Weighted Hypoxemia Index: An adaptable method for quantifying hypoxemia severity. by Diane C Lim, Cheng-Bang Chen, Ankita Paul, Yujie Wang, Jinyoung Kim, Soonhyun Yook, Emily Y Kim, Edison Q Kim, Anup Das, Medhi Wangpaichitr, Virend K Somers, Chi Hang Lee, Phyllis C Zee, Toshihiro Imamura, Hosung Kim

“…<h4>Objective</h4>To quantitate hypoxemia severity.<h4>Methods</h4>We developed the Weighted Hypoxemia Index to be adapted to different clinical settings by applying 5 steps to the oxygen saturation curve: (1) Identify desaturation/resaturation event [Formula: see text] by setting the upper threshold; (2) Exclude events as artifact by setting a lower threshold; (3) Calculate weighted area for each [Formula: see text] as [Formula: see text]; (4) Calculate a normalization factor [Formula: see text] for each subject; (5) Calculate the Weighted Hypoxemia Index as the summation of all weighted areas multiplied by [Formula: see text]. …”
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Weighted Hypoxemia Index: An adaptable method for quantifying hypoxemia severity by Diane C. Lim, Cheng-Bang Chen, Ankita Paul, Yujie Wang, Jinyoung Kim, Soonhyun Yook, Emily Y. Kim, Edison Q. Kim, Anup Das, Medhi Wangpaichitr, Virend K. Somers, Chi Hang Lee, Phyllis C. Zee, Toshihiro Imamura, Hosung Kim

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Volume-weighted Bellman error method for adaptive meshing in approximate dynamic programming by Leopoldo Armesto, Antonio Sala

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Weighted Geometric Mean (WGM) method: A new chromatic adaptation model. by Che Shen, Mark D Fairchild

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Combined Wind Power Prediction Method Based on CNN-LSTM&GRU with Adaptive Weights by Rui JIA, Guohua YANG, Haofeng ZHENG, Honghao ZHANG, Xuan LIU, Hang YU

“…Then, the CNN-LSTM network is paralleled with a gated recurrent unit (GRU) network. An adaptive weight learning module is employed to select the best weights for the outputs of the CNN-LSTM module and the GRU module. …”
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An Adaptive Linearized Method for Localizing Video Endoscopic Capsule Using Weighted Centroid Algorithm by Umma Hany, Khan A. Wahid

“…The proposed localization system consists of a 3D antenna array (with 8 receiver sensors) and one transmitter embedded inside the electronic capsule. We propose an adaptive linearized method of localization using Weighted Centroid Localization (WCL) where the position is calculated by averaging the weighted sum of the reference positions. …”
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An Adaptive Variable-Weight Combination Forecasting Method for Energy Product Sales Based on Meta-Learning by Meitian Wang

“…To address these problems, this study proposes a dynamic combination forecasting method that can adaptively change the model combination weights according to external environment changes. …”
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Study of the Factors Influencing Cultural Similarity in the Post-Migration Adaptation Process in the Province of Van Using the GWR Method by Çetin Görür, Bahadır Yüzbaşı

“…In this study, the factors influencing cultural similarity in the post-migration adaptation process of individuals migrating from first- and second-degree border provinces to the province of Van were examined using Ordinary Least Squares and Geographically Weighted Regression methods. …”
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Adaptive weighted dual MAML: Proposing a novel method for the automated diagnosis of partial sleep deprivation. by Soraya Khanmohmmadi, Toktam Khatibi, Golnaz Tajeddin, Elham Akhondzadeh, Amir Shojaee

“…To overcome these limitations, we developed a Few-Shot Learning-based Model-Agnostic Meta-Learning (FSL-based MAML) approach aimed at improving classification accuracy and generalization abilities. Our method, Adaptive Weighted Dual MAML, combines two base models-a ResNet and a CNN-Transformer-within the MAML framework, which leverages multi-shot tasks to improve the EEG signal classification.…”
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Adaptive weighted dual MAML: Proposing a novel method for the automated diagnosis of partial sleep deprivation by Soraya Khanmohmmadi, Toktam Khatibi, Golnaz Tajeddin, Elham Akhondzadeh, Amir Shojaee

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Elastic Momentum-Enhanced Adaptive Hybrid Method for Short-Term Load Forecasting by Wenting Zhao, Haoran Xu, Peng Chen, Juan Zhang, Jing Li, Tingting Cai

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Adaptive Multi-Objective Optimization-Based Coverage Path Planning Method for UUVs by Shaojing ZHAO, Songchen FU, Letian BAI, Yutong GUO, Ta LI

“…However, due to environmental uncertainties, motion constraints, and energy limitations, traditional path planning methods struggle to adapt to complex scenarios. This paper proposed an adaptive multi-objective optimization-based coverage path planning method for UUVs, integrating proximal policy optimization(PPO) with a dynamic weight adjustment mechanism. …”
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Method of adaptive knowledge distillation from multi-teacher to student deep learning models by Oleksandr Chaban, Eduard Manziuk, Pavlo Radiuk

“…In this work, we improve multi-teacher knowledge distillation by developing a holistic framework, enhanced multi-teacher knowledge distillation (EMTKD), that synergistically integrates three components: domain adaptation within teacher training, an instance-specific adap-tive weighting mechanism for knowledge fusion, and semi-supervised learning to leverage unlabeled data. …”
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Leveling method for airborne electromagnetic data based on the curvelet transform and adaptive group-sparse variational model by Qiong Zhang, Xin Chen, Haomiao Wang, Zhonghang Ji, Fei Yan, Yunqing Liu

“…To address the challenge of assigning uniform weights to the variational model in the curvelet domain representation of leveling errors, this study adaptively adjusts the weights of different components, effectively isolating the leveling errors from the surveyed data. …”
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A new low-rank adaptation method for brain structure and metastasis segmentation via decoupled principal weight direction and magnitude by Hancan Zhu, Hongxia Yang, Yaqing Wang, Keli Hu, Guanghua He, Jia Zhou, Zhong Li, Alzheimer’s Disease Neuroimaging Initiative

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Adaptive weighted multi-view subspace clustering method for recognizing urban functions from multi-source social sensing data by Qiliang Liu, Zexin Lu, Weihua Huan, Chong Fan

“…Therefore, this study proposes an adaptive weighted multi-view subspace clustering (AWMSC) method. …”
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Omni directional video coding rate distortion optimization method based on weighted-to-spherically-uniform structural similarity by Yufeng ZHOU, Mei YU, Baozhen DU, Yang SONG, Gangyi JIANG

“…Aiming at the shortcomings of the coding rate distortion model in traditional video coding,considering the characteristics of equal rectangular omnidirectional video,a method of omnidirectional video coding rate distortion optimization based on spherical weighted structural similarity (WS-SSIM) was proposed.By considering the distortion of the internal structural similarity of the projection plane and the relationship between the spherical distortion and the projection plane distortion,the “spherical weighted structural similarity” was proposed to describe the degree of distortion of the planar omnidirectional image local block relative to the viewing sphere,which was applied to the rate-distortion optimization process of omnidirectional video coding and adaptive selection of quantization parameters to improve vision-based coding efficiency.The experimental results show that compared with the HEVC video coding standard HM16.9 test platform,the proposed method can save an average of 24.48% code rate under the same visual quality,which indicates that the method has significant performance for improving the omnidirectional video coding rate distortion performance.…”
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A Machine Learning-Based Method for Pig Weight Estimation and the PIGRGB-Weight Dataset by Xintong Ji, Qifeng Li, Kaijun Guo, Weihong Ma, Mingyu Li, Zhankang Xu, Simon X. Yang, Zhiyu Ren

“…This study demonstrates that machine learning methods using RGB image features provide accurate and adaptable results, offering a viable solution for real-time pig weight estimation. …”
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Wind Power Short-Term Prediction Method Based on Time-Domain Dual-Channel Adaptive Learning Model by Haotian Guo, Keng-Weng Lao, Junkun Hao, Xiaorui Hu

“…After TCN-based feature compression, an adaptive weighted early fusion mechanism dynamically optimizes channel weights. …”
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Development of Adaptive Testing Method Based on Neurotechnologies by E. V. Chumakova, D. G. Korneev, M. S. Gasparian

“…The aim of the study is to create neural network models of modules in an adaptive testing system to design an individual testing trajectory.The research article discusses the implementation of an adaptive testing system in terms of introducing artificial neural network modules into its composition, which should solve the problem of choosing a topic and the complexity of the next question, taking into account previous answers and the complexity of previously asked questions, as well as the connectivity of topics and response time as a factor guessing or searching for an answer, thereby forming an individual testing trajectory.Materials and methods. …”
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