Variation Characteristics of Mass-Loss Rate in Dynamic Seepage System of the Broken Rocks by Luzhen Wang, Hailing Kong

“…In this study, the seepage tests of the broken mudstone were carried out using the patented pumping station seepage method, and the time-varying function of the mass-loss rate was generalized. Then, the optimal coefficients in the function of mass-loss rate were computed using the genetic algorithm. …”
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A CNN-Based Approach for Classical Music Recognition and Style Emotion Classification by Yawen Shi

“…For searching for optimal performance of the model, a novel optimization algorithm also be proposed to find optimal hyperparameters of loss function. …”
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Effects of acute weight loss on serum mineral homeostasis in elite male judoka by Burcu Yenturk, Mihrac Koroglu, Nuri Muhammet Celik, Cuneyt Sensoy, Fıkret Soyer

“…Maintaining optimal serum mineral levels is critical for both physiological function and athletic performance. …”
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Alloimmune Causes of Recurrent Pregnancy Loss: Cellular Mechanisms and Overview of Therapeutic Approaches by Cristina Uța, Alexandru Tîrziu, Elena-Larisa Zimbru, Răzvan-Ionuț Zimbru, Marius Georgescu, Laura Haidar, Carmen Panaitescu

“…Recurrent pregnancy loss (RPL) is a complex early pregnancy complication affecting 1–2% of couples and is often linked to immune dysfunction. …”
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The effect of home-based behavioural weight loss combined with pelvic floor muscle training in women seeking weight loss combined with stress urinary incontinence: protocol for a r... by Wei Chen, ZhiJing Sun, Zhao Tian, Xiuqi Wang, Linru Fu, Zhe Du, Tangdi Lin

“…The secondary outcomes include weight loss effectiveness, pelvic muscle strength, pelvic floor ultrasound, three-dimensional body posture, adherence to the intervention and questionnaires for symptoms of pelvic organ prolapse, quality of life and sexual function.Ethics and dissemination This study has been approved by the Peking Union Medical College Hospital ethics committee (K5504). …”
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Computational Aspects of <i>L</i>₀ Linking in the Rasch Model by Alexander Robitzsch

“…The <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>L</mi><mn>0</mn></msub></semantics></math></inline-formula> linking approach replaces the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>L</mi><mn>2</mn></msub></semantics></math></inline-formula> loss function in mean–mean linking under the Rasch model with the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>L</mi><mn>0</mn></msub></semantics></math></inline-formula> loss function. …”
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A Self-Supervised Adversarial Deblurring Face Recognition Network for Edge Devices by Hanwen Zhang, Myun Kim, Baitong Li, Yanping Lu

“…The model employs a generative adversarial network (GAN) as the core algorithm, optimizing its generation and recognition modules by decomposing the global loss function and incorporating a feature pyramid, thereby solving the balance challenge in GAN training. …”
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LSOD-YOLOv8: Enhancing YOLOv8n with New Detection Head and Lightweight Module for Efficient Cigarette Detection by Yijie Huang, Huimin Ouyang, Xiaodong Miao

“…Finally, we propose a new loss function, WIMIoU (Weighted Intersection over Union with Inner, Multi-scale, and Proposal-aware Optimization), by combining the ideas of WiseIoU (Wise Intersection over Union), InnerIoU (Inner Intersection over Union), and MPDIoU (Mean Pairwise Distance Intersection over Union), resulting in a significant accuracy improvement without any loss in performance. …”
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Exploring novel molecular mechanisms underlying recurrent pregnancy loss in decidual tissues by Hui Ding, Yajie Gao, Yuan Gao, Yulu Chen, Ruimin Liu, Caili Wang, Yuqing Gao

“…Three RPL decidual tissue transcriptomic datasets (GSE113790, GSE161969, and GSE178535) were integrated for differential expression, weighted gene co-expression network analysis (WGCNA), and functional enrichment analyses. Machine learning (LASSO, SVM-RFE, RF) identified optimal feature genes, which were validated via real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC). …”
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Otoacoustic Emissions Testing to Identify Hearing Loss in the ICU: A Feasibility Study by Ramya Kaushik, MD, Nicholas Reed, AuD, PhD, Lauren E. Ferrante, MD, MHS

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LSTM-IOT (LSTM-based IoT) untuk Mengatasi Kehilangan Data Akibat Kegagalan Koneksi by Yosia Adi Susetyo, Hanna Arini Parhusip, Suryasatriya Trihandaru, Bambang Susanto

“…This architecture has been optimized through experiments using different types of optimizers, such as Adam, RMSprop, AdaGrad, SGD, Nadam, and Adadelta. …”
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Corona-Virus Pandemic: Time of Collaboration in Business by A. A. Nikonorova, A. G. Luchkin, V. A. Melnikov

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Benchmarking reinforcement learning and accurate modeling of ground source heat pump systems: Intelligent strategy using spiking recurrent neural network combined with spider WASP... by Sana Qaiyum, Kashif Irshad, Mohamed E. Zayed, Salem Algarni, Talal Alqahtani, Asif Irshad Khan

“…Furthermore, the proposed SWO-SRNN was trained using the selected features to predict the ground temperature and Coefficient of Performance (COP), which enables to make appropriate actions to optimize the functioning of GSHP. Finally, statistical analysis was used to evaluate the robustness of the developed SWO-SRNN models. …”
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Experimental Evaluation of the Loss Coefficient of Insect-Proof Agro-Textiles and Application to Wind Loads by Sergio Castellano, Giuseppe Starace

“…The knowledge of this relationship would make it possible to optimize the size of the holes in order to maintain the anti-insect function with the increase in air velocity. …”
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Autonomous Obstacle Avoidance with Improved Deep Reinforcement Learning Based on Dynamic Huber Loss by Xiaoming Xu, Xian Li, Na Chen, Dongjie Zhao, Chunmei Chen

“…To address these challenges, we propose an enhanced DRL framework that leverages a Dynamic Huber loss function tailored for UAV autonomous obstacle avoidance. …”
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Modeling eye gaze velocity trajectories using GANs with spectral loss for enhanced fidelity by Shailendra Bhandari, Pedro Lencastre, Rujeena Mathema, Alexander Szorkovszky, Anis Yazidi, Pedro G. Lind

“…Our findings reveal that the LSTM-CNN architecture trained with this new loss function exhibits the closest alignment to the real data distribution, effectively capturing both the distribution tails and the intricate temporal dependencies. …”
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Wafer-Scale Experimental Determination of Coupling and Loss for Photonic Integrated Circuit Design Optimisation by Daniel Schmid, René Eisermann, Anna Peczek, Georg Winzer, Lars Zimmermann, Stephan Krenek

“…Third, we demonstrate how curve fitting of loss and coupling coefficients as a function of the gaps can be used to estimate the optimal gap that realizes critical coupling with a significantly reduced number of manufactured test structures needed to find optimal design parameters.…”
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Wireless routeing scheme for UAV-assisted access networks based on the link path loss by Beza Negash Getu, Ali Alnoman

“…The communication route between the sender and receiver is established with awareness of the link path loss between the cooperating UAV relay nodes. Then, Dijkstra’s shortest path algorithm is used to find the optimal route that has the minimum total path loss among all other possible routes. …”
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Intelligent Dynamic Trajectory Planning of UAVs: Addressing Unknown Environments and Intermittent Target Loss by Zhengpeng Yang, Suyu Yan, Chao Ming, Xiaoming Wang

“…Additionally, considering future practical applications, the predictor and planner adopt a parallel optimization and correction algorithm structure to ensure planning accuracy and computational efficiency. …”
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Contrastive Learning with Image Deformation and Refined NT-Xent Loss for Urban Morphology Discovery by Chunliang Hua, Daijun Chen, Mengyuan Niu, Lizhong Gao, Junyan Yang, Qiao Wang

“…The data analysis demonstrated the effectiveness of our image deformation pipeline and loss function, and the sociological analysis illustrated the unique urban functions of these urban types.…”
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