Design and Analysis of Parallel Adjusting Equipment of Vertical Drilling by Zhou Bin, Zeng Yishan, Zi Bin

“…Focusing on the current limited vertical adjustment technique of large-scale drillings,a 6-DOF parallel adjustment equipment with 12 inputs is designed for the working condition of vertical drilling.The equipment mechanism consists of 6branched chains with redundancy which are symmetrical in structure.Each of the chains is composed by a compound of rotate joint and a compound of spherical joint,while the two pairs are connected by two prismatic pairs.The modal analysis is carried out on the body which is based on ANSYS software,first six order frequency distribution and modal vibration mode,and along the X、Y、Zdirection of the displacement frequency response about the moving platform are got.The analysis consequence shows that the most sensitive of external forces to the moving platform is 46 Hz frequency.Otherwise,the working space of the 6-DOF platform is obtained by using the 3-D searching algorithm.The results have significant meanings in the further research on the correlation between the parameters and the whole mechanism,as well as the optimization of the parameter.…”
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Saliency Detection via Fusing Color Contrast and Hash Fingerprint by Yin Lv, Xuanrui Zhang, Yong Wang

“…Besides, another saliency map that enhances the salient region while restraining the background is also generated through hash fingerprint matching. …”
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Robust Mainlobe Interference Suppression Based on Joint Oblique Projection for Dual Polarization Conformal Array by Chao Liu, Xiaoyuan Zhang, Junjie Qian, Lei Zhang

“…In this paper, a robust mainlobe interference suppression algorithm is proposed in a space-polarization joint domain based on a dual-polarized conformal array. …”
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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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Task offloading and resource allocation for blockchain‐enabled mobile edge computing by Renbin Fang, Peng Lin, Yize Liu, Yan Liu

“…To manage the allocation of computing resources between task offloading and blockchain consensus, the task offloading and resource allocation are formulated as a joint optimization problem. The aim of the problem is to minimize the energy consumption of UTs while guaranteeing the delay requirement. …”
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Distance Estimation with a Stereo Camera and Accuracy Determination by Arnold Zaremba, Szymon Nitkiewicz

“…These results provide valuable information on the capabilities and limitations of the measurement system used, while pointing out directions for its further optimization.…”
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Neural Network-Based Imitation Learning for Approximating Stochastic Battery Management Systems by Andrea Pozzi, Alessandro Incremona, Daniele Toti

“…Traditional predictive control methods are limited by their reliance on precise models, which are often hindered by uncertainties in battery parameters due to aging, production variability, and operational conditions. While stochastic predictive control policies can address these uncertainties by incorporating them directly into the optimization process, they typically introduce considerable computational complexity. …”
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A Simulation Based Metaheuristics for Capacitated Vehicle Routing Problem by Tamara Latifah Jasmine, Heru Purboyo Hidayat Putro, Niken Prilandita, Gatot Yudoko

“…The methodology utilizes a simheuristics approach, integrating a Genetic Algorithm (GA) to determine optimal routing solutions, while employing Discrete Event Simulation (DES) to incorporate key economic, environmental, and social variables. …”
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IRS-Assisted Wireless Sensor Networks With Hybrid TDMA-NOMA by Haitham Al-Obiedollah, Haythem Bany Salameh, Kanapathippillai Cumanan

“…To overcome these challenges, an iterative algorithm is proposed to solve the formulated optimization problem. …”
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Multi-Modal Federated Learning Over Cell-Free Massive MIMO Systems for Activity Recognition by Seyed Mohammad Sheikholeslami, Pai Chet Ng, Jamshid Abouei, Konstantinos N. Plataniotis

“…Additionally, we employ a modified Particle Swarm Optimization (PSO) algorithm for efficient resource allocation. …”
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SafeTrack: Secure Tracking Protocol for Mobile Sensor Nodes in Unstable Wireless Sensor Networks by Ali Adnan Al-Khazraji, Fatimah Abdulridha Rashid

“…It also incorporates an Adaptive Routing Algorithm (ARA) and an Energy Optimization Module (EOM) to enable both efficient resource utilization and resilience to changes in dynamic network conditions. …”
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Factor Graph-Based Planning as Inference for Autonomous Vehicle Racing by Salman Bari, Xiagong Wang, Ahmad Schoha Haidari, Dirk Wollherr

“…By leveraging the duality between optimization and inference, a fast solution to the maximum a posteriori estimation of the factor graph is obtained via least-squares optimization. …”
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Retracted: Computer Medical Image Segmentation Based on Neural Network by Xiaopeng Wang, Lei Gu, Zhongyi Wang

“…This article proposes an image segmentation method based on an optimized cellular neural network. This method introduces a non-linear template and data quantization on the basis of a basic network model, which greatly reduces the computational complexity while maintaining the accuracy of image segmentation. …”
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Deep Reinforcement Learning for Dynamic Pricing and Ordering Policies in Perishable Inventory Management by Yusuke Nomura, Ziang Liu, Tatsushi Nishi

“…To tackle this challenge, we propose eliminating irrational actions in dynamic programming without sacrificing optimality. To solve this problem more efficiently, we also implement a deep reinforcement learning algorithm, proximal policy optimization, to solve this problem. …”
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A Deformation Reconstruction Strategy for Integrated Truss Structures Subjected to Thermal–Mechanical Load by Zexing Yu, Xiaofei Ma, Jialong Zhu, Dayu Zhang, Yonggang Xue, Pengfei Huang, Yichen Li, Hao Li

“…The proposed approach utilizes Ko displacement theory as the core algorithm, while the least squares optimization method is employed to determine the integration with unknown initial values during the reconstruction process. …”
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Research on Adaptive Identification Technology for Rolling Bearing Performance Degradation Based on Vibration–Temperature Fusion by Zhenghui Li, Lixia Ying, Liwei Zhan, Shi Zhuo, Hui Li, Xiaofeng Bai

“…Finally, a dual-criteria adaptive bottom-up merging algorithm (DC-ABUM) was proposed, which achieves bearing life-stage identification through error threshold constraints and the adaptive optimization of segmentation quantities. …”
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MAOOA‐Residual‐Attention‐BiConvLSTM: An Automated Deep Learning Framework for Global TEC Map Prediction by Haoran Wang, Haijun Liu, Jing Yuan, Huijun Le, Weifeng Shan, Liangchao Li

“…It also includes an optimization algorithm, MAOOA, for optimizing the hyper‐parameters of the model. …”
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A Nonlinear Compensation Method for Enhancing the Detection Accuracy of Weak Targets in FMCW Radar by Bo Wang, Tao Lai, Qingsong Wang, Haifeng Huang

“…Parameter estimation is refined using the Adaptive Moment Estimation (ADAM) algorithm and Limited-Memory Broyden–Fletcher–Goldfarb–Shanno (LBFGS) optimization. …”
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A Framework for Synergy Measurement Between Transportation and Production–Living–Ecological Space Using Volume-to-Capacity Ratio, Accessibility, and Coordination by Xiaoyi Ma, Mingmin Liu, Jingru Huang, Ruihua Hu, Hongjie He

“…By introducing an improved accessibility evaluation model and developing a coordination measurement algorithm, a three-dimensional evaluation mechanism covering development potential assessment, service efficiency diagnosis, and resource allocation optimization is established. …”
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Charging Station Management Strategy for Returns Maximization via Improved TD3 Deep Reinforcement Learning by Hengjie Li, Jianghao Zhu, Yun Zhou, Qi Feng, Donghan Feng

“…Also, we use marginalised importance sampling to calculate the Q-return function for TD3, which ensures that the constructed strategies are more likely to learn high-value experiences while having higher robustness. It is shown in numerical experiments that the charging station management strategy (CSMS) based on the modified TD3 obtains the fastest convergence speed and the highest robustness and achieves the largest operational returns compared to the CSMS constructed using deep deterministic policy gradient (DDPG), actor-critic using Kronecker-factored trust region (ACKTR), trust region policy optimization (TRPO), proximal policy optimization (PPO), soft actor-critic (SAC), and the original TD3.…”
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