Dual-Closed-Loop Control System for Polysilicon Reduction Furnace Power Supply Based on Hysteresis PID and Predictive Control by Shihao Li, Tiejun Zeng, Shan Jian, Guiping Cui, Ziwen Che, Genghong Lin, Zeyu Yan

“…Meanwhile, the outer loop employs a hybrid MFAC-based improved PID algorithm to optimize the temperature tracking performance, achieving precise temperature control even in the presence of system uncertainties. …”
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Demonstration of an Advanced Rectification Strategy on a Linear Generator for Better Electricity Quality by Boru Jia, Liutao Sun, Yidi Wei, Huihua Feng, Jian Li, Qiming Lei, Jiazheng Miao, Zhengxing Zuo

“…In terms of control strategy, a model predictive sliding mode compound control algorithm is introduced to optimize traditional PWM rectification. …”
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A Novel Crowdsourcing-Assisted 5G Wireless Signal Ranging Technique in MEC Architecture by Rui Lu, Lei Shi, Yinlong Liu, Zhongkai Dang

“…This study designs a progressive solution by (1) building a crowdsourced data collection network, using mobile terminals equipped with GPS technology to automatically collect device signal features, replacing inefficient manual drive tests; (2) developing a progressive signal update algorithm that integrates real-time crowdsourced data and historical signals to optimize the signal fingerprint database in dynamic environments; (3) establishing an edge service architecture to offload signal matching and trajectory estimation tasks to MEC nodes, using lightweight computing engines to reduce the load on the core network. …”
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Prediction of Power System Ramping Demand Using Meteorological Features by Kuan Lu, Song Gao, Jun Li, Kang Chen, Chunhao Yu

“…First, an adaptive trend identification algorithm is proposed to extract key features of upward and downward ramps, including magnitude and duration. …”
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Toward a conceptual model to improve the user experience of a sustainable and secure intelligent transport system by Abdullah Alsaleh

“…By leveraging cloud computing and vehicular networks, intelligent transportation solutions optimize traffic flow, improve emergency response systems, and forecast potential collisions, contributing to safer and more efficient roads. …”
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Nonlinear Stability Analysis of Shallow-Buried Bias Tunnel Based on Failure Mode Improvement by Wei Luo, Gequan Xiao, Zhi Tao, Jingyu Chen, Xi Lu, Haifeng Wang

“…Based on the improvement of the Karl Terzaghi failure mode for calculating the surrounding rock pressure of loose rock mass, combined with the upper bound theorem of limit analysis, the formula for calculating the surrounding rock pressure of shallow-buried tunnel in a slope area under a nonlinear failure criterion is derived. The SQP algorithm in MATLAB (R2022a) software was used to optimize the solution, and the influence of slope top load, buried depth ratio, cohesion, and axial tensile stress on the surrounding rock pressure and the failure mode of shallow-buried tunnel was analyzed through examples. …”
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Occlusion mapping reveals the impact of flight and sensing parameters on vertical forest structure exploration with cost-effective UAV based laser scanning by Matthias Gassilloud, Barbara Koch, Anna Göritz

“…Using sensor position reconstruction and a ray tracing algorithm to quantify occlusion, we found that: (1) A larger sensor tilt angle up to 15° increased total occlusion, enhancing exploration in the upper canopy, while decreasing it below due to reduced canopy penetration. (2) Flying multiple azimuthal directions with a linear scanning mode reduced vertical occlusion by up to 15.0% due to improved coverage from diverse perspectives. (3) Lissajous scanning patterns resulted in 10.1% less vertical occlusion compared to linear patterns, underscoring the importance of additional viewing angles. …”
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ASHM-YOLOv9: A Detection Model for Strawberry in Greenhouses at Multiple Stages by Yan Mo, Shaowei Bai, Wei Chen

“…Haar wavelet downsampling (HWD) was applied to optimize the Adaptive Downsampling module (Adown) of the initial model, thereby increasing the precision of object detection. …”
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Development and validation of machine learning models to predict unplanned hospitalizations of patients with diabetes within the next 12 months by A. E. Andreychenko, A. D. Ermak, D. V. Gavrilov, R. E. Novitskiy, A. V. Gusev

“…The creation and inference of a machine learning model for predicting hospitalizations of patients with DM to an inpatient medical facility will make it possible to personalize the provision of medical care and optimize the load on the entire healthcare system.AIM: Development and validation of models for predicting unplanned hospitalizations of patients with diabetes due to the disease itself and its complications using machine learning algorithms and data from real clinical practice.MATERIALS AND METHODS: 170,141 depersonalized electronic health records of 23,742 diabetic patients were included in the study. …”
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Application of Improved BQGA in Robot Kinematics Inverse Solution by Xiaoqing Lv, Ming Zhao

“…In addition, the improved algorithm further completes the anti-degradation mechanism, which maintains the diversity of the population while preserving the dominant gene to the maximum extent, so that the algorithm is not easy to fall into the local extremum and finally approaches the global optimal solution. …”
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SpecPCM: A Low-Power PCM-Based In-Memory Computing Accelerator for Full-Stack Mass Spectrometry Analysis by Keming Fan, Ashkan Moradifirouzabadi, Xiangjin Wu, Zheyu Li, Flavio Ponzina, Anton Persson, Eric Pop, Tajana Rosing, Mingu Kang

“…We further optimize multilevel PCM devices for different tasks by using different materials. …”
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Progressive Pruning of Light Dehaze Networks for Static Scenes by Byeongseon Park, Heekwon Lee, Yong-Kab Kim, Sungkwan Youm

“…Our progressive pruning algorithm, targeting a specific PSNR(Peak Signal-to-Noise Ratio) threshold, achieved optimal results at a certain pruning ratio, significantly reducing the number of channels in the target layer while maintaining PSNR above the threshold and preserving good structural similarity, before automatically stopping when performance dropped below the target. …”
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Dynamic spectrum allocation based on one-band multi-winner auction by Wen-zhu ZHANG, Ling-yun WANG

“…In order to improve the effectiveness of traditional auction in DSA (dynamic spectrum allocation) issue in cognitive radio networks,a new dynamic spectrum allocation algorithm based on one-band multi-winner auction was proposed.Compared with the original greedy algorithm,the new algorithm can achieve better spectrum allocation solutions with lower computational complexity by introducing the multiple greedy strategy.It increases the seller's revenue by improving the VCG (vickery-clarke-groves) mechanism,while retaining the dominant strategy incentive compatible property.In addition,it suppresses the occurrence of collusion effectively.Simulation results show that the algorithm proposed can get spectrum allocation efficiency close to the optimal solution and increase the auction revenue significantly.…”
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SCL-YOLOv11: A Lightweight Object Detection Network for Low-Illumination Environments by Shulong Zhuo, Hao Bai, Lifeng Jiang, Xiaojian Zhou, Xu Duan, Yiqun Ma, Zihan Zhou

“…Experimental results on the ExDark dataset demonstrate that the proposed algorithm achieves 67.6% mAP@0.5 and 42.4% mAP@0.5:0.95, while reducing parameter count by 38.5% and computational cost by 25.4%. …”
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Solution of methodological problems in selection of methods of euthrophic water bodies’ rehabilitation by Aleksandr N. Popov, Valery F. Mukhutdinov

“…However, at present in Russia there is no single algorithm and method for pre-design engineering/ecological surveying, no recommendations on optimal choice of rehabilitation methods for a specific water body with taking into account the whole integrity of impact and connections of aquatic, ground, and aerial ecosystems, as well as anthropogenesis. …”

基于萤火虫神经网络的轴承性能退化程度评估 by 刘永前, 徐强, 田德, 龙泉

“…Precise assessment of bearing performance degradation is the foundation and key of predictive maintenance for rotating machinery,and also a new research area nowadays.An optimized BP neural network based on glowworm swarm optimization algorithm is proposed and applied for the first time in the performance degradation assessment of bearings.The glowworm swarm optimization algorithm is applied to obtain the initial weights and thresholds of BP neural network,while power spectral entropy,wavelet entropy,box dimension,correlation dimension,kurtosis and skewness are selected as the fault features.Experiments show that the glowworm swarm optimization algorithm has improved the prediction accuracy of network and the proposed method can precisely assess the performance degradation of rolling bearings,the effectiveness and accuracy of the proposed method in engineering application is validated.…”
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Quantum natural stochastic pairwise coordinate descent by Mohammad Aamir Sohail, Mohsen Heidari, S. Sandeep Pradhan

“…We develop a quantum optimization algorithm that leverages the geometry of the state space via this estimator while avoiding full-state tomography, as in conventional techniques. …”
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Adaptive Path Planning for Multi-Drone Systems Based on SFS, DPF, and Learning Based Refinement by Srwa Ahmed Mustafa, Amin Salih Kakshar

“…The results show that ASF creates routes requiring 12.5% less travel distance and 18% decreased energy consumption, resulting in a 20% shorter operational time than existing drone control methods. The updated algorithm provides optimal coordination capabilities for drones while managing their navigation system, making it suitable for complex, dynamic drone flight operations. …”
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HGCS—A Multiplex Transmission Method for Wide-Area Unmanned Aerial Vehicle Cluster Inspection Data in Hybrid Networked Transmission Lines by Ruchao Liao, Xionggang Li, Jinchao Guo, Wenxing Sun, Guoqiang Li

“…To address these challenges, an effective optimization algorithm is required to balance the algorithmic performance while considering the fairness and QoS parameters. …”
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Efficient Orchestration of Distributed Workloads in Multi-Region Kubernetes Cluster by Radoslav Furnadzhiev, Mitko Shopov, Nikolay Kakanakov

“…Experiments cover multiple cluster configurations, varying in node count, region count, and inter-region latencies, with performance metrics recorded for scheduler efficiency, inter-zone communication impact, and execution time across different optimization algorithms. The obtained results indicate that network-aware scheduling approaches significantly improve latency-aware placement decisions, achieving lower inter-region communication delays while maintaining resource efficiency.…”
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