang, Han Liang

“…Additionally, we employ BLS aggregate signatures to achieve efficient and verifiable parameter aggregation, and leverage the DDSketch distributed quantile estimation algorithm to optimize the feature bucketing process. …”
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On-Board Content Caching With Dynamic Cache Reconfiguration in Multi-Layer Satellite Edge Networks by Haftay Gebreslasie Abreha, Ilora Maity, Houcine Chougrani, Christos Politis, Symeon Chatzinotas

“…To address these challenges, in this paper, we propose an on-board dynamic cache reconfiguration strategy that maximizes the cache hit rate while minimizing reconfiguration overhead. We design a proximity-based content popularity model and an Age of Information (AoI)-aware caching strategy to optimize on-board satellite resources, enhancing the cache hit rate and ensuring content freshness. …”
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