Comparative Analysis of Deep Learning Models for Intrusion Detection in IoT Networks by Abdullah Waqas, Sultan Daud Khan, Zaib Ullah, Mohib Ullah, Habib Ullah

“…Each model was assessed under balanced and imbalanced dataset configurations and evaluated using three loss functions (cross-entropy, focal loss, and dual focal loss). …”
Get full text

PDGrad: Guiding Diffusion Model for Reference-Based Blind Face Restoration with Pivot Direction Gradient Guidance by Geon Min, Tae Bok Lee, Yong Seok Heo

“…To this end, we first define the loss function based on both low-level and high-level features. …”
Get full text

Distributed quantile regression over sensor networks via the primal–dual hybrid gradient algorithm by Zheng Qin, Zhaoting Liu

“…QR solves a non-smooth optimization problem characterized by a piecewise linear loss function, commonly known as the check function. …”
Get full text

Knowledge-Based Deep Learning for Time-Efficient Inverse Dynamics by Shuhao Ma, Yu Cao, Ian D. Robertson, Chaoyang Shi, Jindong Liu, Zhi-Qiang Zhang

“…Prior physical knowledge from forward dynamics and pre-selected inverse dynamics based physiological criteria are integrated into the loss function to guide the training of neural networks. …”
Get full text

Forecasting Stock Market Volatility Using Housing Market Indicators: A Reinforcement Learning-Based Feature Selection Approach by Pourya Zareeihemat, Samira Mohamadi, Jamal Valipour, Seyed Vahid Moravvej

“…Current EWS methods often face significant hurdles, including model generalization, feature selection, and hyperparameter optimization challenges. To directly address these issues, our innovative approach utilizes a spatial attention-based Transductive Long Short-Term Memory (TLSTM) model combined with a Reinforcement Learning (RL) strategy, which is further enhanced by a novel scope loss function for refined feature selection and an Artificial Bee Colony (ABC) algorithm for hyperparameter optimization. …”
Get full text

Comparison of Kolmogorov–Arnold Networks and Multi-Layer Perceptron for modelling and optimisation analysis of energy systems by Talha Ansar, Waqar Muhammad Ashraf

“…In this regard, first, we modify the loss function of both KAN and MLP algorithms and embed Pearson Correlation Coefficient (PCC). …”
Get full text

A Joint Knowledge Extraction Model for Tobacco Pest and Disease Prevention Based on BERT+BA+CASREL by Kehan Liu, Feng Zhang, Qiulan Wu, Xiang Sun, Huarui Wu, Ziruo Sun

“…The CASREL module, as the core component of the framework, employs a cascade binary tagging approach to achieve joint extraction of entities and relations, effectively improving the precision of complex relation recognition and end-to-end optimization. Additionally, the GHM loss function is adopted to replace the traditional cross-entropy loss function, alleviating the data imbalance issue. …”
Get full text

Uniform Quantization for Multi-Antenna Amplify–Quantize–Forward Relay by Gangsan Jeong, Xianglan Jin

“…Furthermore, we propose a USL method with Monte Carlo (USL-MC), leveraging an approximated loss function to address the heightened complexity observed in multi-antenna systems. …”
Get full text

Low power energy balanced clustering routing scheme based on improved SSA and Multi-Hop transmission in IoT by Rui Wang, Xiaoling Guo, Xinghua Sun, Jie Yang

“…Firstly, the sparrow search algorithm is improved by adding adaptive sine function and Cauchy random number to raise the search capability of the discoverer; The standard normal distribution random number is used to enhance the vigilant escape from the limit of local optimal value. …”
Get full text

Seven-Level Soft Charging Switched-Capacitor Multilevel Inverter by Mehmet Memis, Murat Karakilic

“…The study shows that SC-MLI is optimized as a function of low component count, high efficiency and low cost. …”
Get full text

Application of a Dual-Stream Network Collaboratively Based on Wavelet and Spatial-Channel Convolution in the Inpainting of Blank Strips in Marine Electrical Imaging Logging Images:... by Guilan Lin, Sinan Fang, Manxin Li, Hongtao Wu, Chenxi Xue, Zeyu Zhang

“…Combined with the spatial channel convolution (SCConv) to enhance the feature fusion module, the cross-modal interaction between texture and structural features is optimized through a dynamic gating mechanism. Furthermore, a multi-objective loss function is introduced to constrain the semantic coherence and visual authenticity of image reconstruction. …”
Get full text

Protocol for adaptive laboratory evolution of S. cerevisiae by PEG/LiAc transformation and sequencing by Bei Jiang, Chuyao Xiao, Li Liu

Get full text

AdaPDTW: An Efficient Abstract-Adaptive Piecewise Dynamic Time Warping for Time Series Classification by Qinglin Cai, Leiying Chen, Jian Shao, Ling Chen

“…We formulate a joint objective function that combines global classification loss with local clustering loss, and introduce an efficient optimization method based on closed-form solutions. …”
Get full text

Storage Temperature Effect on Quality and Shelf-Life of <i>Hericium erinaceus</i> Mushroom by Mafalda Silva, Manuela Vida, Ana Cristina Ramos, Fernando J. Lidon, Fernando H. Reboredo, Elsa M. Gonçalves

“…However, higher temperatures promoted antioxidant activity and total phenolic content, likely due to moisture loss and oxidative stress. These findings highlight the critical role of low-temperature storage in preserving both the physicochemical integrity and functional bioactivity of <i>H. erinaceus</i>, and suggest further research into packaging solutions and preservation strategies to optimize the post-harvest handling of <i>H. erinaceus</i>.…”
Get full text

Influence of Prosthetic Emergence Profile on Peri-Implant Marginal Bone Stability: A Comprehensive Review by Rossana Izzetti, Chiara Cinquini, Marco Nisi, Michele Covelli, Fortunato Alfonsi, Antonio Barone

“…Proper maintenance and a continuous follow-up to monitor marginal bone loss are beneficial for obtaining stable and optimal long-term results.…”
Get full text

Convolutional neural network based on transfer learning for discriminating the fermentation degree of black tea by Xuesong Zhu, Zezhong Ding, Mei Wang, Shanjian Liu, Yulong Chen, Chunwang Dong

“…Next, we modified the loss function with PolyLoss and optimizer with AdamW for the student model. …”
Get full text

Density-Aware Differentially Private Textual Perturbations Using Truncated Gumbel Noise by Nan Xu, Oluwaseyi Feyisetan, Abhinav Aggarwal, Zekun Xu, Nathanael Teissier

“…Recently, it was proposed that this effect can be addressed in the text domain by optimizing for the worst case loss function over all possible word substitutions within the training examples. …”
Get full text

Antiplatelet therapy de-escalation in a patient after percutaneous coronary intervention with a high risk of bleeding by A. A. Kassymova, J. A. Mansurova, L. K. Karazhanova, A. A. Chinybayeva

“…The optimal dosage of strong P2Y12 receptor inhibitors, such as ticagrelor or prasugrel is not entirely clear and is especially difficult to define for patients of Asian nationality.The article describes a clinical case of antiplatelet therapy de-escalation, particularly a dose reduction of the potent P2Y12 receptor inhibitor ticagrelor in a patient after percutaneous coronary intervention (PCI) with a high risk of bleeding based on platelet function determination and genetic testing. …”
Get full text

Bubaline tissues-based extracellular matrix scaffolds for tissue regeneration: current use and future prospectives by Naveen Kumar, Vineet Kumar, Anil Kumar Gangwar, Sonal Saxena, Pawan Diwan Singh Raghuvansi, Dayamon D. Mathew, Sameer Shrivastava, Ashwathy Gopinathan

“…No methods of decellularization resulted in disruption of the architecture and loss of surface structure and composition. The acellular ECM scaffolds can create a favorable regenerative microenvironment, promote tissue-specific remodeling, and act as an inductive template for the repair and functional reconstruction. …”
Get full text

Port terminal mobile recognition based on combined YOLOv5s-DeepSort. by Chengzhi Wang, Donghong Chen, Zhen Liu, Yuanhao Li, Yifei Wang, Sanglan Zhao

“…Finally, the original classification loss function was enhanced using a distributed sorting loss approach to mitigate the imbalance among loaded objects and the influence of background variations in the dock image sequence. …”
Get full text