Digital-twin driven alignment control method for marine shafting with air spring vibration isolation system by Song Liu, Liang Shi, Wei Xu, ZeChao Hu

“…To obtain the optimal air spring pressures, the genetic algorithm is introduced to solve the optimization problem, fully exploiting its global search capacity. …”
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Energy-Efficient Scheduling for Resilient Container-Supply Hybrid Flow Shops Under Transportation Constraints and Stochastic Arrivals by Huaixia Shi, Huaqiang Si, Jiyun Qin

“…To address the TDEHFSP model, the study proposes a Q-learning-based multi-swarm collaborative optimization algorithm (Q-MGCOA). The algorithm integrates a time gap left-shift scheduling strategy with a machine on–off control mechanism to construct an energy-saving optimization framework. …”
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Physical Information Neural Network-Based Seepage Behavior Analysis of Earth and Rock Dams by XUE binghan, HUANG zhenhua, LEI Jianwei, FANG Hongyuan

“…Impermeable boundary conditions are imposed on these initial free-surface nodes, while other boundaries are assigned conditions according to the physical model. …”
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Eecs-fl: energy-efficient client selection for federated learning in AIoT by Yiyang Zhang, Yiming Luo, Tao Yang, Xiaofeng Wu, Bo Hu

“…We formulate the client selection problem as a multi-dimensional knapsack problem (MKP) and solve it using dynamic programming to maximize energy efficiency while maintaining fast convergence. Experimental results show that incorporating WPT leads to a reduction in unit energy consumption by over 24.54%; while, the proposed algorithm achieves a reduction of over 15.31% compared to random selection. …”
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YOLO-SMUG: An Efficient and Lightweight Infrared Object Detection Model for Unmanned Aerial Vehicles by Xinzhe Luo, Xiaogang Zhu

“…To tackle the high computational demands and accuracy limitations in UAV-based infrared object detection, this study proposes YOLO-SMUG, a lightweight detection algorithm optimized for small object identification. …”
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Machine learning for defect condition rating of wall wooden columns in ancient buildings by Yufeng Li, Wu Ouyang, Zhenbo Xin, Houjiang Zhang, Shuqi Sun, Dian Zhang, Wenbo Zhang

“…The RBF neural network model achieved the highest accuracy (94.57 %) on the feature fusion dataset, while Grey Wolf Optimizer (GWO) optimization further improved accuracy to 96.74 %. …”
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Multi-UAV assisted air-to-ground data collection for ground sensors with unknown positions by Cheng Yiran, Dong Yangrui

“…Simulation results reveal that, compared to the existing algorithms, the proposed approach adeptly tackles the data collection challenge when sensor positions remain unknown while significantly enhancing task execution efficiency across diverse environmental conditions. …”
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Modified Diagnostic Criteria Tools for Familial Hypercholesterolemia without the Requirement for Clinical Genetic Testing: Rationale and Design of the MOOCS Adaptive Clinical Trial by Satyanarayana Upadhyayula

“…Various available FH diagnostic tools are grouped together in the FH diagnostic criteria tool universal algorithm. Background: The standard diagnostic criteria tools for FH require GT. …”
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Overheating Defect Detection of Composite Insulator Based on Mask R-CNN by Yi GAO, Lianfang TIAN, Qiliang DU

“…On the whole, the accuracy rate of 93% is achieved in defect detection of test sets.…”
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Software pipeline for predicting and analyzing the structure of the receptor–ligand by A.S. Kozlova, A.R. Mukhametgalieva, A.N. Fattakhova, N.I. Akberova

“…Possible interactions of the receptor–ligand complex are studied based on certain parameters: the energy of the affinity of the ligand for the receptor; the length and energy of the bond between the receptor and the ligand, both in the whole complex and between individual atoms. All characteristics can be automatically calculated by default under the specified optimal parameters. …”
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Advanced machine learning techniques reveal multidimensional EEG abnormalities in children with ADHD: a framework for automatic diagnosis by Ying Mao, Ying Mao, Xuchen Qi, Xuchen Qi, Xuchen Qi, Lingyan He, Shan Wang, Zhaowei Wang, Fang Wang, Fang Wang

“…Then, four widely-employed machine learning algorithms (including random forest (RF), XGBoost, CatBoost, and LightGBM) were used for classification calculations, and the SHAP algorithm was then used to assess the importance of the contributing features to interpret the model’s decision process.ResultsThe results showed that the highest classification accuracy of 99.58% for pediatric ADHD detection was obtained with the CatBoost model based on the optimal feature subset of 206 features (PSD/FuzEn/MI = 53/5/148). …”
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Finding a suitable chest x-ray image size for the process of Machine learning to build a model for predicting Pneumonia by Kriengsak Yothapakdee, Yosawaj Pugtao, Sarawoot Charoenkhun, Tanunchai Boonnuk, Kreangsak Tamee

“…The neural network algorithm achieved an accuracy rate of 87.00% across different image sizes. …”
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Adaptive Anomaly Detection in Network Flows With Low-Rank Tensor Decompositions and Deep Unrolling by Lukas Schynol, Marius Pesavento

“…To optimize the deep network weights for detection performance, we employ a homotopy optimization approach based on an efficient approximation of the area under the receiver operating characteristic curve. …”
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Fault reconfiguration control strategy of islanded marine ranching power supply system based on deep reinforcement learning by Yichun Wang, Bo Zhang, Rongjie Wang, Jiang Desong, Yabo Cui, Zhouyang Sun, Hao Liu

“…Finally, through analysis of fault reconstruction cases in different operating conditions of the marine ranching power system, it is demonstrated that this proposed algorithm can provide optimal reconstruction strategies within as short as 70 ms while achieving objectives such as maximum load recovery, minimum switching times, and minimum network losses. …”
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Development of Adaptive Testing Method Based on Neurotechnologies by E. V. Chumakova, D. G. Korneev, M. S. Gasparian

“…SGD, Adam, NAdam and RMSprop implemented in Keras were compared as optimizers to achieve faster convergence. Adam showed the best results in terms of accuracy, while the MSE loss function (mean square error) was used together with the optimizer. …”
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IMPROVING EFFICIENCY OF RADIO MAINTENANCE TO ENSURE SAFETY by V. E. Emelyanov, I. A. Polotnyanschicov

“…The Algorithm of solving the task of optimal control is given.…”
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MPDP -medoids: Multiple partition differential privacy preserving -medoids clustering for data publishing in the Internet of Medical Things by Zekun Zhang, Tongtong Wu, Xiaoting Sun, Jiguo Yu

“…Based on the traditional k -medoids clustering, multiple partition differential privacy k -medoids clustering algorithm optimizes the randomness of selecting initial center points and adds Laplace noise to the clustering process to improve data availability while protecting user’s privacy information. …”
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Design of artwork resource management system based on block classification coding and bit plane rearrangement by Xiaomeng Xia

“…By employing refined block classification coding (RS-BCC) and optimized bit plane rearrangement (BPR) techniques, this algorithm significantly enhances the watermark embedding capacity and robustness while ensuring image quality. …”
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Low latency Montgomery multiplier for cryptographic applications by khalid javeed, Muhammad Huzaifa, Safiullah Khan, Atif Raza Jafri

“…The proposed Montgomery multiplier is based on school-book multiplier, Karatsuba-Ofman algorithm and fast adders techniques. The Karatsuba-Ofman algorithm and school-book multiplier recommends cutting down the operands into smaller chunks while adders facilitate fast addition for large size operands. …”
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Sum Rate Maximization for Active RIS MISO Systems Based on DRL by Zhipeng Xi, Jianbo Ji

“…Additionally, it is observed that proper parameter settings significantly enhance the performance of the proposed algorithm. Finally, the algorithm can allocate suitable power to the active RIS while maintaining a constant total power, thereby optimizing the system performance.…”
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